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A Framework for P2P Botnets

A Framework for P2P Botnets. Su Chang, Linfeng Zhang, Yong Guan, Thomas E. Daniels Dept of Electrical and Computer Engineering Iowa State University Ames, Iowa 50011, USA. Speaker: Chi-Sheng Chen Date:2010/11/16. Introduction.

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A Framework for P2P Botnets

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  1. A Framework for P2P Botnets Su Chang, Linfeng Zhang, Yong Guan, Thomas E. Daniels Dept of Electrical and Computer Engineering Iowa State University Ames, Iowa 50011, USA Speaker:Chi-Sheng Chen Date:2010/11/16

  2. Introduction Previously, DDoS and spamming were the primary concern, but now applications such as keylogging and click fraud and other “for profit” purposes are becoming a focus of botnets. To make effective countermeasures against botnets, it is very important to not only study the existing ones of various kinds separately,but the inherent relationships among different botnets/worms (since most current botnets make use of worms to propagate), as well as the ones to appear in the

  3. Introduction In this paper, we address the above issues and makecontributions in 1) proposing a general framework for understanding botnet of different kinds; 2) predicting a new botnet from the framework and comparing its performance with known ones. To the best of our knowledge, we are the first to propose the framework for botnets/worms, the lcbot concept in botnet and related fields

  4. Related Work

  5. Related Work Many schemes are proposed in the literature to detect botnets of centralized structure. To summarize, those schemes are based on one or more of the following techniques: DNS inspection DNSBL inspection traffic pattern recognition tempro or spatial correlation

  6. Related Work Encryption, C&C structure (P2P), commonly used protocols for C&C are the main directions of their evolution.Encryption makes identifying botnets more difficult resulting in the inefficacy of schemes based on signatures or abnormal detections using character distribution. C&C by other commonly used protocols makes the communication among bots more covert as it hides its messages among legitimate traffic. Consequently, there are reports of botnets using VoIP, Skype, Gmail, and HTTP in C&C.

  7. Related Work A P2P structure makes the botnet robust and resilient to bot removal/repair. Lists the timeline of captured botnets using P2P. The main ideas is that each bot has a “buddy list” or routing information consisting of IP addresses of n other infected hosts.

  8. Related Work PUSH” based botnets The peerlist construction of supernode in is similar to except that only exchange of peerlist is needed, there is no replacement of newly infected supernodes’ IPs, and only client nodes can infect supernodes. PULL” based botnet The idea of botnet structure in is similar to , except that the clients periodically communicate with any servant bot in their peerlist to grab the command.

  9. Predicting the New Botnet For a network composed of either a worm or a botnet, each infected host i is associated with three parameters psi, pci, and ki, which are defined as follows: • • psi ∈ {0, 1}: “Can the infected host i be a server in the botnet?” • • pci ∈ {0, 1}: “Can infected host i be a client in the botnet?” • • ki: the number of hosts with which an infected host i can communicate.

  10. Predicting the New Botnet From the viewpoint of communication in command delivery, we can integrate various botnets/worms into a framework by setting different value

  11. Predicted Botnet (lcbot) The values of psi and ki are important to current botnets. On one hand, the botmaster wants the number of bots having psi = 1 and ki as low as possible to make the C&C control more covert. On the other hand, given certain portion of bots in the botnet will be turned off or cleaned at any time, these values have to be large enough to maintain connectivity with the remaining botnet. Normally it is expected that attackers can adjust the above values to balance the tradeoff in these proposed botnets under specific situations.

  12. Predicted Botnet (lcbot) The basic concept of lcbot is to consider the botnet being composed of many groups of different group codes, and decouple psi into pisi and posi. Any bot in the lcbot have pisi equal to 1, and the peerlist contains all the other bots in the same group. Within each group, a small number of bots in have posi equal to 1, each of these bots has only one out link to another bot in different groups.

  13. Predicted Botnet (lcbot)

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