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Botnet Dection system. Introduction  Botnet problem  Challenges for botnet detection.

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Presentation on theme: "Botnet Dection system. Introduction  Botnet problem  Challenges for botnet detection."— Presentation transcript:

1 Botnet Dection system

2 Introduction  Botnet problem  Challenges for botnet detection

3 What Is a Bot/Botnet?  Bot A malware instance that runs autonomously and automatically on a compromised computer (zombie) without owner’s consent Profit-driven, professionally written, widely propagated  Botnet (Bot Army): network of bots controlled by criminals Definition: “A coordinated group of malware instances that are controlled by a botmaster via some C&C channel” Architecture: centralized (e.g., IRC,HTTP), distributed (e.g., P2P) “25% of Internet PCs are part of a botnet!” ( - Vint Cerf)

4 Botnets are used for …  All DDoS attacks  Spam  Click fraud  Information theft  Phishing attacks  Distributing other malware, e.g., spywarePCs are part of a botnet!” ( - Vint Cerf)

5 Challenges for Botnet Detection  Bots are stealthy on the infected machines – We focus on a network-based solution  Bot infection is usually a multi-faceted and multiphased process – Only looking at one specific aspect likely to fail  Bots are dynamically evolving – Static and signature-based approaches may not be effective  Botnets can have very flexible design of C&C channels – A solution very specific to a botnet instance is not desirable

6 Roadmap to three Detection Systems  Bothunter: regardless of the C&C structure and network protocol, if they follow pre-defined infection live cycle  Botsniffer:works for IRC and http, can be extended to detect centralized C&C botnets  Botminer:independent of the protocol and structure

7 BotHunter system-detection on single infected client  Detecting Malware Infection Through IDS-Driven Dialog Correlation  Monitors two-way communication flows between internal networks and the Internet for signs of bot and other malware  Correlates dialog trail of inbound intrusion alarms with outbound communication patterns

8 Bot infection case study: Phatbot

9 Dialog-based Correlation  BotHunter employs an Infection Lifecycle Model to detect host infection behavior

10 Bothunter Architecture

11 Evaluation  Example: http://www.cyber- ta.org/releases/malware- analysis/public/2009-01-13-public/

12 BotSniffer-detection on centralized C&C botnets(IRC,HTTP)  WHY we will focus on C&C?  C&C is essential to a botnet – Without C&C, bots are just discrete, unorganized infections  C&C detection is important – Relatively stable and unlikely to change within botnets – Reveal C&C server and local victims – The weakest link

13 Botnet C&C Communication Example

14 Botnet C&C: Spatial-Temporal Correlation and Similarity

15 BotSniffer Architecture

16 Correlation Engine  Based on two properties  Response crowd – a set of clients that have (message/activity) response behavior -A Dense response crowd: the fraction of clients with message/activity behavior within the group is larger than a threshold (e.g., 0.5).  A homogeneous response crowd – Many members have very similar responses

17 Evaluation

18 Why Botminer?  Botnets can change their C&C content (encryption, etc.), protocols (IRC, HTTP, etc.),structures (P2P, etc.), C&C servers, dialog models  So bothunter, botsniffer systems may be evaded. We need to consider more

19 Revisit Botnet Definition  “A coordinated group of malware instances that are controlled by a botmaster via some C&C channel”  We need to monitor two planes – C-plane (C&C communication plane): “who is talking to whom” – A-plane (malicious activity plane): “who is doing what”

20 C-Plane clustering  What characterizes a communication flow (Cflow) between a local host and a remote service? –

21 A-plane clustering

22 Cross-clustering  Two hosts in the same A-clusters and in at least one common C-cluster are clustered together

23 Botminer Architecture

24 Evaluation Data

25 Evaluation Result(FP)

26 Evaluation Result(Detection Rate)

27 Botnet Detection Systems summary  Bothunter: Vertical Correlation. Correlation on the behaviors of single host.  Botsniffer: Horizontal Correlation. On centralized C&C botnets  Botminer: Extension on Botsniffer, no limitations on the C&C types.

28 Thank you! Questions?


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