IEEE 2014 DOTNET MOBILE COMPUTING PROJECTS Preserving location-privacy-in-geosocial-applications
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Published on: Mar 4, 2016
Transcripts - IEEE 2014 DOTNET MOBILE COMPUTING PROJECTS Preserving location-privacy-in-geosocial-applications
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Preserving Location Privacy in Geosocial Applications
Using geosocial applications, such as FourSquare, millions of people interact with
their surroundings through their friends and their recommendations. Without
adequate privacy protection, however, these systems can be easily misused, for
example, to track users or target them for home invasion. In this paper, we
introduce LocX, a novel alternative that provides significantly improvedlocation
privacy without adding uncertainty into query results or relying on strong
assumptions about server security. Our key insight is to apply secure user-specific,
distance-preserving coordinate transformations to all location data shared with the
server. The friends of a user share this user’s secrets so they can apply the same
transformation. This allows all location queries to be evaluated correctly by the
server, but our privacy mechanisms guarantee that servers are unable to see or infer
the actual location data from the transformed data or from the data access. We
show that LocX provides privacy even against a powerful adversary model, and we
use prototype measurements to show that it provides privacy with very little
performance overhead, making it suitable for today’s mobile devices.
Existing systems have mainly taken three approaches to improving user privacy in
Introducing uncertainty or error into location data.
Relying on trusted servers or intermediaries to apply anonymization to user
identities and private data.
Relying on heavy-weight cryptographic or private information retrieval
None of them, however, have proven successful on current application platforms.
Techniques using the first approach fall short because they require both users and
application providers to introduce uncertainty into their data, which degrades the
quality of application results returned to the user. In this approach, there is a
fundamental tradeoff between the amount of error introduced into the time or
location domain, and the amount of privacy granted to the user. Users dislike the
loss of accuracy in results, and application providers have a natural disincentive to
hide user data from themselves, which reduces their ability to monetize the data.
The second approach relies on the trusted proxies or servers in the system to
protect user privacy. This is a risky assumption, since private data can be exposed
by either software bugs and configuration errors at the trusted servers or by
malicious administrators. Finally, relying on heavy-weight cryptographic
mechanisms to obtain provable privacy guarantees are too expensive to deploy on
mobile devices and even on the servers in answering queries such as nearest
neighbor and range queries.
DISADVANTAGES OF EXISTING SYSTEM:
Location data privacy. The servers should not be able to view the content of
data stored at a location.
This new functionality comes with significantly increased risks to personal
In this paper, we propose LocX(short for location to index mapping), a novel
approach to achieving user privacy while maintaining full accuracy in location-based
social applications (LBSAs from here on ward). Our insight is that many
services do not need to resolve distance-based queries between arbitrary pairs of
users, but only between friends interested in each other’s locations and data. Thus,
we can partition location data based on users’ social groups, and then perform
transformations on the location coordinates before storing them on untrusted
servers. A user knows the transformation keys of all her friends, allowing her to
transform her query into the virtual coordinate system that her friends use. Our
coordinate transformations preserve distance metrics, allowing an application
server to perform both point and nearest-neighbor queries correctly on transformed
data. However, the transformation is secure, in that transformed values cannot be
easily associated with real-world locations without a secret, which is only available
to the members of the social group. Finally, transformations are efficient, in that
they incur minimal overhead on the LBSAs. This makes the applications built on
LocX lightweight and suitable for running on today’s mobile devices.
ADVANTAGES OF PROPOSED SYSTEM:
Our goal is to support both query types in an efficient fashion, suitable for
today’s mobile devices.
Flexibility to support point, circular range, and nearest-neighbor queries on
Strong location privacy. The servers processing the data (and the
administrators of these servers) should not be able to learn the history of
locations that a user has visited.
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 1.44 Mb.
Monitor : 15 VGA Colour.
Mouse : Logitech.
Ram : 512 Mb.
Operating system : Windows XP/7.
Coding Language : ASP.net, C#.net
Tool : Visual Studio 2010
Database : SQL SERVER 2008
Krishna P.N. Puttaswamy, Shiyuan Wang, Troy Steinbauer, Divyakant Agrawal,
Fellow, IEEE, Amr El Abbadi, Christopher Kruegel, and Ben Y.
Zhao,“Preserving Location Privacy in Geosocial Applications”, IEEE
TRANSACTIONS ON MOBILE COMPUTING,VOL. 13,NO. 1, JANUARY