Reputation-based systems are used to establish trust among members of on-line communities where parties with no prior knowledge of each other use the feedback from their peers to assess the trust worthiness of the peers in the community. Generally the reputation system in P2P network follows four steps.
Step 1: a requestor r locates available resources sending a broadcast Query message to ask for the files it needs to download. Other peers will answer with a QueryHit message to the requesting node to notify that they have the requested resource.
Step 2: Upon receiving a set of QueryHit messages, r selects an offerer o and polls the community for any available reputation information on o sending a Poll message. As a result of step 2, r receives a set V of votes, some of which express a good opinion while others express a bad one.
step 3: r evaluates the votes to collapse any set of votes that may belong to a clique and explicitly selects a random set of votes for verifying their trustworthiness.
step 4: the set of reputations collected in step 3 is computed into an aggregated community-wide reputation value. Base on this reputation value, the requestor r can take a decision on whether accessing the resource offered by o or not.After accessing the resource r can update its local trust on o (depending on whether the downloaded resource was satisfactory of not).
P2PRep is a reputation-based protocol runs in a completely anonymous P2P networks. In P2PReP, local reputation management and community-wide reputation management are two different levels. Local reputation is defined as one single peer’s opinion of one other peer’s reputation, based on its formal experience. The community reputation means the aggregated general opinion given by multiple peers. P2PRep is generally combine these two factors togeter.
P2Prep works well in the environments of the percentage of malicious peers’ increasing and decreasing by changing well-behaved ones to rogues ones and changing rogue ones into well-behaved ones. As to the turn over case in peers’ population, P2PReP confirms its robust-ness showing a percentage of malicious downloads greater about 1% than scenario with no change.