This document proposes a novel time-obfuscated algorithm to protect user trajectory privacy in location-based services. Existing techniques only address snapshot queries and not continuous queries, which allow malicious services to track user trajectories. The proposed algorithm combines r-anonymity, k-anonymity and s-segment paradigms to cloak user locations. It introduces a time-obfuscation technique to randomize query times and prevent services from reconstructing actual trajectories. Experimental results show the technique protects privacy while maintaining query accuracy.

1. GLOBALSOFT TECHNOLOGIES
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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.