際際滷shows by User: skrasser / http://www.slideshare.net/images/logo.gif 際際滷shows by User: skrasser / Mon, 31 Aug 2020 17:17:26 GMT 際際滷Share feed for 際際滷shows by User: skrasser Of Search Lights and Blind Spots: Machine Learning in Cybersecurity /slideshow/of-search-lights-and-blind-spots-machine-learning-in-cybersecurity/238343962 csraisa3-200831171726
Talk at the Workshop for Robustness of AI Systems Against Adversarial Attacks 2020 (RAISA3) https://www.skrasser.com/blog/2020/08/31/adversarial-machine-learning-and-robust-classification/]]>
Talk at the Workshop for Robustness of AI Systems Against Adversarial Attacks 2020 (RAISA3) https://www.skrasser.com/blog/2020/08/31/adversarial-machine-learning-and-robust-classification/]]> Mon, 31 Aug 2020 17:17:26 GMT /slideshow/of-search-lights-and-blind-spots-machine-learning-in-cybersecurity/238343962 skrasser@slideshare.net(skrasser) Of Search Lights and Blind Spots: Machine Learning in Cybersecurity skrasser Talk at the Workshop for Robustness of AI Systems Against Adversarial Attacks 2020 (RAISA3) https://www.skrasser.com/blog/2020/08/31/adversarial-machine-learning-and-robust-classification/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/csraisa3-200831171726-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Talk at the Workshop for Robustness of AI Systems Against Adversarial Attacks 2020 (RAISA3) https://www.skrasser.com/blog/2020/08/31/adversarial-machine-learning-and-robust-classification/
Of Search Lights and Blind Spots: Machine Learning in Cybersecurity from Sven Krasser
]]> 591 0 https://cdn.slidesharecdn.com/ss_thumbnails/csraisa3-200831171726-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Fundamentals of Machine Learning: Perspectives from a Data Scientist (ISC West 2018) /slideshow/fundamentals-of-machine-learning-perspectives-from-a-data-scientist-isc-west-2018/93851267 iscwest2018krasserml-180414000204
https://www.iscwest.com/en/Sessions/52328/Fundamentals-of-Machine-Learning-Perspectives-from-a-Data-Scientist Abstract: As our world grows more connected, organizations are collecting ever-growing amounts of data. Almost always there are hidden insights in such data that can lead to better outcomes and more value. One important tool to tap into these opportunities is Machine Learning (ML), and across all verticals more and more companies are investing into their ML operations. In this talk, we will take a look at what ML is, what problems it solves, how it is applied, and why companies need to make sure that they have a strategy to employ ML. First, we will explain the relevant fundamental concepts with a focus on supervised learning and geometric models. An intuitive data set with an accessible instance space from the physical world is used to illustrate our ability to classify data. Various models are used and visually represented to explain the underlying algorithms in an accessible fashion. Next, we will discuss how ML is revolutionizing approaches to cybersecurity, and how the cybersecurity industry has been changing its approach to the data it collects. From there, we explore other applications in the larger domain of security. Lastly, we will wrap up with an outlook of where this technology is going and some pointers to get started with employing ML to the data you already collect.]]>
https://www.iscwest.com/en/Sessions/52328/Fundamentals-of-Machine-Learning-Perspectives-from-a-Data-Scientist Abstract: As our world grows more connected, organizations are collecting ever-growing amounts of data. Almost always there are hidden insights in such data that can lead to better outcomes and more value. One important tool to tap into these opportunities is Machine Learning (ML), and across all verticals more and more companies are investing into their ML operations. In this talk, we will take a look at what ML is, what problems it solves, how it is applied, and why companies need to make sure that they have a strategy to employ ML. First, we will explain the relevant fundamental concepts with a focus on supervised learning and geometric models. An intuitive data set with an accessible instance space from the physical world is used to illustrate our ability to classify data. Various models are used and visually represented to explain the underlying algorithms in an accessible fashion. Next, we will discuss how ML is revolutionizing approaches to cybersecurity, and how the cybersecurity industry has been changing its approach to the data it collects. From there, we explore other applications in the larger domain of security. Lastly, we will wrap up with an outlook of where this technology is going and some pointers to get started with employing ML to the data you already collect.]]> Sat, 14 Apr 2018 00:02:04 GMT /slideshow/fundamentals-of-machine-learning-perspectives-from-a-data-scientist-isc-west-2018/93851267 skrasser@slideshare.net(skrasser) Fundamentals of Machine Learning: Perspectives from a Data Scientist (ISC West 2018) skrasser https://www.iscwest.com/en/Sessions/52328/Fundamentals-of-Machine-Learning-Perspectives-from-a-Data-Scientist Abstract: As our world grows more connected, organizations are collecting ever-growing amounts of data. Almost always there are hidden insights in such data that can lead to better outcomes and more value. One important tool to tap into these opportunities is Machine Learning (ML), and across all verticals more and more companies are investing into their ML operations. In this talk, we will take a look at what ML is, what problems it solves, how it is applied, and why companies need to make sure that they have a strategy to employ ML. First, we will explain the relevant fundamental concepts with a focus on supervised learning and geometric models. An intuitive data set with an accessible instance space from the physical world is used to illustrate our ability to classify data. Various models are used and visually represented to explain the underlying algorithms in an accessible fashion. Next, we will discuss how ML is revolutionizing approaches to cybersecurity, and how the cybersecurity industry has been changing its approach to the data it collects. From there, we explore other applications in the larger domain of security. Lastly, we will wrap up with an outlook of where this technology is going and some pointers to get started with employing ML to the data you already collect. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iscwest2018krasserml-180414000204-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> https://www.iscwest.com/en/Sessions/52328/Fundamentals-of-Machine-Learning-Perspectives-from-a-Data-Scientist Abstract: As our world grows more connected, organizations are collecting ever-growing amounts of data. Almost always there are hidden insights in such data that can lead to better outcomes and more value. One important tool to tap into these opportunities is Machine Learning (ML), and across all verticals more and more companies are investing into their ML operations. In this talk, we will take a look at what ML is, what problems it solves, how it is applied, and why companies need to make sure that they have a strategy to employ ML. First, we will explain the relevant fundamental concepts with a focus on supervised learning and geometric models. An intuitive data set with an accessible instance space from the physical world is used to illustrate our ability to classify data. Various models are used and visually represented to explain the underlying algorithms in an accessible fashion. Next, we will discuss how ML is revolutionizing approaches to cybersecurity, and how the cybersecurity industry has been changing its approach to the data it collects. From there, we explore other applications in the larger domain of security. Lastly, we will wrap up with an outlook of where this technology is going and some pointers to get started with employing ML to the data you already collect.
Fundamentals of Machine Learning: Perspectives from a Data Scientist (ISC West 2018) from Sven Krasser
]]> 1010 4 https://cdn.slidesharecdn.com/ss_thumbnails/iscwest2018krasserml-180414000204-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Straight Talk on Machine Learning -- What the Marketing Department Doesnt Want You to Know /slideshow/straight-talk-on-machine-learning-what-the-marketing-department-doesnt-want-you-to-know/78422205 bh2017-170731174903
Sponsored workshop at Black Hat USA 2017 https://www.blackhat.com/us-17/business-hall/schedule/#straight-talk-on-machine-learning----what-the-marketing-department-doesnt-want-you-to-know-8203]]>
Sponsored workshop at Black Hat USA 2017 https://www.blackhat.com/us-17/business-hall/schedule/#straight-talk-on-machine-learning----what-the-marketing-department-doesnt-want-you-to-know-8203]]> Mon, 31 Jul 2017 17:49:02 GMT /slideshow/straight-talk-on-machine-learning-what-the-marketing-department-doesnt-want-you-to-know/78422205 skrasser@slideshare.net(skrasser) Straight Talk on Machine Learning -- What the Marketing Department Doesnt Want You to Know skrasser Sponsored workshop at Black Hat USA 2017 https://www.blackhat.com/us-17/business-hall/schedule/#straight-talk-on-machine-learning----what-the-marketing-department-doesnt-want-you-to-know-8203 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bh2017-170731174903-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Sponsored workshop at Black Hat USA 2017 https://www.blackhat.com/us-17/business-hall/schedule/#straight-talk-on-machine-learning----what-the-marketing-department-doesnt-want-you-to-know-8203
Straight Talk on Machine Learning -- What the Marketing Department Doesnt Want You to Know from Sven Krasser
]]> 1281 4 https://cdn.slidesharecdn.com/ss_thumbnails/bh2017-170731174903-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Practical Machine Learning in Information Security /slideshow/practical-machine-learning-in-information-security/76749943 microsoftsecuritydatasciencecolloquium-170608021729
際際滷s from the Security Data Science Colloquium hosted by Microsoft on June 7, 2017.]]>
際際滷s from the Security Data Science Colloquium hosted by Microsoft on June 7, 2017.]]> Thu, 08 Jun 2017 02:17:29 GMT /slideshow/practical-machine-learning-in-information-security/76749943 skrasser@slideshare.net(skrasser) Practical Machine Learning in Information Security skrasser 際際滷s from the Security Data Science Colloquium hosted by Microsoft on June 7, 2017. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/microsoftsecuritydatasciencecolloquium-170608021729-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s from the Security Data Science Colloquium hosted by Microsoft on June 7, 2017.
Practical Machine Learning in Information Security from Sven Krasser
]]> 3653 3 https://cdn.slidesharecdn.com/ss_thumbnails/microsoftsecuritydatasciencecolloquium-170608021729-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 IJCNN 2017 /slideshow/ijcnn-2017/76041328 ijcnn17-170517021731
My slides from the Cybersecurity Intelligence panel at the International Joint Conference on Neural Networks 2017]]>
My slides from the Cybersecurity Intelligence panel at the International Joint Conference on Neural Networks 2017]]> Wed, 17 May 2017 02:17:31 GMT /slideshow/ijcnn-2017/76041328 skrasser@slideshare.net(skrasser) IJCNN 2017 skrasser My slides from the Cybersecurity Intelligence panel at the International Joint Conference on Neural Networks 2017 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijcnn17-170517021731-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> My slides from the Cybersecurity Intelligence panel at the International Joint Conference on Neural Networks 2017
IJCNN 2017 from Sven Krasser
]]> 1771 2 https://cdn.slidesharecdn.com/ss_thumbnails/ijcnn17-170517021731-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 AICS 2017 /slideshow/aics-2017/71831233 aics17-170206204029
際際滷s from the Applications of AI to Operations panel at the AAAI-17 Workshop on Artificial Intelligence for Cyber Security (AICS). Workshop program: http://www-personal.umich.edu/~arunesh/AICS2017/program.html]]>
際際滷s from the Applications of AI to Operations panel at the AAAI-17 Workshop on Artificial Intelligence for Cyber Security (AICS). Workshop program: http://www-personal.umich.edu/~arunesh/AICS2017/program.html]]> Mon, 06 Feb 2017 20:40:29 GMT /slideshow/aics-2017/71831233 skrasser@slideshare.net(skrasser) AICS 2017 skrasser 際際滷s from the Applications of AI to Operations panel at the AAAI-17 Workshop on Artificial Intelligence for Cyber Security (AICS). Workshop program: http://www-personal.umich.edu/~arunesh/AICS2017/program.html <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aics17-170206204029-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s from the Applications of AI to Operations panel at the AAAI-17 Workshop on Artificial Intelligence for Cyber Security (AICS). Workshop program: http://www-personal.umich.edu/~arunesh/AICS2017/program.html
AICS 2017 from Sven Krasser
]]> 388 2 https://cdn.slidesharecdn.com/ss_thumbnails/aics17-170206204029-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 A Sober Look at Machine Learning /slideshow/a-sober-look-at-machine-learning/64136128 issasoberml-160718185349
際際滷s from July 2016 ISSA OC talk (https://issa-oc.org/event/july-2016-meeting/). Abstract: Machine learning is presently a hot topic in the security industry. On the one side, we have companies praising machine learning as the panacea solving all of our security needs. On the other side, there are companies seeing no merit in machine learning urging us to stay with so-called proven approaches. As always, the truth is a bit more complicated. In this talk, we will take a sober and scientific look at machine learning beyond the hype. First, we will cover what objectives machine learning addresses and how those are accomplished. Next, we will review how machine learning techniques apply to the security space, which problems they solve (and which ones they dont), and what challenges and opportunities they present. Lastly, with these preliminaries addressed, we will dive into what customers need to look for when evaluating machine learning based security products.]]>
際際滷s from July 2016 ISSA OC talk (https://issa-oc.org/event/july-2016-meeting/). Abstract: Machine learning is presently a hot topic in the security industry. On the one side, we have companies praising machine learning as the panacea solving all of our security needs. On the other side, there are companies seeing no merit in machine learning urging us to stay with so-called proven approaches. As always, the truth is a bit more complicated. In this talk, we will take a sober and scientific look at machine learning beyond the hype. First, we will cover what objectives machine learning addresses and how those are accomplished. Next, we will review how machine learning techniques apply to the security space, which problems they solve (and which ones they dont), and what challenges and opportunities they present. Lastly, with these preliminaries addressed, we will dive into what customers need to look for when evaluating machine learning based security products.]]> Mon, 18 Jul 2016 18:53:49 GMT /slideshow/a-sober-look-at-machine-learning/64136128 skrasser@slideshare.net(skrasser) A Sober Look at Machine Learning skrasser 際際滷s from July 2016 ISSA OC talk (https://issa-oc.org/event/july-2016-meeting/). Abstract: Machine learning is presently a hot topic in the security industry. On the one side, we have companies praising machine learning as the panacea solving all of our security needs. On the other side, there are companies seeing no merit in machine learning urging us to stay with so-called proven approaches. As always, the truth is a bit more complicated. In this talk, we will take a sober and scientific look at machine learning beyond the hype. First, we will cover what objectives machine learning addresses and how those are accomplished. Next, we will review how machine learning techniques apply to the security space, which problems they solve (and which ones they dont), and what challenges and opportunities they present. Lastly, with these preliminaries addressed, we will dive into what customers need to look for when evaluating machine learning based security products. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/issasoberml-160718185349-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s from July 2016 ISSA OC talk (https://issa-oc.org/event/july-2016-meeting/). Abstract: Machine learning is presently a hot topic in the security industry. On the one side, we have companies praising machine learning as the panacea solving all of our security needs. On the other side, there are companies seeing no merit in machine learning urging us to stay with so-called proven approaches. As always, the truth is a bit more complicated. In this talk, we will take a sober and scientific look at machine learning beyond the hype. First, we will cover what objectives machine learning addresses and how those are accomplished. Next, we will review how machine learning techniques apply to the security space, which problems they solve (and which ones they dont), and what challenges and opportunities they present. Lastly, with these preliminaries addressed, we will dive into what customers need to look for when evaluating machine learning based security products.
A Sober Look at Machine Learning from Sven Krasser
]]> 1124 3 https://cdn.slidesharecdn.com/ss_thumbnails/issasoberml-160718185349-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Finding the Needle in the IP Stack /slideshow/finding-the-needle-in-the-ip-stack/8575113 krasserrr-403-110712094036-phpapp01
RSA Conference 2010]]>
RSA Conference 2010]]> Tue, 12 Jul 2011 09:40:35 GMT /slideshow/finding-the-needle-in-the-ip-stack/8575113 skrasser@slideshare.net(skrasser) Finding the Needle in the IP Stack skrasser RSA Conference 2010 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/krasserrr-403-110712094036-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> RSA Conference 2010
Finding the Needle in the IP Stack from Sven Krasser
]]> 1175 2 https://cdn.slidesharecdn.com/ss_thumbnails/krasserrr-403-110712094036-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-skrasser-48x48.jpg?cb=1598893975 Experienced leader in network security, reputation systems, cloud intelligence, data mining and analytics, machine learning, big data. www.skrasser.com https://cdn.slidesharecdn.com/ss_thumbnails/csraisa3-200831171726-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/of-search-lights-and-blind-spots-machine-learning-in-cybersecurity/238343962 Of Search Lights and B... https://cdn.slidesharecdn.com/ss_thumbnails/iscwest2018krasserml-180414000204-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/fundamentals-of-machine-learning-perspectives-from-a-data-scientist-isc-west-2018/93851267 Fundamentals of Machin... https://cdn.slidesharecdn.com/ss_thumbnails/bh2017-170731174903-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/straight-talk-on-machine-learning-what-the-marketing-department-doesnt-want-you-to-know/78422205 Straight Talk on Machi...