Social closeness based clone attack detection for mobile healthcare system

Abstract

Abstract-The explosion of the usage of mobile devices and their rapid deployment of sensing technology provide users with the ability to sense the world. The collected sensing data from the mobile device enabled network can be mined not only for extracting social communities which reflect close relationships or similar behavior patterns among people but also for supporting a broad range of applications including mobile healthcare systems. However, the mobile networks are vulnerable to clone attacks, in which the adversary replicates the legitimate nodes and distributes the clones throughout the network to start a variety of insider attacks. The traditional detection approaches can not address such kind of insider attacks in the mobile device network. (ychen: too vague.) In this paper, we propose a social community based method that exploits the social relationships to detect the clone attack launched to undermine a mobile device enabled disease propagation control framework. We define a new metric called community betweenness, which considers both the community and neighboring information of mobile users. We further propose three methods based on community betweenness to facilitate the detection of the clone attack. An analytical analysis on threshold setting when using community betweeness is provided. We evaluate our clone attack detection scheme through extensive simulations using a trace-driven approach by utilizing data sets collected from mobile phones. The results confirm that our method can detect clone attacks efficiently with high detection ratio and low false positive rate. This strongly indicates the feasibility of exploiting the social community information derived from mobile sensing data for detecting the clone attacks.

SAKE: scalable authenticated key exchange for mobile e‐health networks

“…Mobile e‐Health Networks are heavily relied on technologies that are prone to security threats. MHNs suffer from various attack threats . The intruders including hackers, spites, terrorists and co‐intruders can use operator commands, macro and other methods to break through MHNs with the propose to retaliate, steal confidential information or even fulfill themselves' senses of accomplishment.…”