ºÝºÝߣshows by User: ijnsa / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: ijnsa / Thu, 26 Jun 2025 10:21:57 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: ijnsa 6th International Conference on Natural Language Computing Advances (NLCA 2025) /slideshow/6th-international-conference-on-natural-language-computing-advances-nlca-2025-ea19/281028042 nlca2025cfp-250626102158-9291a199
6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:]]>

6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:]]>
Thu, 26 Jun 2025 10:21:57 GMT /slideshow/6th-international-conference-on-natural-language-computing-advances-nlca-2025-ea19/281028042 ijnsa@slideshare.net(ijnsa) 6th International Conference on Natural Language Computing Advances (NLCA 2025) ijnsa 6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to: <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/nlca2025cfp-250626102158-9291a199-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
6th International Conference on Natural Language Computing Advances (NLCA 2025) from IJNSA Journal
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A MULTI-LAYER HYBRID TEXT STEGANOGRAPHY FOR SECRET COMMUNICATION USING WORD TAGGING AND RGB COLOR CODING /slideshow/a-multi-layer-hybrid-text-steganography-for-secret-communication-using-word-tagging-and-rgb-color-coding/280992965 10618ijnsa01-250625102941-b35aded4
This paper introduces a multi-layer hybrid text steganography approach by utilizing word tagging and recoloring. Existing approaches are planned to be either progressive in getting imperceptibility, or high hiding limit, or robustness. The proposed approach does not use the ordinary sequential inserting process and overcome issues of the current approaches by taking a careful of getting imperceptibility, high hiding limit, and robustness through its hybrid work by using a linguistic technique and a format-based technique. The linguistic technique is used to divide the cover text into embedding layers where each layer consists of a sequence of words that has a single part of speech detected by POS tagger, while the format-based technique is used to recolor the letters of a cover text with a near RGB color coding to embed 12 bits from the secret message in each letter which leads to high hidden capacity and blinds the embedding, moreover, the robustness is accomplished through a multi-layer embedding process, and the generated stego key significantly assists the security of the embedding messages and its size. The experimental results comparison shows that the purpose approach is better than currently developed approaches in providing an ideal balance between imperceptibility, high hiding limit, and robustness criteria. ]]>

This paper introduces a multi-layer hybrid text steganography approach by utilizing word tagging and recoloring. Existing approaches are planned to be either progressive in getting imperceptibility, or high hiding limit, or robustness. The proposed approach does not use the ordinary sequential inserting process and overcome issues of the current approaches by taking a careful of getting imperceptibility, high hiding limit, and robustness through its hybrid work by using a linguistic technique and a format-based technique. The linguistic technique is used to divide the cover text into embedding layers where each layer consists of a sequence of words that has a single part of speech detected by POS tagger, while the format-based technique is used to recolor the letters of a cover text with a near RGB color coding to embed 12 bits from the secret message in each letter which leads to high hidden capacity and blinds the embedding, moreover, the robustness is accomplished through a multi-layer embedding process, and the generated stego key significantly assists the security of the embedding messages and its size. The experimental results comparison shows that the purpose approach is better than currently developed approaches in providing an ideal balance between imperceptibility, high hiding limit, and robustness criteria. ]]>
Wed, 25 Jun 2025 10:29:41 GMT /slideshow/a-multi-layer-hybrid-text-steganography-for-secret-communication-using-word-tagging-and-rgb-color-coding/280992965 ijnsa@slideshare.net(ijnsa) A MULTI-LAYER HYBRID TEXT STEGANOGRAPHY FOR SECRET COMMUNICATION USING WORD TAGGING AND RGB COLOR CODING ijnsa This paper introduces a multi-layer hybrid text steganography approach by utilizing word tagging and recoloring. Existing approaches are planned to be either progressive in getting imperceptibility, or high hiding limit, or robustness. The proposed approach does not use the ordinary sequential inserting process and overcome issues of the current approaches by taking a careful of getting imperceptibility, high hiding limit, and robustness through its hybrid work by using a linguistic technique and a format-based technique. The linguistic technique is used to divide the cover text into embedding layers where each layer consists of a sequence of words that has a single part of speech detected by POS tagger, while the format-based technique is used to recolor the letters of a cover text with a near RGB color coding to embed 12 bits from the secret message in each letter which leads to high hidden capacity and blinds the embedding, moreover, the robustness is accomplished through a multi-layer embedding process, and the generated stego key significantly assists the security of the embedding messages and its size. The experimental results comparison shows that the purpose approach is better than currently developed approaches in providing an ideal balance between imperceptibility, high hiding limit, and robustness criteria. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/10618ijnsa01-250625102941-b35aded4-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This paper introduces a multi-layer hybrid text steganography approach by utilizing word tagging and recoloring. Existing approaches are planned to be either progressive in getting imperceptibility, or high hiding limit, or robustness. The proposed approach does not use the ordinary sequential inserting process and overcome issues of the current approaches by taking a careful of getting imperceptibility, high hiding limit, and robustness through its hybrid work by using a linguistic technique and a format-based technique. The linguistic technique is used to divide the cover text into embedding layers where each layer consists of a sequence of words that has a single part of speech detected by POS tagger, while the format-based technique is used to recolor the letters of a cover text with a near RGB color coding to embed 12 bits from the secret message in each letter which leads to high hidden capacity and blinds the embedding, moreover, the robustness is accomplished through a multi-layer embedding process, and the generated stego key significantly assists the security of the embedding messages and its size. The experimental results comparison shows that the purpose approach is better than currently developed approaches in providing an ideal balance between imperceptibility, high hiding limit, and robustness criteria.
A MULTI-LAYER HYBRID TEXT STEGANOGRAPHY FOR SECRET COMMUNICATION USING WORD TAGGING AND RGB COLOR CODING from IJNSA Journal
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June 2025 - Top 10 Read Articles in Network Security and Its Applications /slideshow/june-2025-top-10-read-articles-in-network-security-and-its-applications/280950038 june2025-top10readarticlesinnetworksecurityitsapplications-250624072526-62e0acd7
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Tue, 24 Jun 2025 07:25:25 GMT /slideshow/june-2025-top-10-read-articles-in-network-security-and-its-applications/280950038 ijnsa@slideshare.net(ijnsa) June 2025 - Top 10 Read Articles in Network Security and Its Applications ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/june2025-top10readarticlesinnetworksecurityitsapplications-250624072526-62e0acd7-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
June 2025 - Top 10 Read Articles in Network Security and Its Applications from IJNSA Journal
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Submit Your Research Articles - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed /slideshow/submit-your-research-articles-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-2f7e/280911949 ijnsacfp-250623092635-8cef7b08
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Mon, 23 Jun 2025 09:26:35 GMT /slideshow/submit-your-research-articles-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-2f7e/280911949 ijnsa@slideshare.net(ijnsa) Submit Your Research Articles - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijnsacfp-250623092635-8cef7b08-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
Submit Your Research Articles - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed from IJNSA Journal
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A LIGHTWEIGHT NETWORK INTRUSION DETECTION SYSTEM FOR SMES /slideshow/a-lightweight-network-intrusion-detection-system-for-smes/280807628 17325ijnsa06-250620100320-e2ab9d95
Small and medium enterprises (SMEs) face increasing cybersecurity threats but often lack access to practical and affordable intrusion detection solutions. This article proposes a lightweight, modular Network Intrusion Detection System (NIDS) tailored to SME environments, emphasizing low resource consumption, ease of deployment, and scalable functionality. The system integrates signature-based detection with streamlined behavioural analysis to deliver strong threat identification without overwhelming infrastructure or administrative capacity. A structured evaluation framework and comparative benchmarking against existing lightweight IDS solutions demonstrate the system’s potential to achieve high detection accuracy, efficient resource usage, and real-time responsiveness. By aligning security capabilities with SME operational realities, the proposed solution aims to bridge a critical gap in cybersecurity resilience, enabling smaller organizations to strengthen their defences and contribute to broader digital ecosystem security.]]>

Small and medium enterprises (SMEs) face increasing cybersecurity threats but often lack access to practical and affordable intrusion detection solutions. This article proposes a lightweight, modular Network Intrusion Detection System (NIDS) tailored to SME environments, emphasizing low resource consumption, ease of deployment, and scalable functionality. The system integrates signature-based detection with streamlined behavioural analysis to deliver strong threat identification without overwhelming infrastructure or administrative capacity. A structured evaluation framework and comparative benchmarking against existing lightweight IDS solutions demonstrate the system’s potential to achieve high detection accuracy, efficient resource usage, and real-time responsiveness. By aligning security capabilities with SME operational realities, the proposed solution aims to bridge a critical gap in cybersecurity resilience, enabling smaller organizations to strengthen their defences and contribute to broader digital ecosystem security.]]>
Fri, 20 Jun 2025 10:03:20 GMT /slideshow/a-lightweight-network-intrusion-detection-system-for-smes/280807628 ijnsa@slideshare.net(ijnsa) A LIGHTWEIGHT NETWORK INTRUSION DETECTION SYSTEM FOR SMES ijnsa Small and medium enterprises (SMEs) face increasing cybersecurity threats but often lack access to practical and affordable intrusion detection solutions. This article proposes a lightweight, modular Network Intrusion Detection System (NIDS) tailored to SME environments, emphasizing low resource consumption, ease of deployment, and scalable functionality. The system integrates signature-based detection with streamlined behavioural analysis to deliver strong threat identification without overwhelming infrastructure or administrative capacity. A structured evaluation framework and comparative benchmarking against existing lightweight IDS solutions demonstrate the system’s potential to achieve high detection accuracy, efficient resource usage, and real-time responsiveness. By aligning security capabilities with SME operational realities, the proposed solution aims to bridge a critical gap in cybersecurity resilience, enabling smaller organizations to strengthen their defences and contribute to broader digital ecosystem security. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17325ijnsa06-250620100320-e2ab9d95-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Small and medium enterprises (SMEs) face increasing cybersecurity threats but often lack access to practical and affordable intrusion detection solutions. This article proposes a lightweight, modular Network Intrusion Detection System (NIDS) tailored to SME environments, emphasizing low resource consumption, ease of deployment, and scalable functionality. The system integrates signature-based detection with streamlined behavioural analysis to deliver strong threat identification without overwhelming infrastructure or administrative capacity. A structured evaluation framework and comparative benchmarking against existing lightweight IDS solutions demonstrate the system’s potential to achieve high detection accuracy, efficient resource usage, and real-time responsiveness. By aligning security capabilities with SME operational realities, the proposed solution aims to bridge a critical gap in cybersecurity resilience, enabling smaller organizations to strengthen their defences and contribute to broader digital ecosystem security.
A LIGHTWEIGHT NETWORK INTRUSION DETECTION SYSTEM FOR SMES from IJNSA Journal
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6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) /slideshow/6th-international-conference-on-advances-in-artificial-intelligence-techniques-arit-2025-5211/280747867 arit2025cfp-250619095024-9e3eea9b
6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its advances. The Conference looks for significant contributions to all major fields of the Artificial Intelligence in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only]]>

6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its advances. The Conference looks for significant contributions to all major fields of the Artificial Intelligence in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only]]>
Thu, 19 Jun 2025 09:50:24 GMT /slideshow/6th-international-conference-on-advances-in-artificial-intelligence-techniques-arit-2025-5211/280747867 ijnsa@slideshare.net(ijnsa) 6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) ijnsa 6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its advances. The Conference looks for significant contributions to all major fields of the Artificial Intelligence in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/arit2025cfp-250619095024-9e3eea9b-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its advances. The Conference looks for significant contributions to all major fields of the Artificial Intelligence in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only
6th International Conference on Advances in Artificial Intelligence Techniques (ArIT 2025) from IJNSA Journal
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STATIC TESTING TOOLS ARCHITECTURE IN OPENMP FOR EXASCALE SYSTEMS /slideshow/static-testing-tools-architecture-in-openmp-for-exascale-systems/280697793 17325ijnsa05-250618072200-a99584d3
In the coming years, exascale systems are expected to be deployed at scale, offering unprecedented computational capabilities. These systems will address many significant challenges related to parallel programming and developer productivity, distinguishing themselves through massive performance and scalability. Considerable research efforts have been dedicated to this field, with a central focus on enhancing system performance. However, the inherent parallelism and complexity of exascale systems introduce new challenges, particularly in programming correctness and efficiency. Modern architectures often employ multicore processors to achieve high performance, increasing the need for robust development tools. In this paper, we present the design of a static testing tool architecture in OpenMP tailored for exascale systems. The primary objective of this architecture is to detect and resolve static errors that may occur during code development. Such errors can affect both program correctness and execution performance. Our proposed architecture aims to assist developers in writing correct and efficient OpenMP code, thereby improving overall software reliability in exascale computing environments. ]]>

In the coming years, exascale systems are expected to be deployed at scale, offering unprecedented computational capabilities. These systems will address many significant challenges related to parallel programming and developer productivity, distinguishing themselves through massive performance and scalability. Considerable research efforts have been dedicated to this field, with a central focus on enhancing system performance. However, the inherent parallelism and complexity of exascale systems introduce new challenges, particularly in programming correctness and efficiency. Modern architectures often employ multicore processors to achieve high performance, increasing the need for robust development tools. In this paper, we present the design of a static testing tool architecture in OpenMP tailored for exascale systems. The primary objective of this architecture is to detect and resolve static errors that may occur during code development. Such errors can affect both program correctness and execution performance. Our proposed architecture aims to assist developers in writing correct and efficient OpenMP code, thereby improving overall software reliability in exascale computing environments. ]]>
Wed, 18 Jun 2025 07:22:00 GMT /slideshow/static-testing-tools-architecture-in-openmp-for-exascale-systems/280697793 ijnsa@slideshare.net(ijnsa) STATIC TESTING TOOLS ARCHITECTURE IN OPENMP FOR EXASCALE SYSTEMS ijnsa In the coming years, exascale systems are expected to be deployed at scale, offering unprecedented computational capabilities. These systems will address many significant challenges related to parallel programming and developer productivity, distinguishing themselves through massive performance and scalability. Considerable research efforts have been dedicated to this field, with a central focus on enhancing system performance. However, the inherent parallelism and complexity of exascale systems introduce new challenges, particularly in programming correctness and efficiency. Modern architectures often employ multicore processors to achieve high performance, increasing the need for robust development tools. In this paper, we present the design of a static testing tool architecture in OpenMP tailored for exascale systems. The primary objective of this architecture is to detect and resolve static errors that may occur during code development. Such errors can affect both program correctness and execution performance. Our proposed architecture aims to assist developers in writing correct and efficient OpenMP code, thereby improving overall software reliability in exascale computing environments. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17325ijnsa05-250618072200-a99584d3-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In the coming years, exascale systems are expected to be deployed at scale, offering unprecedented computational capabilities. These systems will address many significant challenges related to parallel programming and developer productivity, distinguishing themselves through massive performance and scalability. Considerable research efforts have been dedicated to this field, with a central focus on enhancing system performance. However, the inherent parallelism and complexity of exascale systems introduce new challenges, particularly in programming correctness and efficiency. Modern architectures often employ multicore processors to achieve high performance, increasing the need for robust development tools. In this paper, we present the design of a static testing tool architecture in OpenMP tailored for exascale systems. The primary objective of this architecture is to detect and resolve static errors that may occur during code development. Such errors can affect both program correctness and execution performance. Our proposed architecture aims to assist developers in writing correct and efficient OpenMP code, thereby improving overall software reliability in exascale computing environments.
STATIC TESTING TOOLS ARCHITECTURE IN OPENMP FOR EXASCALE SYSTEMS from IJNSA Journal
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International Journal of Network Security & Its Applications (IJNSA) /slideshow/international-journal-of-network-security-its-applications-ijnsa-883e/280657913 ijnsacfp-250617110551-9a0cfb63
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Tue, 17 Jun 2025 11:05:51 GMT /slideshow/international-journal-of-network-security-its-applications-ijnsa-883e/280657913 ijnsa@slideshare.net(ijnsa) International Journal of Network Security & Its Applications (IJNSA) ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijnsacfp-250617110551-9a0cfb63-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
International Journal of Network Security & Its Applications (IJNSA) from IJNSA Journal
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Call for Papers - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed /slideshow/call-for-papers-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-b384/280614964 ijnsacfp-250616110930-dbe92306
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Mon, 16 Jun 2025 11:09:30 GMT /slideshow/call-for-papers-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-b384/280614964 ijnsa@slideshare.net(ijnsa) Call for Papers - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijnsacfp-250616110930-dbe92306-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
Call for Papers - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed from IJNSA Journal
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SCALABILITY ANALYSIS OF IOT-DAG DISTRIBUTED LEDGERS USING PREFERENTIAL ATTACHMENT TOPOLOGY: A SIMULATION APPROACH /slideshow/scalability-analysis-of-iot-dag-distributed-ledgers-using-preferential-attachment-topology-a-simulation-approach/280502208 17325ijnsa04-250613061023-bff30c60
Directed Acyclic Graph (DAG) based Distributed Ledger Technologies (DLTs) are being explored to address the scalability and energy efficiency challenges of traditional blockchain in IoT applications. The objective of this research was to gain insight into algorithms predicting how IoT-DAG DLT horizontal scalability changes with increasing node count in a heterogeneous ecosystem of full and light nodes. It specifically questioned how incorporating preferential attachment topology impacts IoT network scalability and performance, focusing on transaction throughput and energy efficiency. Using an AgentBased Modelling (ABM) simulation, the study evaluated a heterogeneous 1:10 full/light node network with Barabási Albert Preferential Attachment (PA-2.3) across increasing node counts (100-6400). Performance was measured by Confirmed Transactions Per Second (CTPS) and Mean Transaction Latency (MTL). Results showed CTPS scales linearly with node count (R² ≈ 1.000), exhibiting robust predictability. MTL increased logarithmically (R² ≈ 0.970), becoming more predictable as the network grew. Horizontal scalability showed exponential decay. The study confirms that IoT-DAG DLTs with preferential attachment can achieve predictable, near-linear throughput horizontal scalability, highlighting that topology matters and optimising CTPS yields the highest throughput gains. ]]>

Directed Acyclic Graph (DAG) based Distributed Ledger Technologies (DLTs) are being explored to address the scalability and energy efficiency challenges of traditional blockchain in IoT applications. The objective of this research was to gain insight into algorithms predicting how IoT-DAG DLT horizontal scalability changes with increasing node count in a heterogeneous ecosystem of full and light nodes. It specifically questioned how incorporating preferential attachment topology impacts IoT network scalability and performance, focusing on transaction throughput and energy efficiency. Using an AgentBased Modelling (ABM) simulation, the study evaluated a heterogeneous 1:10 full/light node network with Barabási Albert Preferential Attachment (PA-2.3) across increasing node counts (100-6400). Performance was measured by Confirmed Transactions Per Second (CTPS) and Mean Transaction Latency (MTL). Results showed CTPS scales linearly with node count (R² ≈ 1.000), exhibiting robust predictability. MTL increased logarithmically (R² ≈ 0.970), becoming more predictable as the network grew. Horizontal scalability showed exponential decay. The study confirms that IoT-DAG DLTs with preferential attachment can achieve predictable, near-linear throughput horizontal scalability, highlighting that topology matters and optimising CTPS yields the highest throughput gains. ]]>
Fri, 13 Jun 2025 06:10:23 GMT /slideshow/scalability-analysis-of-iot-dag-distributed-ledgers-using-preferential-attachment-topology-a-simulation-approach/280502208 ijnsa@slideshare.net(ijnsa) SCALABILITY ANALYSIS OF IOT-DAG DISTRIBUTED LEDGERS USING PREFERENTIAL ATTACHMENT TOPOLOGY: A SIMULATION APPROACH ijnsa Directed Acyclic Graph (DAG) based Distributed Ledger Technologies (DLTs) are being explored to address the scalability and energy efficiency challenges of traditional blockchain in IoT applications. The objective of this research was to gain insight into algorithms predicting how IoT-DAG DLT horizontal scalability changes with increasing node count in a heterogeneous ecosystem of full and light nodes. It specifically questioned how incorporating preferential attachment topology impacts IoT network scalability and performance, focusing on transaction throughput and energy efficiency. Using an AgentBased Modelling (ABM) simulation, the study evaluated a heterogeneous 1:10 full/light node network with Barabási Albert Preferential Attachment (PA-2.3) across increasing node counts (100-6400). Performance was measured by Confirmed Transactions Per Second (CTPS) and Mean Transaction Latency (MTL). Results showed CTPS scales linearly with node count (R² ≈ 1.000), exhibiting robust predictability. MTL increased logarithmically (R² ≈ 0.970), becoming more predictable as the network grew. Horizontal scalability showed exponential decay. The study confirms that IoT-DAG DLTs with preferential attachment can achieve predictable, near-linear throughput horizontal scalability, highlighting that topology matters and optimising CTPS yields the highest throughput gains. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17325ijnsa04-250613061023-bff30c60-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Directed Acyclic Graph (DAG) based Distributed Ledger Technologies (DLTs) are being explored to address the scalability and energy efficiency challenges of traditional blockchain in IoT applications. The objective of this research was to gain insight into algorithms predicting how IoT-DAG DLT horizontal scalability changes with increasing node count in a heterogeneous ecosystem of full and light nodes. It specifically questioned how incorporating preferential attachment topology impacts IoT network scalability and performance, focusing on transaction throughput and energy efficiency. Using an AgentBased Modelling (ABM) simulation, the study evaluated a heterogeneous 1:10 full/light node network with Barabási Albert Preferential Attachment (PA-2.3) across increasing node counts (100-6400). Performance was measured by Confirmed Transactions Per Second (CTPS) and Mean Transaction Latency (MTL). Results showed CTPS scales linearly with node count (R² ≈ 1.000), exhibiting robust predictability. MTL increased logarithmically (R² ≈ 0.970), becoming more predictable as the network grew. Horizontal scalability showed exponential decay. The study confirms that IoT-DAG DLTs with preferential attachment can achieve predictable, near-linear throughput horizontal scalability, highlighting that topology matters and optimising CTPS yields the highest throughput gains.
SCALABILITY ANALYSIS OF IOT-DAG DISTRIBUTED LEDGERS USING PREFERENTIAL ATTACHMENT TOPOLOGY: A SIMULATION APPROACH from IJNSA Journal
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6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) /slideshow/6th-international-conference-on-artificial-intelligence-and-machine-learning-caiml-2025/280468412 caiml2025cfp-250612071144-b22d7038
6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:]]>

6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:]]>
Thu, 12 Jun 2025 07:11:44 GMT /slideshow/6th-international-conference-on-artificial-intelligence-and-machine-learning-caiml-2025/280468412 ijnsa@slideshare.net(ijnsa) 6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) ijnsa 6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to: <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/caiml2025cfp-250612071144-b22d7038-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
6th International Conference on Artificial Intelligence and Machine Learning (CAIML 2025) from IJNSA Journal
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DEEP LEARNING SOLUTIONS FOR SOURCE CODE VULNERABILITY DETECTION /slideshow/deep-learning-solutions-for-source-code-vulnerability-detection/280395513 17325ijnsa03-250610063900-07866a61
Detecting vulnerabilities in software source code has become a critical aspect of developing secure systems. Traditional methods are increasingly limited in processing complex code structures and generalizing to previously unseen scenarios. In response, advanced deep learning models such as CNN, LSTM, Bi-LSTM, Self-Supervised Learning (SSL), and Transformer have demonstrated potential in automatically capturing the semantic and contextual characteristics embedded in code. This paper serves as both a guided review and a quantitative comparison of the performance of deep learning models for vulnerability detection. Key evaluation indicators, such as accuracy, F1-score, and computational cost, are used to benchmark the models. Results highlight that Transformer achieves the highest accuracy (96.8%), while CNN remains favorable in low-resource environments. The paper concludes with model selection guidelines and suggestions for future enhancements in real-world deployment. ]]>

Detecting vulnerabilities in software source code has become a critical aspect of developing secure systems. Traditional methods are increasingly limited in processing complex code structures and generalizing to previously unseen scenarios. In response, advanced deep learning models such as CNN, LSTM, Bi-LSTM, Self-Supervised Learning (SSL), and Transformer have demonstrated potential in automatically capturing the semantic and contextual characteristics embedded in code. This paper serves as both a guided review and a quantitative comparison of the performance of deep learning models for vulnerability detection. Key evaluation indicators, such as accuracy, F1-score, and computational cost, are used to benchmark the models. Results highlight that Transformer achieves the highest accuracy (96.8%), while CNN remains favorable in low-resource environments. The paper concludes with model selection guidelines and suggestions for future enhancements in real-world deployment. ]]>
Tue, 10 Jun 2025 06:39:00 GMT /slideshow/deep-learning-solutions-for-source-code-vulnerability-detection/280395513 ijnsa@slideshare.net(ijnsa) DEEP LEARNING SOLUTIONS FOR SOURCE CODE VULNERABILITY DETECTION ijnsa Detecting vulnerabilities in software source code has become a critical aspect of developing secure systems. Traditional methods are increasingly limited in processing complex code structures and generalizing to previously unseen scenarios. In response, advanced deep learning models such as CNN, LSTM, Bi-LSTM, Self-Supervised Learning (SSL), and Transformer have demonstrated potential in automatically capturing the semantic and contextual characteristics embedded in code. This paper serves as both a guided review and a quantitative comparison of the performance of deep learning models for vulnerability detection. Key evaluation indicators, such as accuracy, F1-score, and computational cost, are used to benchmark the models. Results highlight that Transformer achieves the highest accuracy (96.8%), while CNN remains favorable in low-resource environments. The paper concludes with model selection guidelines and suggestions for future enhancements in real-world deployment. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17325ijnsa03-250610063900-07866a61-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Detecting vulnerabilities in software source code has become a critical aspect of developing secure systems. Traditional methods are increasingly limited in processing complex code structures and generalizing to previously unseen scenarios. In response, advanced deep learning models such as CNN, LSTM, Bi-LSTM, Self-Supervised Learning (SSL), and Transformer have demonstrated potential in automatically capturing the semantic and contextual characteristics embedded in code. This paper serves as both a guided review and a quantitative comparison of the performance of deep learning models for vulnerability detection. Key evaluation indicators, such as accuracy, F1-score, and computational cost, are used to benchmark the models. Results highlight that Transformer achieves the highest accuracy (96.8%), while CNN remains favorable in low-resource environments. The paper concludes with model selection guidelines and suggestions for future enhancements in real-world deployment.
DEEP LEARNING SOLUTIONS FOR SOURCE CODE VULNERABILITY DETECTION from IJNSA Journal
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Online Paper Submission - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed /slideshow/online-paper-submission-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-dd53/280345095 ijnsacfp-250609070324-772833b3
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Mon, 09 Jun 2025 07:03:24 GMT /slideshow/online-paper-submission-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-dd53/280345095 ijnsa@slideshare.net(ijnsa) Online Paper Submission - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijnsacfp-250609070324-772833b3-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
Online Paper Submission - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed from IJNSA Journal
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ACCESS DETECTION SYSTEM ON WEB CAMERAS AND MICROPHONES /slideshow/access-detection-system-on-web-cameras-and-microphones/280251550 17325ijnsa02-250606085452-6065047c
The proliferation of unauthorized access to webcams and microphones poses significant risks to user privacy and security. Current tools in the market fail to provide comprehensive detection and prevention mechanisms, often lacking hybrid capabilities and quick responses. SilentEye is a proposed system designed to address these gaps by integrating active monitoring, a database-driven detection approach, and automated mitigation features. Built for Windows PCs, SilentEye combines PowerShell scripts, Python-based interfaces, and MySQL databases to detect and respond to both known and unknown threats. This paper outlines the architecture, workflow, and proposed functionality of SilentEye, highlighting its ability to disable compromised devices, notify users of unauthorized access, and adapt dynamically through its evolving database. Though currently limited in platform scope and attack coverage, SilentEye lays the groundwork for a scalable, AI-enhanced detection framework. By addressing critical vulnerabilities and setting new standards for privacy protection, SilentEye demonstrates its potential as a robust tool in the evolving landscape of cybersecurity. Future work will focus on testing, cross-platform expansion, and integration of advanced machine learning techniques to further enhance its capabilities. ]]>

The proliferation of unauthorized access to webcams and microphones poses significant risks to user privacy and security. Current tools in the market fail to provide comprehensive detection and prevention mechanisms, often lacking hybrid capabilities and quick responses. SilentEye is a proposed system designed to address these gaps by integrating active monitoring, a database-driven detection approach, and automated mitigation features. Built for Windows PCs, SilentEye combines PowerShell scripts, Python-based interfaces, and MySQL databases to detect and respond to both known and unknown threats. This paper outlines the architecture, workflow, and proposed functionality of SilentEye, highlighting its ability to disable compromised devices, notify users of unauthorized access, and adapt dynamically through its evolving database. Though currently limited in platform scope and attack coverage, SilentEye lays the groundwork for a scalable, AI-enhanced detection framework. By addressing critical vulnerabilities and setting new standards for privacy protection, SilentEye demonstrates its potential as a robust tool in the evolving landscape of cybersecurity. Future work will focus on testing, cross-platform expansion, and integration of advanced machine learning techniques to further enhance its capabilities. ]]>
Fri, 06 Jun 2025 08:54:52 GMT /slideshow/access-detection-system-on-web-cameras-and-microphones/280251550 ijnsa@slideshare.net(ijnsa) ACCESS DETECTION SYSTEM ON WEB CAMERAS AND MICROPHONES ijnsa The proliferation of unauthorized access to webcams and microphones poses significant risks to user privacy and security. Current tools in the market fail to provide comprehensive detection and prevention mechanisms, often lacking hybrid capabilities and quick responses. SilentEye is a proposed system designed to address these gaps by integrating active monitoring, a database-driven detection approach, and automated mitigation features. Built for Windows PCs, SilentEye combines PowerShell scripts, Python-based interfaces, and MySQL databases to detect and respond to both known and unknown threats. This paper outlines the architecture, workflow, and proposed functionality of SilentEye, highlighting its ability to disable compromised devices, notify users of unauthorized access, and adapt dynamically through its evolving database. Though currently limited in platform scope and attack coverage, SilentEye lays the groundwork for a scalable, AI-enhanced detection framework. By addressing critical vulnerabilities and setting new standards for privacy protection, SilentEye demonstrates its potential as a robust tool in the evolving landscape of cybersecurity. Future work will focus on testing, cross-platform expansion, and integration of advanced machine learning techniques to further enhance its capabilities. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17325ijnsa02-250606085452-6065047c-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The proliferation of unauthorized access to webcams and microphones poses significant risks to user privacy and security. Current tools in the market fail to provide comprehensive detection and prevention mechanisms, often lacking hybrid capabilities and quick responses. SilentEye is a proposed system designed to address these gaps by integrating active monitoring, a database-driven detection approach, and automated mitigation features. Built for Windows PCs, SilentEye combines PowerShell scripts, Python-based interfaces, and MySQL databases to detect and respond to both known and unknown threats. This paper outlines the architecture, workflow, and proposed functionality of SilentEye, highlighting its ability to disable compromised devices, notify users of unauthorized access, and adapt dynamically through its evolving database. Though currently limited in platform scope and attack coverage, SilentEye lays the groundwork for a scalable, AI-enhanced detection framework. By addressing critical vulnerabilities and setting new standards for privacy protection, SilentEye demonstrates its potential as a robust tool in the evolving landscape of cybersecurity. Future work will focus on testing, cross-platform expansion, and integration of advanced machine learning techniques to further enhance its capabilities.
ACCESS DETECTION SYSTEM ON WEB CAMERAS AND MICROPHONES from IJNSA Journal
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7th International Conference on Machine Learning & Applications (CMLA 2025) /slideshow/7th-international-conference-on-machine-learning-applications-cmla-2025/280200438 cmla2025cfp-250605072604-a48fc444
7th International Conference on Machine Learning & Applications (CMLA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. ]]>

7th International Conference on Machine Learning & Applications (CMLA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. ]]>
Thu, 05 Jun 2025 07:26:04 GMT /slideshow/7th-international-conference-on-machine-learning-applications-cmla-2025/280200438 ijnsa@slideshare.net(ijnsa) 7th International Conference on Machine Learning & Applications (CMLA 2025) ijnsa 7th International Conference on Machine Learning & Applications (CMLA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/cmla2025cfp-250605072604-a48fc444-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 7th International Conference on Machine Learning &amp; Applications (CMLA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning &amp; Applications Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.
7th International Conference on Machine Learning & Applications (CMLA 2025) from IJNSA Journal
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DETECTING MALICIOUS URLS:TRENDS, CHALLENGES AND THE ROLE OF BROWSER EXTENSIONS /slideshow/detecting-malicious-urls-trends-challenges-and-the-role-of-browser-extensions/280143924 17325ijnsa01-250604064159-b4a600a4
Malicious URLs continue to pose a significant cybersecurity threat, frequently bypassing conventional detection systems through URL masking and rapid domain switching. This paper proposes a conceptual framework for a lightweight, real-time browser extension designed to block harmful URLs using a dynamically updated blacklist. Beyond detection, the system integrates a user-awareness module offering contextual security guidance and regulatory resources, promoting safer online behavior. The proposed extension aims to address key limitations in existing tools by offering client-side protection with minimal performance overhead and a community driven reporting mechanism. Although the current design employs deterministic logic, future development will incorporate machine learning to enhance adaptability and improve classification of emerging threats. By combining real-time detection, user education, and planned AI integration, the proposed solution contributes a practical and forward-looking approach to strengthening browserlevel web security. ]]>

Malicious URLs continue to pose a significant cybersecurity threat, frequently bypassing conventional detection systems through URL masking and rapid domain switching. This paper proposes a conceptual framework for a lightweight, real-time browser extension designed to block harmful URLs using a dynamically updated blacklist. Beyond detection, the system integrates a user-awareness module offering contextual security guidance and regulatory resources, promoting safer online behavior. The proposed extension aims to address key limitations in existing tools by offering client-side protection with minimal performance overhead and a community driven reporting mechanism. Although the current design employs deterministic logic, future development will incorporate machine learning to enhance adaptability and improve classification of emerging threats. By combining real-time detection, user education, and planned AI integration, the proposed solution contributes a practical and forward-looking approach to strengthening browserlevel web security. ]]>
Wed, 04 Jun 2025 06:41:59 GMT /slideshow/detecting-malicious-urls-trends-challenges-and-the-role-of-browser-extensions/280143924 ijnsa@slideshare.net(ijnsa) DETECTING MALICIOUS URLS:TRENDS, CHALLENGES AND THE ROLE OF BROWSER EXTENSIONS ijnsa Malicious URLs continue to pose a significant cybersecurity threat, frequently bypassing conventional detection systems through URL masking and rapid domain switching. This paper proposes a conceptual framework for a lightweight, real-time browser extension designed to block harmful URLs using a dynamically updated blacklist. Beyond detection, the system integrates a user-awareness module offering contextual security guidance and regulatory resources, promoting safer online behavior. The proposed extension aims to address key limitations in existing tools by offering client-side protection with minimal performance overhead and a community driven reporting mechanism. Although the current design employs deterministic logic, future development will incorporate machine learning to enhance adaptability and improve classification of emerging threats. By combining real-time detection, user education, and planned AI integration, the proposed solution contributes a practical and forward-looking approach to strengthening browserlevel web security. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/17325ijnsa01-250604064159-b4a600a4-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Malicious URLs continue to pose a significant cybersecurity threat, frequently bypassing conventional detection systems through URL masking and rapid domain switching. This paper proposes a conceptual framework for a lightweight, real-time browser extension designed to block harmful URLs using a dynamically updated blacklist. Beyond detection, the system integrates a user-awareness module offering contextual security guidance and regulatory resources, promoting safer online behavior. The proposed extension aims to address key limitations in existing tools by offering client-side protection with minimal performance overhead and a community driven reporting mechanism. Although the current design employs deterministic logic, future development will incorporate machine learning to enhance adaptability and improve classification of emerging threats. By combining real-time detection, user education, and planned AI integration, the proposed solution contributes a practical and forward-looking approach to strengthening browserlevel web security.
DETECTING MALICIOUS URLS:TRENDS, CHALLENGES AND THE ROLE OF BROWSER EXTENSIONS from IJNSA Journal
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Submit Your Research Articles - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed /slideshow/submit-your-research-articles-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-9fc2/280091993 ijnsacfp-250603072606-35d40ce8
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Tue, 03 Jun 2025 07:26:06 GMT /slideshow/submit-your-research-articles-international-journal-of-network-security-its-applications-ijnsa-era-wjci-indexed-9fc2/280091993 ijnsa@slideshare.net(ijnsa) Submit Your Research Articles - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijnsacfp-250603072606-35d40ce8-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
Submit Your Research Articles - International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed from IJNSA Journal
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International Journal of Network Security & Its Applications (IJNSA) - Current Issue: May 2025, Volume 17, Number 3 /slideshow/international-journal-of-network-security-its-applications-ijnsa-current-issue-may-2025-volume-17-number-3/280033829 ijnsatoc-ijnsamay25-250602072443-a262712e
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>

The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.]]>
Mon, 02 Jun 2025 07:24:43 GMT /slideshow/international-journal-of-network-security-its-applications-ijnsa-current-issue-may-2025-volume-17-number-3/280033829 ijnsa@slideshare.net(ijnsa) International Journal of Network Security & Its Applications (IJNSA) - Current Issue: May 2025, Volume 17, Number 3 ijnsa The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijnsatoc-ijnsamay25-250602072443-a262712e-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The International Journal of Network Security &amp; Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security &amp; its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
International Journal of Network Security & Its Applications (IJNSA) - Current Issue: May 2025, Volume 17, Number 3 from IJNSA Journal
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6th International Conference on Natural Language Computing Advances (NLCA 2025) /slideshow/6th-international-conference-on-natural-language-computing-advances-nlca-2025/279856740 nlca2025cfp-250529101402-7496690d
6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:]]>

6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:]]>
Thu, 29 May 2025 10:14:02 GMT /slideshow/6th-international-conference-on-natural-language-computing-advances-nlca-2025/279856740 ijnsa@slideshare.net(ijnsa) 6th International Conference on Natural Language Computing Advances (NLCA 2025) ijnsa 6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to: <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/nlca2025cfp-250529101402-7496690d-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 6th International Conference on Natural Language Computing Advances (NLCA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:
6th International Conference on Natural Language Computing Advances (NLCA 2025) from IJNSA Journal
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A TIERED BLOCKCHAIN FRAMEWORK FOR VEHICULAR FORENSICS /slideshow/a-tiered-blockchain-framework-for-vehicular-forensics-9966/279797393 10518ijnsa03-250528105247-8f92ad5e
In this paper, we present a tiered vehicular forensics framework based on permission BlockChain. We integrate all entities involved in the forensics process and record their interactions in the BlockChain to generate comprehensive evidence for settling disputes and appropriating blame. We incorporate a watchdog entity in our tiered framework to prevent collusive tendencies of potentiality liable entities and to prevent exploitation of evidence. Also, we incorporate a state mechanism to prove the state of a smart vehicle when an accident occurs. Furthermore, we conduct a security analysis to demonstrate the resilience of our framework against identified attacks and describe security mechanisms used to achieve key requirements for vehicular forensics. Finally, we comparatively evaluate our framework against existing proposals. ]]>

In this paper, we present a tiered vehicular forensics framework based on permission BlockChain. We integrate all entities involved in the forensics process and record their interactions in the BlockChain to generate comprehensive evidence for settling disputes and appropriating blame. We incorporate a watchdog entity in our tiered framework to prevent collusive tendencies of potentiality liable entities and to prevent exploitation of evidence. Also, we incorporate a state mechanism to prove the state of a smart vehicle when an accident occurs. Furthermore, we conduct a security analysis to demonstrate the resilience of our framework against identified attacks and describe security mechanisms used to achieve key requirements for vehicular forensics. Finally, we comparatively evaluate our framework against existing proposals. ]]>
Wed, 28 May 2025 10:52:47 GMT /slideshow/a-tiered-blockchain-framework-for-vehicular-forensics-9966/279797393 ijnsa@slideshare.net(ijnsa) A TIERED BLOCKCHAIN FRAMEWORK FOR VEHICULAR FORENSICS ijnsa In this paper, we present a tiered vehicular forensics framework based on permission BlockChain. We integrate all entities involved in the forensics process and record their interactions in the BlockChain to generate comprehensive evidence for settling disputes and appropriating blame. We incorporate a watchdog entity in our tiered framework to prevent collusive tendencies of potentiality liable entities and to prevent exploitation of evidence. Also, we incorporate a state mechanism to prove the state of a smart vehicle when an accident occurs. Furthermore, we conduct a security analysis to demonstrate the resilience of our framework against identified attacks and describe security mechanisms used to achieve key requirements for vehicular forensics. Finally, we comparatively evaluate our framework against existing proposals. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/10518ijnsa03-250528105247-8f92ad5e-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this paper, we present a tiered vehicular forensics framework based on permission BlockChain. We integrate all entities involved in the forensics process and record their interactions in the BlockChain to generate comprehensive evidence for settling disputes and appropriating blame. We incorporate a watchdog entity in our tiered framework to prevent collusive tendencies of potentiality liable entities and to prevent exploitation of evidence. Also, we incorporate a state mechanism to prove the state of a smart vehicle when an accident occurs. Furthermore, we conduct a security analysis to demonstrate the resilience of our framework against identified attacks and describe security mechanisms used to achieve key requirements for vehicular forensics. Finally, we comparatively evaluate our framework against existing proposals.
A TIERED BLOCKCHAIN FRAMEWORK FOR VEHICULAR FORENSICS from IJNSA Journal
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https://cdn.slidesharecdn.com/profile-photo-ijnsa-48x48.jpg?cb=1750933202 The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas. airccse.org/journal/ijnsa.html https://cdn.slidesharecdn.com/ss_thumbnails/nlca2025cfp-250626102158-9291a199-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/6th-international-conference-on-natural-language-computing-advances-nlca-2025-ea19/281028042 6th International Conf... https://cdn.slidesharecdn.com/ss_thumbnails/10618ijnsa01-250625102941-b35aded4-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/a-multi-layer-hybrid-text-steganography-for-secret-communication-using-word-tagging-and-rgb-color-coding/280992965 A MULTI-LAYER HYBRID T... https://cdn.slidesharecdn.com/ss_thumbnails/june2025-top10readarticlesinnetworksecurityitsapplications-250624072526-62e0acd7-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/june-2025-top-10-read-articles-in-network-security-and-its-applications/280950038 June 2025 - Top 10 Rea...