�ݺ�ߣshows by User: ardymulyaiswardani

�ݺ�ߣshows by User: ardymulyaiswardani / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ardymulyaiswardani / Thu, 31 May 2018 07:50:21 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ardymulyaiswardani DENIAL OF SERVICE LOG ANALYSIS USING DENSITY K-MEANS METHOD /slideshow/denial-of-service-log-analysis-using-density-kmeans-method/99699074 18vol83no2-180531075021
Denial of service attacks launched by flooding the data on the ftp server causes the server to be unable to handle requests from legitimate users, one of the techniques in detecting these attacks is by monitoring, but found several problems including the difficulty in distinguishing the attack and with normal data traffic. So that the necessary field studies of triage forensics to get a vital information at the scene that is useful in supporting the overall digital forensics investigation. Triage forensics begins with the log databases which are then performed by using the grouping density k-means algorithm to produce three levels of danger (low, medium and high). Proposed density k-means algorithm using three groups that represent the level of danger. The minimum value, medium, and maximum of the dataset as early centroid, the data which has minimum distance to the centroid value specified will join to form a cluster centroid. Data that has been joined in a cluster and then evaluated the level of density (density) with its center (centroid) using Davies-Bouldin index. Results of clustering that has been done in the dataset resulted in three clusters, but the level of danger which successfully identified only two, namely the level of danger of medium and high, the value of DBI obtained 0.082, indicates that the data used manifold homogeneous, results DBI obtained is also influenced by the selection of the value of the centroid beginning clustering process]]>
Denial of service attacks launched by flooding the data on the ftp server causes the server to be unable to handle requests from legitimate users, one of the techniques in detecting these attacks is by monitoring, but found several problems including the difficulty in distinguishing the attack and with normal data traffic. So that the necessary field studies of triage forensics to get a vital information at the scene that is useful in supporting the overall digital forensics investigation. Triage forensics begins with the log databases which are then performed by using the grouping density k-means algorithm to produce three levels of danger (low, medium and high). Proposed density k-means algorithm using three groups that represent the level of danger. The minimum value, medium, and maximum of the dataset as early centroid, the data which has minimum distance to the centroid value specified will join to form a cluster centroid. Data that has been joined in a cluster and then evaluated the level of density (density) with its center (centroid) using Davies-Bouldin index. Results of clustering that has been done in the dataset resulted in three clusters, but the level of danger which successfully identified only two, namely the level of danger of medium and high, the value of DBI obtained 0.082, indicates that the data used manifold homogeneous, results DBI obtained is also influenced by the selection of the value of the centroid beginning clustering process]]> Thu, 31 May 2018 07:50:21 GMT /slideshow/denial-of-service-log-analysis-using-density-kmeans-method/99699074 ardymulyaiswardani@slideshare.net(ardymulyaiswardani) DENIAL OF SERVICE LOG ANALYSIS USING DENSITY K-MEANS METHOD ardymulyaiswardani Denial of service attacks launched by flooding the data on the ftp server causes the server to be unable to handle requests from legitimate users, one of the techniques in detecting these attacks is by monitoring, but found several problems including the difficulty in distinguishing the attack and with normal data traffic. So that the necessary field studies of triage forensics to get a vital information at the scene that is useful in supporting the overall digital forensics investigation. Triage forensics begins with the log databases which are then performed by using the grouping density k-means algorithm to produce three levels of danger (low, medium and high). Proposed density k-means algorithm using three groups that represent the level of danger. The minimum value, medium, and maximum of the dataset as early centroid, the data which has minimum distance to the centroid value specified will join to form a cluster centroid. Data that has been joined in a cluster and then evaluated the level of density (density) with its center (centroid) using Davies-Bouldin index. Results of clustering that has been done in the dataset resulted in three clusters, but the level of danger which successfully identified only two, namely the level of danger of medium and high, the value of DBI obtained 0.082, indicates that the data used manifold homogeneous, results DBI obtained is also influenced by the selection of the value of the centroid beginning clustering process <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/18vol83no2-180531075021-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Denial of service attacks launched by flooding the data on the ftp server causes the server to be unable to handle requests from legitimate users, one of the techniques in detecting these attacks is by monitoring, but found several problems including the difficulty in distinguishing the attack and with normal data traffic. So that the necessary field studies of triage forensics to get a vital information at the scene that is useful in supporting the overall digital forensics investigation. Triage forensics begins with the log databases which are then performed by using the grouping density k-means algorithm to produce three levels of danger (low, medium and high). Proposed density k-means algorithm using three groups that represent the level of danger. The minimum value, medium, and maximum of the dataset as early centroid, the data which has minimum distance to the centroid value specified will join to form a cluster centroid. Data that has been joined in a cluster and then evaluated the level of density (density) with its center (centroid) using Davies-Bouldin index. Results of clustering that has been done in the dataset resulted in three clusters, but the level of danger which successfully identified only two, namely the level of danger of medium and high, the value of DBI obtained 0.082, indicates that the data used manifold homogeneous, results DBI obtained is also influenced by the selection of the value of the centroid beginning clustering process

DENIAL OF SERVICE LOG ANALYSIS USING DENSITY K-MEANS METHOD from Ardymulya Iswardani

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