Trust evaluation in online social networks for secured user interactions

Online social network is a good platform, where users can share their opinions, ideas, products, and reviews with known (friends and relatives) and unknown users. The growing fame and its easy accesses of new users sometimes lead to security and privacy issues. Many methods are reported so far to address these issues but usage of high complex cryptographic algorithms creating new set of performance related challenges to the mobile users. In this paper, light weight soft security (trust) method is proposed. The proposed method “Trust evaluation in online social networks for secured user interactions-TEOSN” uses user social activities in estimation of his trustworthiness. Each user is observed in terms of followed factor-𝑓𝑑 (his interactions with others) and follower factor-𝑓𝑟 (others interaction with him). The factors 𝑓𝑑 and 𝑓𝑟 are estimated using fuzzy logic and user trust-𝜏 is estimated using beta distribution. The performance of TEOSN is verified theoretically and practically. In experimental results, TEOSN is verified against different number of users; especially it outperformed existing methods in trust computation of target users at 2 to 4-hop distances.