Many different network and host-based security solutions have been developed in the past to counter the threat of autonomously spreading malware. Among the most common detection techniques for such attacks are network traffic analysis and the so-called honeypots. In this thesis, we introduce two new malware detection sensors that make use of the above mentioned techniques. The first sensor called Rishi, passively monitors network traffic to automatically detect bot infected machines. The second sensor called Amun follows the concept of honeypots and detects malware through the emulation of vulnerabilities in network services that are commonly exploited. Both sensors were operated for two years and collected valuable data on autonomously spreading malware in the Internet.From this data we were able to, for example, study the change in exploit behavior and derive predictions about preferred targets of todays' malware.
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He studied computer since at RWTH Aachen University and wrote his diploma thesis on "Advanced Honeynet-based Intrusion Detection". Finally, he finished his Ph.D. at University of Mannheim, researching in the area of honeypots, botnets, spam, and malware analysis.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many different network and host-based security solutions have been developed in the past to counter the threat of autonomously spreading malware. Among the most common detection techniques for such attacks are network traffic analysis and the so-called honeypots. In this thesis, we introduce two new malware detection sensors that make use of the above mentioned techniques. The first sensor called Rishi, passively monitors network traffic to automatically detect bot infected machines. The second sensor called Amun follows the concept of honeypots and detects malware through the emulation of vulnerabilities in network services that are commonly exploited. Both sensors were operated for two years and collected valuable data on autonomously spreading malware in the Internet. From this data we were able to, for example, study the change in exploit behavior and derive predictions about preferred targets of todays' malware. 236 pp. Englisch. N° de réf. du vendeur 9783838127200
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Goebel Jan GerritHe studied computer since at RWTH Aachen University and wrote his diploma thesis on Advanced Honeynet-based Intrusion Detection . Finally, he finished his Ph.D. at University of Mannheim, researching in the area of h. N° de réf. du vendeur 5407035
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Taschenbuch. Etat : Neu. Large-Scale Detection and Measurement of Malicious Content | Jan Gerrit Göbel | Taschenbuch | 236 S. | Englisch | 2015 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838127200 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 106902385
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Many different network and host-based security solutions have been developed in the past to counter the threat of autonomously spreading malware. Among the most common detection techniques for such attacks are network traffic analysis and the so-called honeypots. In this thesis, we introduce two new malware detection sensors that make use of the above mentioned techniques. The first sensor called Rishi, passively monitors network traffic to automatically detect bot infected machines. The second sensor called Amun follows the concept of honeypots and detects malware through the emulation of vulnerabilities in network services that are commonly exploited. Both sensors were operated for two years and collected valuable data on autonomously spreading malware in the Internet. From this data we were able to, for example, study the change in exploit behavior and derive predictions about preferred targets of todays' malware.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 236 pp. Englisch. N° de réf. du vendeur 9783838127200
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many different network and host-based security solutions have been developed in the past to counter the threat of autonomously spreading malware. Among the most common detection techniques for such attacks are network traffic analysis and the so-called honeypots. In this thesis, we introduce two new malware detection sensors that make use of the above mentioned techniques. The first sensor called Rishi, passively monitors network traffic to automatically detect bot infected machines. The second sensor called Amun follows the concept of honeypots and detects malware through the emulation of vulnerabilities in network services that are commonly exploited. Both sensors were operated for two years and collected valuable data on autonomously spreading malware in the Internet. From this data we were able to, for example, study the change in exploit behavior and derive predictions about preferred targets of todays' malware. N° de réf. du vendeur 9783838127200
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