HBLP: A Privacy Protection Framework for TIP Attributes in NTTP-Based LBS Systems

Nowadays, location-based services are being widely popularized due to their massive usage in current and emerging technologies. These services are based on searching out areas of interest which are likely to be accessed by users. Despite helping users worldwide, Location Based Services (LBSs) Systems endanger users’ privacy because a user must provide personal information in order to use the services. Users thus become easy prey for assailants to access their social and personal lives. This problem is a giant issue for contemporary technologies because they are increasingly being used with the passage of time. Many existing solutions have attempted to resolve the challenges, but they face some serious dilemmas regarding the preservation of privacy. In order to address the privacy challenges in LBS systems, in this paper we have introduced a new Hierarchy Based Location Privacy (HBLP) model that protects the user’s privacy, including the user’s query time and identity and location information. The proposed model protects the user’s privacy by using pseudo identity exchange, an aggregation protocol, and the concepts of Forest User (FU), Tree User (TU), and Child Users (CU) with k-anonymity and t-closeness, which is a reasonable combination for privacy provision for a user’s query time, identity, and location. In order to evaluate the privacy protection level, we implemented the HBLP model in a Riverbed (Opnet) simulation and compared the results with existing state-of-the-art privacy-provisioning methods. The results showed that HBLP protected all the privacy attributes when a user interacts with an LBS system.

[1]  Stuart J. Barnes.  Location-Based Services: The State of the Art , 2004 .

[2]  Edward Chou.  Location Data and Geo-Indistinguishable Privacy Preserving Protocols , 2017 .

[3]  Ruchika Gupta,et al.  Achieving location privacy through CAST in location based services , 2017, Journal of Communications and Networks.

[4]  Adnan Ahmed Abi Sen,et al.  Improving Privacy and Security of User Data in Location Based Services , 2018, Int. J. Ambient Comput. Intell..

[5]  Zheng Qin,et al.  An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme , 2018, Secur. Commun. Networks.

[6]  Min Chen,et al.  Blind Filtering at Third Parties: An Efficient Privacy-Preserving Framework for Location-Based Services , 2018, IEEE Transactions on Mobile Computing.

[7]  Frank Dürr,et al.  A classification of location privacy attacks and approaches , 2012, Personal and Ubiquitous Computing.

[8]  Paolo Palmieri,et al.  Spatial Bloom Filters: Enabling Privacy in Location-Aware Applications , 2014, Inscrypt.

[9]  Toshiya Itoh,et al.  Efficient Private Information Retrieval , 1999 .

[10]  Huirong Fu,et al.  Evaluating Trajectory Privacy in Autonomous Vehicular Communications , 2019 .

[11]  Elisa Bertino,et al.  Protecting location privacy against spatial inferences: the PROBE approach , 2009, SPRINGL '09.

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

[13]  Chao Zhang,et al.  L2P2: Location-aware location privacy protection for location-based services , 2012, 2012 Proceedings IEEE INFOCOM.

[14]  L. Ertaul.  Privacy in Location Based Services (LBS) via Composite Functions: The L4NE Protocol , 2017 .

[15]  Fenghua Li,et al.  Time obfuscation-based privacy-preserving scheme for Location-Based Services , 2016, 2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).

[16]  Maede Ashouri-Talouki,et al.  Homomorphic Encryption to Preserve Location Privacy , 2012 .

[17]  Shibin Wang,et al.  A trigger-based pseudonym exchange scheme for location privacy preserving in VANETs , 2018, Peer-to-Peer Netw. Appl..

[18]  Chunqiang Hu,et al.  Messages in a Concealed Bottle: Achieving Query Content Privacy With Accurate Location-Based Services , 2018, IEEE Transactions on Vehicular Technology.

[19]  Rudi Bekkers,et al.  The Importance of and a Comparison of Standards Development Organizations in the Ubiquitous Society , 2008 .

[20]  Jukka M. Krisp,et al.  Progress in Location-Based Services , 2013, Lecture Notes in Geoinformation and Cartography.

[21]  Neil Gandal,et al.  Standards in wireless telephone networks , 2003 .

[22]  Xiaodong Lin,et al.  PLAM: A privacy-preserving framework for local-area mobile social networks , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[23]  Georg Gartner,et al.  Location based services: ongoing evolution and research agenda , 2018, J. Locat. Based Serv..

[24]  Elena Simona Lohan,et al.  Robustness, Security and Privacy in Location-Based Services for Future IoT: A Survey , 2017, IEEE Access.

[25]  Minyi Guo,et al.  Long-term location privacy protection for location-based services in mobile cloud computing , 2016, Soft Comput..

[26]  Ruchika Gupta,et al.  An Exploration to Location Based Service and Its Privacy Preserving Techniques: A Survey , 2017, Wirel. Pers. Commun..

[27]  Zhongliang Deng,et al.  Location monitoring approach: multiple mix-zones with location privacy protection based on traffic flow over road networks , 2018, Multimedia Tools and Applications.

[28]  Amit Kumar Tyagi,et al.  Location privacy preserving techniques for location based services over road networks , 2015, 2015 International Conference on Communications and Signal Processing (ICCSP).

[29]  Ben Y. Zhao,et al.  Preserving Location Privacy in Geosocial Applications , 2014, IEEE Transactions on Mobile Computing.

[30]  Ben Mokhtar Sonia,et al.  The Long Road to Computational Location Privacy: A Survey , 2018, IEEE Communications Surveys & Tutorials.

[31]  Gang Sun,et al.  L2P2: A location-label based approach for privacy preserving in LBS , 2017, Future Gener. Comput. Syst..

[32]  Byung K. Yi,et al.  Location Based Services for Mobiles :Technologies and Standards , 2008 .

[33]  M. Usman Ashraf,et al.  Privacy provision for TIP attributes in NTTP Based LBS Systems , 2019 .

[34]  Jiaxing Qu,et al.  Prophet: A Context-Aware Location Privacy-Preserving Scheme in Location Sharing Service , 2017 .

[35]  Sabah Arif,et al.  AES-Route Server Model for Location based Services in Road Networks , 2017 .

[36]  Jianfeng Ma,et al.  Blockchain Enabled Trust-Based Location Privacy Protection Scheme in VANET , 2020, IEEE Transactions on Vehicular Technology.

[37]  Katina Michael,et al.  Location-Based Services in Emergency Management- from Government to Citizens: Global Case Studies , 2007 .

[38]  Sanjay Kumar Jena,et al.  Determining t in t-closeness using Multiple Sensitive Attributes , 2013 .