Abdur Rahman Bin Shahid
Florida International University
Abdur Rahman Bin Shahid is a Ph.D. candidate of Computer Science at Florida International University’s School of Computing and Information Sciences under the supervision of Dr. S.S. Iyengar and Dr. Niki Pissinou. He received his B.Sc. in Computer Science and Engineering in December 2011 from Chittagong University of Engineering and Technology, Bangladesh. He worked as a Software Engineer at Samsung Bangladesh R&D Center for two years in his country before joining the SCIS Ph.D. program. His research interests include Location-Based applications, privacy, and security. His current research focuses on privacy preservation in location-based services.
With the rapid advancement of GPS technology, we have observed a tremendous growth of Location-Based Services (LBS). Users enjoy a large array of services through disclosure of their spatial locations. In addition to spatial coordinates, user’s location information also reveals sensitive information. This information can be used for malicious purposes (e.g. revealing user’s interests, home address, relationship etc.). This raises serious privacy concerns. Despite extensive research, the majority of existing methods have either of the following three major weaknesses: (i) they cannot provide strong privacy because of ignoring the large set of information (check-ins, location preference, time-sensitive behavior etc.) available to the LBS; (ii) they impose high communication cost; and (iii) they require a centralized anonymizer.
In this proposal, we study the abovementioned problems and propose a privacy preserving framework for spatial range queries in LBS. This framework has two important attributes: (i) it can ensure personalized privacy preservation by considering the information available to the LBS; and (ii) it does not require a third-party anonymizer. The general model of the framework is as follows. To protect privacy, it cloaks a user’s original location with a concealing region (CR) and ensures that geometrically any location within CR could be the user’s location. That is, the user’s real location in the original query is replaced with the CR. Then, the modified query is submitted to the LBS. Our experimental results show this framework has better privacy and lower communication cost compared to existing state-of-the-art methods.
This proposed framework has three limitations: (i) it neglects the scope of privacy protection through reducing the number of queries submitted to the LBS; (ii) it focuses only on single user’s location privacy; and (iii) it does not consider user’s continuous movement. Based on this observation, we propose to extend this framework in three directions: (i) reducing query submission through cache based mechanism; (ii) privacy preserving group meeting; and (iii) trajectory privacy preservation.