Method for suppressing malicious behavior based on distributed recommendable reputation in peer-to-peer (P2P) network

Abstract

The invention relates to a method for suppressing a malicious behavior based on distributed recommendable reputation in a peer-to-peer (P2P) network. The method comprises the following steps: acquiring reputation values of all nodes from a list; calculating the direct reputation of the current node pair B according to a time factor; requesting for providing a recommended value for the reputation of the node B; according to a deviant, determining the honesty of the behavior of a recommender and updating the recommended reputation of the recommender; calculating the indirect reputation of the node B; setting weight distribution parameters, and integrating into final reputation; selecting appropriate nodes, connecting, and downloading a resource; grading the resource, thereby reducing the success probability of deception gangs; and in terms of the deviant behavior of a non-malicious node, detecting and compensating the deviant behavior thereof, thereby ensuring that the reputation of a honest node is maintained at a normal level. The strategies are reasonably distributed in a reputation management framework and can adapt to the randomness and dynamicness of the nodes of the P2P network, so that the final reputation of a user is more real-time, accurate and reliable compared with the traditional evaluation system.

Description

technical field [0001] The invention relates to a method in the field of network technology, in particular to a method for curbing malicious behavior based on a distributed recommendable reputation in a P2P network. Background technique [0002] Existing resource sharing systems that use P2P protocols mostly use traditional reputation systems, such as BTCHINA, VERYCD, Grape, and Thunder. Since the protocol itself is not particularly binding on nodes, most of these websites will use some reputation system to encourage nodes to "share" more. [0003] Take the VERYCD client eMule modified according to the emule mod as an example: each node has a point file, and eMule uses an encryption method key handshake to ensure that a certain point belongs to a certain person correctly. Only after this method is verified by eMule, this point is authorized to a specific person, otherwise eMule will not recognize the point of the other party. Points are rewarded to those uploaded nodes, th...

AI Technical Summary

Problems solved by technology

Although this technology also adopts the recommended trust model, it mainly focuses on the resistance to malicious nodes, and lacks the specific classification of malicious behaviors and the consideration of dynamic changes in reputation values.

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