Anonysense: privacy-aware people-centric sensing
Proceedings of the 6th international conference on Mobile systems, applications, and services
Social Network Analysis for Information Flow in Disconnected Delay-Tolerant MANETs
IEEE Transactions on Mobile Computing
SMILE: encounter-based trust for mobile social services
Proceedings of the 16th ACM conference on Computer and communications security
Privacy-enhanced social-network routing
Computer Communications
Mitigating the true cost of advertisement-supported "free" mobile applications
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
ACM SIGCOMM Computer Communication Review
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Current mobile opportunistic networks often use social routing protocols to transfer messages among users and to the services. In the face of changing underlying topology, mobility patterns and density of users and their queries, fixed algorithms for user anonymisation cannot provide sufficient level of user anonymity, and adaptive mechanisms for achieving user anonymity are needed. This paper describes a novel flexible and adaptive approach, AdaptAnon that is suitable for dynamic and heterogeneous mobile opportunistic networks. Our approach is multidimensional and combines multiple heuristics based on user profiles, analysis of user connectivity and history of anonymisation in order to predict and decide on the best set of nodes that can help anonymise the sending node. In our demonstration, we show that AdaptAnon achieves high quality of anonymisation in terms of both the number of nodes and the diversity of nodes in the anonymisation layer for varying query intensity and over live San Francisco cab mobility traces while neither decreasing success ratios nor increasing latency. We also compare AdaptAnon to other state of the art single dimensional anonymisation approaches and do real time visualization of performance parameters.