The Research On P2P Anti-pollution Mechanism Based On User Behavior

P2P (peer to peer) network is a distributed architecture of peer network, each node is both a client and the server. Now P2P technology is widely used in file sharing, distributed computing, collaborative systems, e-commerce, in-depth search engines and other applications .As a major file-sharing platform for the present, research has found that current P2P traffic has been about 70% of the entire Internet traffic and is 350% annual growth rate, P2P traffic has become the Internet main component of Internet traffic. Its development has caused network administrators and academic attention.The vigorous development of P2P applications, P2P technology can not cover up the existence of these hidden dangers. It's the biggest risks is that P2P file sharing pollution problems. When a large number of bait files are injected into the point system, with the user nodes of each other services, file pollution will be occur in each other's point to point sharing system. This behavior is closely related to the user node, because the system is a high degree of openness, freely shaped, any node in the system can be barrier-free play the same role of peer. Significant differences between user nodes, this difference is not only reflected in the user nodes of the objective ability, but also reflected in the behavior of user nodes in the subjective consciousness. How to constraint nodes in P2P file-sharing behavior to combat the pollution problem is the content of this paper - A research on P2P Anti-pollution mechanism based on user behavior.In this paper, by studying the current popularity of Napster, Gnutella, KazaA, NeuroGrid etc and other typical P2P file sharing systems. Analysis and comparison of several popular P2P anti-pollution mechanism, found that most mechanisms are general rules of pollution to explore the file and look for pollution prevention and control methods, but their models without considering the impact of user behavior characteristics. Therefore, for the user's behavioral characteristics, we proposed a research on P2P anti-pollution mechanisms based on user behavior.The main contributions of this paper are as follows:(1) Consider the behavior of the user node of the impact of pollution is proposed based on user behavior (pollution) file propagation model.(2) Through the analysis of the characteristics of network user behaviors found that users after download the file, the awareness of pollution in the file, the speed of remove the pollution, and share tendency of these three aspects has a significant impact in anti-pollution, presented a mechanism based on user behavior information circulars and isolation prevention.(3) By NeuroGrid simulator, built NeuroGrid based on the types of P2P network emulation platform. The establishment of P2P file sharing propagation model, the simulation implements a message notification and isolation prevention mechanism based on user behavior. Experimental results show that the accession with the preventive mechanism, the user enhanced alertness, in a short time, the real number of documents into a monotonically increasing. Pollution file after reaching a peak, their number has been declining will eventually be maintained at the state of 10 %.