Efficient botnet detection based on reputation model and content auditing in P2P networks

Botnet is a number of computers connected through internet that can send malicious content such as spam and virus to other computers without the knowledge of the owners. In peer-to-peer (p2p) architecture, it is very difficult to identify the botnets because it does not have any centralized control. In this paper, we are going to use a security principle called data provenance integrity. It can verify the origin of the data. For this, the certificate of the peers can be exchanged. A reputation based trust model is used for identifying the authenticated peer during file transmission. Here the reputation value of each peer can be calculated and a hash table is used for efficient file searching. The proposed system can also verify the trustworthiness of transmitted data by using content auditing. In this, the data can be checked against trained data set and can identify the malicious content.