Achieving secure and accurate friend discovery based on friend-of-friend's recommendations

He, Yanlin; Li, Fenghua; Niu, Ben; Hua, Jiafeng

doi:10.1109/icc.2016.7510779

Cited by 3 publications

(1 citation statement)

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“…In [11], the authors propose a method to check users' credibility before they enter a network. In addition, the authors in [12] design a secure recommendation system for mobile users to learn about potential friends opportunistically. Different from the existing works, we employ the dynamic trust degree to classify the recipients and to rank the sensitivity of publisher to information that needs to be published.…”

Section: Introductionmentioning

confidence: 99%

A Probabilistic Privacy Preserving Strategy for Word‐of‐Mouth Social Networks

Jing

Chen

Wen

2018

Wireless Communications and Mobile Computing

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An online social network (OSN) is a platform that makes people communicate with friends, share messages, accelerate business, and enhance teamwork. In the OSN, privacy issues are increasingly concerned, especially in private message leaks in word-of-mouth. A user’s privacy may be leaked out by acquaintances without user’s consent. In this paper, an integrated system is designed to prevent this illegal privacy leak. In particular, we only use the method of space vector model to determine whether the user’s private message is really leaked. Canary traps techniques are used to detect leakers. Then, we define a trust degree mechanism to evaluate trustworthiness of a communicator dynamically. Finally, we set up a new message publishing system to determine who can obtain the message of publisher. Secrecy performance analysis is provided to verify the effectiveness of the proposed message publishing system. Accordingly, a user in social networks can check whether other users are trustworthy before sending their private messages.

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Section: Introductionmentioning

confidence: 99%