A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
P2P '01 Proceedings of the First International Conference on Peer-to-Peer Computing
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
Trust Based Incentive in P2P Network
CEC-EAST '04 Proceedings of the E-Commerce Technology for Dynamic E-Business, IEEE International Conference
Using Trust for Secure Collaboration in Uncertain Environments
IEEE Pervasive Computing
A survey of peer-to-peer security issues
ISSS'02 Proceedings of the 2002 Mext-NSF-JSPS international conference on Software security: theories and systems
A survey of trust in internet applications
IEEE Communications Surveys & Tutorials
Trust Mass, Volume and Density - a Novel Approach to Reasoning about Trust
Electronic Notes in Theoretical Computer Science (ENTCS)
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Peer-to-Peer (P2P) networks have emerged as a prime research topic, partly due to the vast unexploited possibilities unrestricted distribution of the workload provides. The main hindrance for unrestricted exploitation of the P2P topology is, due to lack of security-related issues, the gullible attitude taken towards unknown agents. Therefore, the severity of the vulnerabilities caused by gullibility must be mended by other means, for example, by an effective incentive scheme encouraging agents to trustworthy behaviour. This paper presents an abstract model for incentive enhanced trust, to progressively assign the participating agents rights for accessing distributed resources, emphasising consistent behaviour. The model consists of a degrading formula, an illustrative incentive triangle and a best-effort distributed supervision model. Moreover, the same incentive model facilitates anticipation of future behaviour concerning any given agent founded on several distinct agents’ opinion, suggesting that any knowledge concerning the counterpart is better than none.