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CS Seminar | Efficient Secure Similarity Computation on Encrypted Trajectory Data

Start Date: November 30, 2015
End Date: November 30, 2015



By Professor An Liu (School of Computer Science and Technology in Soochow University )
 
Outsourcing database to clouds is a scalable and cost-effective way for large scale data storage, management, and query processing. Trajectory data contain rich spatio-temporal relationships and reveal many forms of individual sensitive information (e.g., home address, health condition), which necessitate them to be encrypted before being outsourced for privacy concerns. However, efficient query processing over encrypted trajectory data is a very challenging task. Though some achievements have been reported very recently for simple queries (e.g., SQL queries, kNN queries) on encrypted data, there is rather limited progress on secure evaluation of trajectory queries because they are more complex and need special treatment. In this paper, we focus on secure trajectory similarity computation that is the cornerstone of secure trajectory query processing. More specifically, we propose an efficient solution to securely compute the similarity between two encrypted trajectories, which reveals nothing about the trajectories, but the final result. We theoretically prove that our solution is secure against the semi-honest adversaries model as all the intermediate information in our protocols can be simulated in polynomial time. Finally, we empirically study the efficiency of the proposed method, which demonstrates the feasibility of our solution.

Biography: Dr. An Liu is an Associate Professor with the School of Computer Science at Soochow University. He received his PhD degree in Computer Science from both University of Science and Technology of China and City University of Hong Kong in 2008. He has been working in the area of data security and privacy, spatial database, recommender system, and services computing. He has published over 50 papers in the highly referred journals and conferences such as ICDE, DASFAA, WWW, ICWS, and IEEE Transactions. He was the Program Committee Chair of the International Workshops on Big Data Management and Service (BDMS) (2013 & 2016), and the Workshop Chair of the International Conference on Database Systems for Advanced Applications (DASFAA) in 2015.

More Information:

For more info contact: Prof. Xiangliang  Zhang; email: Xiangliang.Zhang@kaust.edu.sa
Date: Monday 30th November 2015
Time: 14:00 - 14:30
Location: Building 1,  Room 3119