Affiliation:
1. University of Delhi Delhi, India
Abstract
Reputation systems aim to reduce the risk of loss due to untrustworthy participants by providing a mechanism for establishing trustworthiness between mutually unknown online entities in an information asymmetric e-market. These systems encourage honest behavior and discourage malicious behavior of buyer and seller agents by laying a foundation for security and stability in the e-market. However, the success of a reputation system depends on its built-in resilience capabilities to foil various attacks. This paper focuses on how to safeguard buyers from dishonest sellers and advisors by incorporating an attack resilient reputation computation methodology. The objectives of the proposed dynamic reputation system in the distributed environment are to reduce the incentive for behaving dishonestly, and to minimize harm in case of attacks by dishonest participants with the inherent purpose of improving the quality of services in the e-market.
Publisher
Association for Computing Machinery (ACM)
Reference52 articles.
1. Azzedin F. 2010. Identifying honest Recommenders in Reputation Systems. IJRRAS 3(1) April 2010. Azzedin F. 2010. Identifying honest Recommenders in Reputation Systems. IJRRAS 3(1) April 2010.
2. Building the knowledge base of a buyer agent using reinforcement learning techniques
3. Trust and trustworthiness reputations in an investment game
4. A Dynamic Framework of Reputation Systems for an Agent Mediated e-market;Gaur V.;International J. of Computer Science Issues (IJCSI),2011
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献