2014 IEEE JAVA SERVICE COMPUTING PROJECT A novel time obfuscated algorithm for trajectory privacy protection
- 1. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com A Novel Time-Obfuscated Algorithm for Trajectory Privacy Protection ABSTRACT: Location-based services (LBS) which bring so much convenience to our daily life have been intensively studied over the years. Generally, an LBS query processing can be categorized into snapshot and continuous queries which access user location information and return search results to the users. An LBS has full control of the location information, causing user privacy concerns. If an LBS provider has a malicious intention to breach the user privacy by tracking the users’ routes to their destinations, it incurs a serious threat. Most existing techniques have addressed privacy protection mainly for snapshot queries. However, providing privacy protection for continuous queries is of importance, since a maliciousLBS can easily obtain complete user privacy information by observing a sequence of successive query requests. In this paper, we propose a comprehensive trajectory privacy technique and combine ambient conditions to cloak location information based on the user privacy profile to avoid a malicious LBS reconstructing a user trajectory. We first propose an r-anonymity mechanism which pre-processes a set of similar trajectories R to blur the actual trajectory of a service user. We then combine kanonymity with s road segments to protect the user’s privacy. We introduce a novel time-obfuscated technique which breaks the sequence of the query issuing time for a service user to confuse the LBS so it does not know the user trajectory, by sending a query randomly from a set of locations residing at the different trajectories in R. Despite the randomness incurred from the obfuscation process for providing strong trajectory privacy protection, the experimentalresults show that our
- 2. trajectory privacy technique maintains the correctness of the query results at a competitive computational cost. EXISTING SYSTEM: Most existing techniques have addressed privacy protection mainly for snapshot queries. However, providing privacy protection for continuous queries is of importance, since a malicious LBS can easily obtain complete user privacy information by observing a sequence of successive query requests. The existing techniques for protecting trajectory privacy have some weaknesses. For example, the solution proposed by faces the weakness that when there is an empty set of users on an anonymous trajectory, a malicious LBS can easily speculate the queries sent by the service user and track the trajectories to identify the user PROPOSED SYSTEM: Atime-obfuscated approach is proposed to randomize the sequence of the query issuing time by sending a query randomly from a set of locations residing at the trajectory set R. we have proposed a novel technique for trajectory privacy protection, which considers a long-term disclosure issue as well as the real-time ambient conditions. We introduce a time obfuscated technique to dramatically increase the level of trajectory privacy protection. We allow the users to specify their own privacy profile, and our time obfuscated method integrates the r-anonymity, k-anonymity and ssegment paradigms. As the experimental results have shown, our privacy technique is able to protect the user trajectory and prevent the LBS from reconstructing a user’s actual trajectory and the direction. CONCLUSION: In this paper, we have proposed a novel technique for trajectory privacy protection, which considers a long-term disclosure issue aswell as the real time ambient conditions. We introduce a time-obfuscated technique to dramatically increase the level of trajectory privacy protection. We allow the users to specify their own privacy profile,
- 3. and our timeobfuscated method integrates the r-anonymity, k-anonymity and s-segment paradigms. As the experimental results have shown, our privacy technique is able to protect the user trajectory and prevent the LBS from reconstructing a user’s actual trajectory and the direction. Our method guarantees satisfying the user’s privacy profile for providing stronger privacy protection. SYSTEM CONFIGURATION:- HARDWARE CONFIGURATION:- Processor - Pentium –IV Speed - 1.1 Ghz RAM - 256 MB(min) Hard Disk - 20 GB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA SOFTWARE CONFIGURATION:- Operating System : Windows XP Programming Language : JAVA Java Version : JDK 1.6 & above.