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 web. a greater figuring out of Botnets may help to coordinate and improve new applied sciences to counter this severe safeguard threat.
Botnet Detection: Countering the most important safety 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 thoughts, in addition to the most recent effects from best educational, and govt researchers.
Botnet Detection: Countering the biggest defense Threatis meant for researchers and practitioners in undefined. This ebook can also be applicable as a secondary textual content or reference e-book for advanced-level scholars in machine science.
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Additional info for Botnet Detection: Countering the Largest Security Threat
However, the localized scanning is quite hard to identify. It is hard to differentiate whether it is a single scanner or it is part of a large botnet. In this chapter, we mainly studied the botnet scanning behaviors, and use its scanning behavior to infer the general properties of botnets. Scanning is the major tool for recruiting new bots. 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.
One possibility is that every bot defer to execute the scan command by random seconds uniformly. The other possibility is that the scan command is the default channel topic . Therefore, after a bot join the channel, it will get the scan command and start scanning. From the data we cannot separate these two cases. In the departure process, we found, in all the long-lived events, many bots depart before the events end. For the events most bots arrived at the beginning part of the events, we observed at the end of event, the bot departure rate increased sharply.
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. • • • How to use botnet scan behavior to infer the general properties of the botnets?