P2P botnet has become a significant threats in security network. In this paper, we propose a new method to detection the P2P botnet through the analysis of the P2P botnet host's life cycle, use the method of off-line detection to find the suspected botnet hosts, and determine the P2P botnet host through online monitoring method. In this way, the efficiency and the accurate rate of P2P botnet detection have raised then only use one method, and reduce the harm of the P2P botnet.

Abstract

With the rising share of Android platform in smartphone market, the number of malware aiming at Android platform is also increasing, and the problems of security threats and privacy disclosure caused by malicious behaviors are becoming more serious. To solve these problems, using static behavioral analysis approach, the thesis analyzes Android malware, summarizes its malicious behaviors and its ways of stealing private data, and puts forward the methods of detection and prevention.

Abstract. Through the research on the life cycle of P2P botnet host, integrated with offline and online modes, this paper proposes a new technique to analyse the captured export network flow, and to detect and monitor the P2P botnet hosts which are on initial stage, trance stage and attack stage, then make the identified P2P botnet hosts live in isolation. The solution can implement the detection of P2P botnet hosts more efficiently and precisely, and reduce the harm of the botnet.