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Building a Scalable System for Stealthy

P2P-Botnet Detection

ABSTRACT

 In this paper we discussed about Peer-to-peer (P2P) because botnets have recently been taken by botmasters for their attack against take-down efforts. Inside being harder to take down, modern bot nets tend to be attack in the way they perform malicious activities, making current detection approaches ineffective. In addition, the rapidly growing volume of network traffic calls for high measurable of detection systems. we propose a new measurable botnet detection system capable of detecting attack P2P botnets.

EXISTING SYSTEM	PROPOSED SYSTEM
EXISTING CONCEPT: - It is worth noting that the legitimate P2P application running on a bot-compromised host may present a significant challenge for the existing detection method such as.   It is mainly due to the fact that the traffic profile of a bot-compromised host might be completely distorted by the legitimate P2P application running on it simultaneously. For instance, in our experiments, when a host is running a Waledac and a Bitorrent application simultaneously.	PROPOSED  CONCEPT : - We need flow clustering-based analysis approach to identify hosts that are mostly likely running P2P applications. approach does not rely on any transport layer  used by  which can be easily violated by P2P applications We do not need training data set to build a machine learning based model as used in because it is very challenging to get traffic of P2P botnets before they are detected in contrast to our approach can detect and profile various P2P applications rather than identifying a specific P2P application.
EXISTING TECHNIQUE:- Bot Graph	PROPOSED TECHNIQUE: - Coarse grained P2P BOTNET detection.
TECHNIQUE DEFINITION:- A bot-compromised host might be completely distorted by the legitimate P2P application running on it simultaneously Servers are that they represent a single point of failure.	TECHNIQUE DEFINITION:- P2P botnets before they are detected in contrast to our approach can detect and profile various P2P applications. Identifying a specific P2P application.
DRAWBACK:- Fundamental disadvantage of centralized C&C.   Servers are that they represent a single point of failure.	ADVANTAGE:- We also identify the performance bottleneck of our system and optimize its scalability. We presented a novel botnet detection system that is able to identify stealthy P2P botnets, whose malicious activities may not be observable.