By Wen Chen Hu; Chung-Wei Lee; Weidong Kou

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IEEE Internet Computing, 4(2), 36-44. , & Kuwabara, K. (2000). Reputation systems. Communications of the ACM, 43(12), 45-48. , & Vetter, R. (2002). Mobile commerce: Framework, applications and networking support. ACM/Kluwer Journal on Mobile Networks and Applications, 7(3), 185-198. , & Liu, L. (2003). A reputation-based trust model for peer-to-peer eCommerce communities. IEEE Conference on Electronic Commerce. 963 virus. htm 2 PalmOS/LibertyCrack virus. htm 3 Funny SMS Messages. html 4 Wireless Application Protocol Forum.

However, the error becomes 100% when k is greater than 50%, which indicates they completely make wrong evaluations by mistaking good peers as untrustworthy and malicious peers as trustworthy. This is particularly interesting because it shows that malicious peers are able to fool the system by overriding the honest feedback provided by good peers when they are the majority. Last, PeerTrust PSM stays effective even with a large percentage of malicious peers. This confirms that the personalized similarity based credibility acts as a very effective measure to filter out dishonest feedback.

It also presents some initial experiments showing the effectiveness, benefit and vulnerabilities of the reputation systems. Finally it discusses a few interesting open issues. Introduction Mobile commerce (m-commerce) communities create enormous opportunities for many, as participants (or peers) can purchase products, access information, and interact with each other from anywhere at any time. However, they also present risks for participants as they are often established dynamically with unknown or unrelated participants.

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