Integrating online social networks for enhancing reputation systems of e-commerce

Online shopping has been introduced to Internet users for decades. However, many people are still susceptible to the risks of online shopping. Multiple risk-mitigating solutions have been adopted by most online shopping sites. One such solution, the reputation system, is capable of providing an up-to-date reputation score for every online seller. Nevertheless, it is also vulnerable to fake reviews, which can, in turn, mislead prospective buyers. In order to quench the fire, previous research work mounted friendship annotations to certain reviews, so that the prospective buyers can choose to trust such particular reviews based on their close relationships with the reviewers. In this paper, we extend this friend-annotation scheme by integrating online social networks to online shopping sites. Our protocol is designed to provide three online review submission methods with different privacy-preserving requirements.