Neighbor Similarity Trust against Sybil Attack in P2P E-Commerce - 2015


Peer to look (P2P) e-commerce applications exist at the sting of the Internet with vulnerabilities to passive and active attacks. These attacks have pushed away potential business companies and people whose aim is to induce the best profit in e-commerce with minimal losses. The attacks occur during interactions between the trading peers as a transaction takes place. In this paper, we propose how to handle Sybil attack, a vigorous attack, in that peers will have bogus and multiple identities to pretend their owns. Most existing work, which concentrates on social networks and trusted certification, has not been in a position to prevent Sybil attack peers from doing transactions. Our work exploits the neighbor similarity trust relationship to deal with Sybil attack. In our approach, duplicated Sybil attack peers will be identified as the neighbor peers become acquainted and hence a lot of trusted to each alternative. Security and performance analysis shows that Sybil attack can be minimized by our proposed neighbor similarity trust.

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