Privacy Protection via Anonymization for Multi-type Data In recent years, the information technology has entered new era due to the tremendous growth in novel applications, new systems, and powerful mobile devices. People and organizations are enabled to communicate and share information with each other in much efficient and convenient manner unpredecentedly. However, privacy breach is also made much easier like never before, resulting frequent losses to invididuals or organizations. Under this circumstance, researchers are attracted to provide solutions for privacy protection by designing algorithms and developing systems under various real life situations. We aim to contribute to state-of-the-art privacy protection technologies by presenting new algorithms and analysis for three important types of data, namely micro data, graph data and location data in the applications of micro data publication, graph data publication and location based service. Examples of these three types of data are medical records, social network data, and GPS location data respectively. These three types of data are very typical and widely used in our daily life, and yet they contain sensitive information that is critical to privacy. Although these types of data are used in different applications, the causes for pri- vacy threats and corresponding analysis are based on the same principle. Thus, the protection schemes for thwarting privacy breaches are also very similar. Specifically, we propose and analyze effective privacy protection anonymization schemes for applications that access these three types of data based on the techniques derived from either generalization or perturbation.

Mobile Ad Hoc Networks (MANETs)   Wikipedia Mobile ad-hoc network Wireless ad-hoc network Vehicular ad-hoc network Wireless community network Mesh network Wireless mesh network Mobile phone Wizzy Digital Courier MOBILE ad hoc networks or MANETs are autonomous systems formed by mobile nodes that have no infrastructure support. MANETs are usually characterized by mobility, limited bandwidth, limited power, and using wireless channel for communication.

Publications Mingqiang Xue, Panagiotis Karras, Chedy Raissi, Hung Keng Pung: Utility-driven anonymization in data publishing. CIKM 2011: 2277-2280 Mingqiang Xue, Barbara Carminati, Elena Ferrari: P3D - Privacy-Preserving Path Discovery in Decentralized Online Social Networks. COMPSAC 2011: 48-57 Mingqiang Xue, Panagiotis Papadimitriou, Chedy Raissi, Panos Kalnis, Hung Keng Pung: Distributed Privacy Preserving Data Collection. DASFAA (1) 2011: 93-107 Mingqiang Xue, Panos Kalnis, Hung Keng Pung: Location Diversity: Enhanced Privacy Protection in Location Based Services. LoCA 2009: 70-87 Mingqiang Xue, Inn Inn Er and Winston K. G. Seah, "Analysis of Clustering and Routing Overhead for Clustered Mobile Ad Hoc Networks", Proceedings of the 26th International Conference on Distributed Computing Systems (ICDCS2006), July 4-7, 2006, Lisboa, Portugal.

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Resources Various wireless ad hoc networks links maintained by NIST. The links are grouped by topics. Wireless Ad Hoc Networks Links