Botnet Detection: Countering the Largest Security Threat by W. Timothy Strayer, David Lapsely, Robert Walsh, Carl

By W. Timothy Strayer, David Lapsely, Robert Walsh, Carl Livadas (auth.), Wenke Lee, Cliff Wang, David Dagon (eds.)

Botnets became the platform of selection for launching assaults and committing fraud on the net. a greater knowing of Botnets may also help to coordinate and increase new applied sciences to counter this severe safeguard threat.

Botnet Detection: Countering the biggest safeguard Threat, a contributed quantity by way of world-class leaders during this box, is predicated at the June 2006 ARO workshop on Botnets. This edited quantity represents the cutting-edge in study on Botnets. It presents botnet detection options and reaction concepts, in addition to the most recent effects from best educational, and govt researchers.

Botnet Detection: Countering the most important safety Threatis meant for researchers and practitioners in undefined. This e-book can also be applicable as a secondary textual content or reference publication for advanced-level scholars in laptop science.

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Extra resources for Botnet Detection: Countering the Largest Security Threat

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In our study we found out that 75% of the successful botnet scanning events followed by the malicious payloads. Understanding the botnet scanning behavior is very important since it will help us to understand how to detect/prevent botnet propagation. Moreover, we can gain insight into the general properties of botnets through this study. Because of the prevalence of botnet scan activities, we believe that scan based botnet property inference is also very general. In this book chapter we mainly wanted to answer the following questions.

Morgan Kaufmann, San Francisco, CA, 2005. 35. Kunikazu Yoda and Hiroaki Etoh. Finding a connection chain for tracing intruders. In Proc. European Symposium on Research in Computer Security, pages 191–205, October 2000. 36. L. Zhang, A. G. Persaud, A. Johnson, and Y. Guan. Detection of stepping stone attacks under delay and chaff perturbations. In Proceedings of the 25th IEEE International Performance Computing and Communications Conference, April 2006. 37. Yin Zhang and Vern Paxson. Detecting stepping stones.

Rob Thormeyer. Hacker arrested for breaching dod systems with ‘botnets’. Government Computer News, November 4, 2005. 33. Xinyuan Wang, Douglas S. Reeves, and S. Felix Wu. Inter-packet delay based correlation for tracing encrypted connections through stepping stones. In Proc. European Symposium on Research in Computer Security, pages 244–263, October 2002. 34. Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques (2nd Edition). Morgan Kaufmann, San Francisco, CA, 2005.

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