Reputation Estimation and Query in Peer-to-Peer Networks

 

1.ABSTRACT :

           Many peer-to-peer systems assume that peers are cooperative to share and relay data. But in the open environment of the Internet, there may be uncooperative malicious peers. To detect malicious peers or reward well behaved ones, a  reputation system is often used. In this article we give an overview of P2P reputation systems and investigate two fundamental issues in the design: reputation estimation and query. We classify the state-of-the-art approaches into several categories and study representative examples in each category. We also qualitatively compare them  and outline open issues for future research.

2.EXISTING SYSTEM :

                        In many applications, users may only be willing to participate if a certain amount of anonymity is guaranteed, i.e., there may be uncooperative malicious peers.

                          An estimation method describes how to generate peer reputation based on others’ feedback. Existing estimation methods are categorized into three :

1)   social network,

2)   Probabilistic estimation, and

3)   Game-theoretic

                               In the social network, where all feedback available in the network are aggregated to compute peer reputation, while in probabilistic estimation, sampling of the globally available feedback is used to compute peer reputation. The game-theoretic model, which assumes that peers have rational behavior and uses game theory to build a reputation system.

3.PROPOSED SYSTEM :

                                       We investigate two key issues in P2P reputation systems, reputation estimation and query.

3.1 Reputation estimation:   

                               An estimation method describes how to generate peer reputation based on others’ feedback .In current P2P networks proposed peer estimation depends on ,the first one is the social network, where all feedback available in the network are aggregated to compute peer reputation. The second one is probabilistic estimation, which uses sampling of the globally available feedback to compute peer reputation. The third one is the game-theoretic model, which assumes that peers have rational behavior and uses game theory to build a reputation system.

3.2 Reputation query  :

                     To overcome the drawbacks in centralized and partially centralized approaches another approaches are proposed: 

3.2.1: Structured Overlay :

                            Another class of approaches uses distributed hash table (DHT) to store and search for peer reputation. In DHT each peer is assigned a unique peer ID, and each object is hashed to a key in the same space of peer IDs. The peer with ID equal to the hashed key is responsiblefor storing the location of the object (or the object itself)

3.2.2  Unstructured Overlay :

                                   XREP uses a polling algorithm to choose reliable resource in Gnutella-like file sharing networks.It consists of four operations:

resource searching,vote polling, vote evaluation and resource downloading.

                             

4.HARDWARE REQUIREMENTS:

•         System                : Pentium IV 2.4 GHz.

•         Hard Disk            : 40 GB.

•         Floppy Drive       : 1.44 Mb.

•         Monitor                : 15 VGA Colour.

•         Mouse                 : Logitech.

•         Ram                     : 256 Mb.

5.SOFTWARE REQUIREMENTS:

•         Operating System       : - Windows XP Professional.

•         Front End                     : - Asp .Net 2.0.

•         Coding Language       : - Visual C# .Net.