Memorizing algorithm: Protecting user privacy using historical information of location-based services

The rapid development of location-based services, which make use of the location information of the user, presents both opportunities and challenges. Users can benefit from these services; however, they must often disclose their location information, which may lead to privacy problems. In this regard, the authors propose a solution with a memorizing algorithm, using trusted middleware that organizes space in an adaptive grid where it cloaks the user's location information in an anonymization area before sending it to the service providers. This newly introduced memorizing algorithm calculates on the spatial grid to decrease the overlapped areas as much as possible, which helps conceal users' locations. This solution protects the user's privacy while using the service, but also against data mining techniques with respect to their history location data. Experimental results with a user activities map establishes this theoretical analyses as well as the practical value of the proposed solution. Copyright © 2010, IGI Global. Author Keywords: Data mining; Location privacy; Location-based services; Memorizing algorithm; Privacy preserving Index Keywords: Adaptive grids; Anonymization; Data mining techniques; Historical information; Location data; Location information; Location privacy; Location-based services; Memorizing algorithm; Overlapped area; Privacy preserving; Privacy problems; Rapid development; Service provider; Spatial grids; User activity; User privacy; Algorithms; Data mining; Information use; Middleware; Data privacy

[1]  Mohamed F. Mokbel,et al.  Privacy in Location-Based Services: State-of-the-Art and Research Directions , 2007, 2007 International Conference on Mobile Data Management.

[2]  Brian Neil Levine,et al.  A protocol for anonymous communication over the Internet , 2000, CCS.

[3]  Marc Langheinrich,et al.  A Privacy Awareness System for Ubiquitous Computing Environments , 2002, UbiComp.

[4]  Marco Gruteser,et al.  Protecting privacy, in continuous location-tracking applications , 2004, IEEE Security & Privacy Magazine.

[5]  Andreas Gutscher.  Coordinate transformation - a solution for the privacy problem of location based services? , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[6]  P. Bellavista,et al.  Efficiently managing location information with privacy requirements in Wi-Fi networks: a middleware approach , 2005, 2005 2nd International Symposium on Wireless Communication Systems.

[7]  Jorge Cuellar,et al.  Location Information Privacy , 2002 .

[8]  Ling Liu,et al.  A Customizable k-Anonymity Model for Protecting Location Privacy , 2004 .

[9]  Jochen Schiller,et al.  Location Based Services , 2004 .

[10]  Sushil Jajodia,et al.  Protecting Privacy Against Location-Based Personal Identification , 2005, Secure Data Management.

[11]  Thomas Brinkhoff,et al.  A Framework for Generating Network-Based Moving Objects , 2002, GeoInformatica.

[12]  Marco Gruteser,et al.  Framework for security and privacy in automotive telematics , 2002, WMC '02.

[13]  Nigel Davies,et al.  Preserving Privacy in Environments with Location-Based Applications , 2003, IEEE Pervasive Comput..

[14]  Axel Küpper.  Location-based Services: Fundamentals and Operation , 2005 .

[15]  Kyriakos Mouratidis,et al.  Preventing Location-Based Identity Inference in Anonymous Spatial Queries , 2007, IEEE Transactions on Knowledge and Data Engineering.

[16]  Vijayalakshmi Atluri,et al.  Efficiently Enforcing the Security and Privacy Policies in a Mobile Environment , 2008, Handbook of Database Security.

[17]  Marco Gruteser,et al.  USENIX Association , 1992 .

[18]  Yufei Tao,et al.  Personalized privacy preservation , 2006, Privacy-Preserving Data Mining.