Privacy Protection Through k.anonymity in Location.based Services

Abstract The advent of Location-based Services (LBS), especially in wireless communications systems, has raised a growing concern for user about his privacy. As for every location-based query, the user has to reveal his location coordinates (through technologies like Global Positioning Systems); if this information could be revealed to anybody, it becomes a privacy breach. To take care of these issues, several techniques have come up among which k-anonymity has been most widely used and studied in different forms and different contexts. In this paper, we have reviewed the application of k-anonymity for LBS and its recent advancements. While doing so, we have recognized three perspectives for the applicability of k-anonymity for LBS: the application of k-anonymity based on the architecture, based on the algorithms for anonymization, and based on the types of k-anonymity (according to the different query processing techniques). Hence, the review has been done within the framework of these perspectives. These perspectives have covered almost all the aspects of the works which have been reviewed in this paper. This review can arm the privacy providers with the latest techniques and possible modifications in their present techniques.

[1]  Chi-Yin Chow,et al.  A peer-to-peer spatial cloaking algorithm for anonymous location-based service , 2006, GIS '06.

[2]  Mohamed F. Mokbel,et al.  Identifying Unsafe Routes for Network-Based Trajectory Privacy , 2009, SDM.

[3]  Sushil Jajodia,et al.  Anonymity in Location-Based Services: Towards a General Framework , 2007, 2007 International Conference on Mobile Data Management.

[4]  Vijayalakshmi Atluri,et al.  Ensuring Privacy and Security for LBS through Trajectory Partitioning , 2010, 2010 Eleventh International Conference on Mobile Data Management.

[5]  Ling Liu,et al.  Location Privacy in Mobile Systems: A Personalized Anonymization Model , 2005, 25th IEEE International Conference on Distributed Computing Systems (ICDCS'05).

[6]  David Kotz,et al.  AnonySense: Opportunistic and Privacy-Preserving Context Collection , 2009, Pervasive.

[7]  Aris Gkoulalas-Divanis,et al.  A Free Terrain Model for Trajectory K-Anonymity , 2008, DEXA.

[8]  Josep Domingo-Ferrer,et al.  Microaggregation for Database and Location Privacy , 2006, NGITS.

[9]  Baik Hoh.  Achieving guaranteed anonymity in time-series location data , 2008 .

[10]  Panos Kalnis,et al.  PRIVE: anonymous location-based queries in distributed mobile systems , 2007, WWW '07.

[11]  Urs Hengartner,et al.  A distributed k-anonymity protocol for location privacy , 2009, 2009 IEEE International Conference on Pervasive Computing and Communications.

[12]  Walid G. Aref,et al.  Casper*: Query processing for location services without compromising privacy , 2006, TODS.

[13]  Claudio Bettini,et al.  A Comparison of Spatial Generalization Algorithms for LBS Privacy Preservation , 2007, 2007 International Conference on Mobile Data Management.

[14]  Nick Roussopoulos,et al.  K-Nearest Neighbor Search for Moving Query Point , 2001, SSTD.

[15]  Panos Kalnis,et al.  Providing K-Anonymity in location based services , 2010, SKDD.

[16]  Jimeng Sun,et al.  The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries , 2003, VLDB.

[17]  Hanan Samet,et al.  The Design and Analysis of Spatial Data Structures , 1989 .

[18]  Rajeev Motwani,et al.  Approximation Algorithms for k-Anonymity , 2005 .

[19]  Ben Y. Zhao,et al.  StarClique: guaranteeing user privacy in social networks against intersection attacks , 2009, CoNEXT '09.

[20]  Aris Gkoulalas-Divanis,et al.  A k-Anonymity Model for Spatio-Temporal Data , 2007, 2007 IEEE 23rd International Conference on Data Engineering Workshop.

[21]  Agusti Solanas,et al.  Privacy Protection in Location-Based Services Through a Public-Key Privacy Homomorphism , 2007, EuroPKI.

[22]  Yufei Tao,et al.  Continuous Nearest Neighbor Search , 2002, VLDB.

[23]  X. S. Wang,et al.  Preserving Anonymity in Location-based Services When Requests from the Same Issuer May Be Correlated , 2007 .

[24]  Lars Kulik,et al.  Location privacy and location-aware computing , 2006 .

[25]  Chi-Yin Chow,et al.  Enabling Private Continuous Queries for Revealed User Locations , 2007, SSTD.

[26]  Francesco Bonchi,et al.  Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[27]  Jamalul-lail Ab Manan,et al.  Privacy preservation in Location-Based Services (LBS) through Trusted Computing technology , 2009, 2009 IEEE 9th Malaysia International Conference on Communications (MICC).

[28]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

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

[30]  Hassan Takabi,et al.  A collaborative k-anonymity approach for location privacy in location-based services , 2009, 2009 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing.

[31]  Josep Domingo-Ferrer,et al.  Location Privacy in Location-Based Services: Beyond TTP-based Schemes , 2008, PiLBA.

[32]  Tatsuaki Okamoto,et al.  A New Public-Key Cryptosystem as Secure as Factoring , 1998, EUROCRYPT.

[33]  Lars Kulik,et al.  A Formal Model of Obfuscation and Negotiation for Location Privacy , 2005, Pervasive.

[34]  Hua Lu,et al.  Location Privacy Techniques in Client-Server Architectures , 2009, Privacy in Location-Based Applications.

[35]  Ling Liu,et al.  Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms , 2008, IEEE Transactions on Mobile Computing.

[36]  Ernesto Damiani,et al.  Location Privacy Protection Through Obfuscation-Based Techniques , 2007, DBSec.

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

[38]  Panayiotis Bozanis,et al.  A network aware privacy model for online requests in trajectory data , 2009, Data Knowl. Eng..