Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information. However, as recent experience with P2P networks such as Gnutella shows, the anonymous, open nature of these networks offers an almost ideal environment for the spread of self-replicating inauthentic files.

Peer-to-peer (P2P) applications have seen an enormous success, and recently introduced P2P services have reached tens of millions of users. A feature that significantly contributes to the success of many P2P applications is user anonymity. However, anonymity opens the door to possible misuses and abuses, exploiting the P2P network as a way to spread tampered with resources, including Trojan Horses, viruses, and spam. To address this problem we propose a self-regulating system where the P2P network is used to implement a robust reputation mechanism. Reputation sharing is realized through a distributed polling algorithm by which resource requestors can assess the reliability of a resource offered by a participant before initiating the download. This way, spreading of malicious contents will be reduced and eventually blocked. Our approach can be straightforwardly piggybacked on existing P2P protocols and requires modest modifications to current implementations.

It has been reported [26] that life holds but two certainties, death and taxes. And indeed, despite much effort devoted to circumventing both phenomena, it does appear that any society—and in the context of this paper, any large-scale distributed system—must address both death (failure) and the establishment and maintenance of infrastructure (which we assert is a major motivation for taxes, so as to

Peer-to-Peer eCommerce communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such an open community is to use community-based reputations, which can be computed, for example, through feedback about peers' transaction histories. Such reputation information can help estimating the trustworthiness and predicting the future behavior of peers. This paper presents a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system. There are two main features of our model. First, we argue that the trust models based solely on feedback from other peers in the community is inaccurate and ineffective. We introduce three basic trust parameters in computing trustworthiness of peers. In addition to feedback a peer receives through its transactions with other peers, we incorporate the total number of transactions a peer performs, and the credibility of the feedback sources into the model for evaluating the trustworthiness of peers. Second, we introduce two adaptive factors, the transaction context factor and the community context factor, to allow the metric to adapt to different domains and situations and to address common problems encountered in a variety of online communities. We also developed a concrete method to validate the proposed trust model and obtained initial results, showing the feasibility and benefit of our approach.

Decentralized Peer to Peer (P2P) networks offer both opportunities and threats. Its open and decentralized nature makes it extremely susceptible to malicious users spreading harmful content like viruses, trojans or, even just wasting valuable resources of the network. In order to minimize such threats, the use of community-based reputations as trust measurements is fast becoming a de-facto standard. The idea is to dynamically assign each peer a trust rating based on its performance in the network and store it at a suitable place. Any peer wishing to interact with another peer can make an informed decision based on such a rating.

1 Introduction Establishing trust is a fundamental problem in distributedsystems. Peer-to-peer systems, in which service functionality is distributed across clients, eliminate the cen-tralized components that have traditionally functioned as de facto trust brokers, and consequently exacerbate trust-related problems. When peers lack meaningful measures on which to base trust decisions, they end up receivingservices from untrustworthy peers, with e ffects that canrange from wasted resources on mislabeled content to

Reputation systems have been popular in estimating the trustworthiness and predicting the future behavior of nodes in a large-scale distributed system where nodes may transact with one another without prior knowledge or experience. One of the fundamental challenges in distributed reputation management is to understand vulnerabilities and develop mechanisms that can minimize the potential damages to a system by malicious nodes. In this paper, we identify three vulnerabilities that are detrimental to decentralized reputation management and propose TrustGuard -- safeguard framework for providing a highly dependable and yet efficient reputation system. First, we provide a dependable trust model and a set of formal methods to handle strategic malicious nodes that continuously change their behavior to gain unfair advantages in the system. Second, a transaction based reputation system must cope with the vulnerability that malicious nodes may misuse the system by flooding feedbacks with fake transactions. Third, but not least, we identify the importance of filtering out dishonest feedbacks when computing reputation-based trust of a node, including the feedbacks filed by malicious nodes through collusion. Our experiments show that, comparing with existing reputation systems, our framework is highly dependable and effective in countering malicious nodes regarding strategic oscillating behavior, flooding malevolent feedbacks with fake transactions, and dishonest feedbacks.

The field of peer-to-peer reputation systems has exploded in the last few years. Our goal is to organize existing ideas and work to facilitate system design. We present a taxonomy of reputation system components, their properties, and discuss how user behavior and technical constraints can conflict. In our discussion, we describe research that exemplifies compromises made to deliver a useable, implementable system. Ó 2005 Elsevier B.V. All rights reserved.

Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widelyused term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the Semantic Web, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web.

Many peer-to-peer (p2p) system designs assume cooperative environments, with all clients correctly running the same software. Any client who modifies its software may be able to unfairly benefit. This paper considers such fairness issues in the context of p2p multicast streaming services. We present mechanisms that can distinguish nodes with selfish behavior and reduce the quality of service experienced by these selfish nodes from their peers. The peers make their judgments strictly by observing the behavior of their upstream peers. We only require that the multicast trees be periodically rebuilt, increasing the likelihood that a freeloading node's downstream peers will later be upstream of the freeloader and can retaliate by refusing to serve the offender.