Research On Security And Incentive Mechanisms Of Peer-to-Peer Systems

In recent years, the rapid improvement in bandwidth of computer network and capability of personal computer results in a lot of idle network bandwidth, computing power and storage capacity at the edge of computer network, and brings a wide development space to Peer-to-Peer (P2P) systems. The current widely used Client/Server architectures only use a few servers as the center. In contrast, P2P systems utilize the network bandwidth, computing power and storage capacity of personal computers at the edge of network to serve each other. So P2P systems are scalable, robust and cheap. Because P2P systems are also huge, dynamic, asynchronous, and consisted of complicated partners, there are many challenges in designing, development, and maintenance of them. Especially in security and incentive mechanisms, P2P systems are very different from traditional computer systems. In fact, although P2P systems have been the most bandwidth costing systems in Internet now, P2P systems are only limited to some lower security level applications, such as simple P2P file sharing. This is closely related to the lack of applicable security and incentive mechanisms of P2P systems. So the security and incentive mechanisms of P2P systems are investigated in this paper.Reputation system is a major research area of P2P system security, but the existent reputation models are focused on global trust model. As for local trust value, these models only adopt simple methods based on count of success and failure times of P2P transaction to calculate it. Therefore, the local trust value cannot represent the distribution of success and failure in P2P transaction history. Artificial neural networks are introduced in P2P reputation system, and the method of identifying local trust value of P2P systems with neural networks is proposed. P2P transaction result sequence that can represent the P2P transaction history is used as input of neural networks to identify local trust value directly, so the result can be more representative. In addition, it shows an intelligent method of reputation system to use neural networks.ATN (Automated Trust Negotiation) is one of the methods that can carry out reliable access control in P2P systems. But current ATN model is very complex and hard to manage. In fact, there is no really usable ATN system at present. ATLN (Automated Trust Level Negotiation) is proposed. ATLN introduces trust level to extend ATN, and reduces the complexity of the resource access control policy by define the policy with trust level. ATLN is more flexible and manageable than ATN. ATLN fuses ATN and traditional access control model, so it gives a clue of using traditional security mechanisms in P2P systems.Fair resource sharing is one of incentive mechanisms in P2P systems. Inspiring from society where individuals exchange fairly by promising and acting on it, P-Promise, a promise based P2P fair resource sharing protocol is proposed. P-Promise defines promise certificate and a suit of protocol primitives. By using promise certificate and protocol primitives, fair resource sharing ring can be built, and the goal of fair resource sharing can be achieved in P2P systems. The process of building fair resource sharing ring is a process of promising and carrying it out, so P-Promise does not require trusted third parties, certified identities, monetary payment, and symmetric storage relationships. Promise certificate can describe various kinds of resources, so P-Promise can be applied to a wide range of resource sharing.In view of the value of P2P data disaster tolerance, an adaptive P2P data disaster tolerance model is proposed, and a P2P data disaster tolerance system is designed and implemented based on JXTA. The system integrates and verifies the theories proposed in this paper.