Exploiting social relationship for secure routing in mobile social networks
Zhenxiang Gao, Weihua Zhou, Yongming Wang · 2016
Mobile social networks (MSNs) are modern paradigms of delay tolerant networks, which exploit human mobility and consequent wireless contacts between mobile devices to share information in a peer-to-peer manner. Since routing in MSNs depends heavily on the cooperation among participating nodes, selfish or malicious behaviors of nodes impact strongly on the routing performance. In this paper, we introduce the social relationship evaluation method (SRM) for detecting the quality of human social relationship and propose the trustworthy behavior evaluation method (TBM) which exploits recommendations from close friends to detect node's selfish or malicious behaviors. Based on SRM, we define the community of each node as the set of nodes having close social relationships with this node either directly or indirectly, and define the local community centrality to identify influential nodes for message forwarding in the community. Then, we propose SSRS, a novel social-based secure routing strategy, which exploits social relationships to enhance routing security and performance. Simulations have been conducted on the real world data set and results demonstrate that SSRS achieves better performances than the existing algorithms.