GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE ST...
against a powe rful adversary model, and we use prototype measurements to show that it
provides privacy with very little ...
• Floppy Drive: 1.44 Mb.
• Monitor : 14’ Colour Monitor.
• Mouse : Optical Mouse.
• Ram : 512 Mb.
Software Requirement...
of 3

IEEE 2014 DOTNET NETWORKING PROJECTS Preserving location privacy in geosocial applications

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Published on: Mar 4, 2016
Published in: Engineering      
Source: www.slideshare.net


Transcripts - IEEE 2014 DOTNET NETWORKING PROJECTS Preserving location privacy in geosocial applications

  • 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@gmai l.com PRESERVING LOCATION PRIVACY IN GEOSOCIAL APPLICATIONS ABSTRACT: Using geosocial applications, such as Four Square, 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 alte rnative that provides significantly improved location 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
  • 2. against a powe rful 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 System: Using geosocial applications, such as Four Square, 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. Proposed System: In this paper, we introduce LocX, a novel alte rnative that provides significantly improved location 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 powe rful 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. System Specification Hardware Requirements: • System : Pentium IV 2.4 GHz. • Hard Disk : 40 GB.
  • 3. • Floppy Drive: 1.44 Mb. • Monitor : 14’ Colour Monitor. • Mouse : Optical Mouse. • Ram : 512 Mb. Software Requirements: • Operating system : Windows 7. • Coding Language : ASP.Net with C#

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