A Survey On Botnet Detection Approaches In Peer-To-Peer Network

Peer-to-peer network is a decentralized and distributed network where an individual nodes in the network performs as both providers and consumers of resources. This type of network is different from centralized network. In the centralized network, the client requests queries for accessing resources to the central servers. Malware is a harmful effect in the peer-to-peer networks. In the peer-to-peer network, a new type of malware which is called bots has arisen. Bots are distinctive in that they cooperatively preserve communication structures across nodes to robustly distribute commands from a command and control (C&C) node. The capability to organize and upload new commands to bots provides the botnet owner vast power when performing illegal activities, which contains the ability to organize surveillance attacks, execute DDoS extortion, distribution of spam for pay, and phishing. It is very significant for detecting botnets in the peer-to-peer network. In this survey to analyze different methods of detecting peer-to-peer botnets. BotMiner is one of the detection methods in which a group of hosts as bots belonging to the same botnet if they distribute comparable communication patterns. But this detection method is ineffective and there is restricted in scalability. BotGrep is a detection method which analyzes the network flows composed over multiple large networks by analyzing the communication graph formed by overlay networks. In the following survey to analyze different botnet detection methods to improve the detection accuracy in the peer-to-peer network.