A trajectory privacy-preserving scheme based on a dual-K mechanism for continuous location-based services

Abstract Location-based services (LBSs) have increasingly provided by a broad range of devices and applications, but one associated risk is location disclosure. To solve this problem, a commonly method is to adopt K-anonymity in the centralized architecture based on a single trusted anonymizer. However, this strategy may compromise user privacy involving continuous LBSs. In this study, we propose a dual-K mechanism (DKM) to protect the users’ trajectory privacy for continuous LBSs. The proposed DKM method firstly inserted multiple anonymizers between the user and the location service provider (LSP), and K query locations are sent to different anonymizers to achieve K-anonymity. Simultaneously, we combined the dynamic pseudonym and the location selection mechanisms to improve user trajectory privacy. Hence, neither the LSP nor the anonymizer can obtain the user trajectory. Security analyses demonstrates that our proposed scheme can effectively enhance user trajectory privacy protection, and the simulation results prove that the DKM scheme can preserve user trajectory privacy with low overhead on a single anonymizer.

[1]  Qing Liu,et al.  A Hybrid Prediction Model for Moving Objects , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[2]  Ren-Hung Hwang,et al.  A Novel Time-Obfuscated Algorithm for Trajectory Privacy Protection , 2014, IEEE Transactions on Services Computing.

[3]  Rick Siow Mong Goh,et al.  QLDS: A Novel Design Scheme for Trajectory Privacy Protection with Utility Guarantee in Participatory Sensing , 2018, IEEE Transactions on Mobile Computing.

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

[5]  Kim-Kwang Raymond Choo,et al.  Enhancing privacy through uniform grid and caching in location-based services , 2017, Future Gener. Comput. Syst..

[6]  Xiao Liu,et al.  A statistical approach to participant selection in location-based social networks for offline event marketing , 2019, Inf. Sci..

[7]  Christian S. Jensen,et al.  Indexing the past, present, and anticipated future positions of moving objects , 2006, TODS.

[8]  Shaobo Zhang,et al.  A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services , 2019, Future Gener. Comput. Syst..

[9]  Tao Peng,et al.  Enhanced Location Privacy Preserving Scheme in Location-Based Services , 2017, IEEE Systems Journal.

[10]  Jie Wu,et al.  Preserving Privacy with Probabilistic Indistinguishability in Weighted Social Networks , 2017, IEEE Transactions on Parallel and Distributed Systems.

[11]  Qiong Huang,et al.  Privacy-Preserving Location Sharing Services for Social Networks , 2017, IEEE Transactions on Services Computing.

[12]  Chen Wang,et al.  ILLIA: Enabling $k$ -Anonymity-Based Privacy Preserving Against Location Injection Attacks in Continuous LBS Queries , 2018, IEEE Internet of Things Journal.

[13]  Xi Wen,et al.  A Trajectory Privacy-Preserving Scheme Based on Dual-K Mechanism for Continuous Location-Based Services , 2017, 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC).

[14]  Nasser Ghadiri,et al.  $P^4QS$: A Peer-to-Peer Privacy Preserving Query Service for Location-Based Mobile Applications , 2016, IEEE Transactions on Vehicular Technology.

[15]  Thomas Brinkhoff,et al.  Generating Traffic Data , 2003, IEEE Data Eng. Bull..

[16]  Jemal H. Abawajy,et al.  A trajectory privacy-preserving scheme based on query exchange in mobile social networks , 2018, Soft Comput..

[17]  Jie Wu,et al.  Friendship-based location privacy in Mobile Social Networks , 2011, Int. J. Secur. Networks.

[18]  Jinjun Chen,et al.  A two-stage locality-sensitive hashing based approach for privacy-preserving mobile service recommendation in cross-platform edge environment , 2018, Future Gener. Comput. Syst..

[19]  Wei Liu,et al.  A low redundancy data collection scheme to maximize lifetime using matrix completion technique , 2019, EURASIP J. Wirel. Commun. Netw..

[20]  Kang G. Shin,et al.  Privacy protection for users of location-based services , 2012, IEEE Wireless Communications.

[21]  Chao Li,et al.  ReverseCloak: A Reversible Multi-level Location Privacy Protection System , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[22]  Xiaoqing Li,et al.  Privacy-area aware dummy generation algorithms for Location-Based Services , 2014, 2014 IEEE International Conference on Communications (ICC).

[23]  Naixue Xiong,et al.  A novel code data dissemination scheme for Internet of Things through mobile vehicle of smart cities , 2019, Future Gener. Comput. Syst..

[24]  Yaping Lin,et al.  Anonymizing popularity in online social networks with full utility , 2017, Future Gener. Comput. Syst..

[25]  Tao Peng,et al.  Collaborative trajectory privacy preserving scheme in location-based services , 2017, Inf. Sci..

[26]  Xiong Li,et al.  Anonymous mutual authentication and key agreement scheme for wearable sensors in wireless body area networks , 2017, Comput. Networks.

[27]  Yuan Zhang,et al.  On Designing Satisfaction-Ratio-Aware Truthful Incentive Mechanisms for $k$ -Anonymity Location Privacy , 2016, IEEE Transactions on Information Forensics and Security.

[28]  Ming-Hour Yang,et al.  Unchained Cellular Obfuscation Areas for Location Privacy in Continuous Location-Based Service Queries , 2017, Wirel. Commun. Mob. Comput..

[29]  Xuyun Zhang,et al.  A Distributed Locality-Sensitive Hashing-Based Approach for Cloud Service Recommendation From Multi-Source Data , 2017, IEEE Journal on Selected Areas in Communications.

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

[31]  Laurence T. Yang,et al.  A Big Data-as-a-Service Framework: State-of-the-Art and Perspectives , 2018, IEEE Transactions on Big Data.

[32]  Arun Kumar Sangaiah,et al.  CenLocShare: A centralized privacy-preserving location-sharing system for mobile online social networks , 2017, Future Gener. Comput. Syst..

[33]  Qiang Zhang,et al.  Enabling Cooperative Privacy-preserving Personalized search in cloud environments , 2019, Inf. Sci..

[34]  Md Zakirul Alam Bhuiyan,et al.  A Dual Privacy Preserving Scheme in Continuous Location-Based Services , 2018, IEEE Internet of Things Journal.

[35]  Fan Wu,et al.  A Robust ECC-Based Provable Secure Authentication Protocol With Privacy Preserving for Industrial Internet of Things , 2018, IEEE Transactions on Industrial Informatics.

[36]  Arun Kumar Sangaiah,et al.  ESCAPE: Effective Scalable Clustering Approach for Parallel Execution of Continuous Position-Based Queries in Position Monitoring Applications , 2017, IEEE Transactions on Sustainable Computing.

[37]  Laurence T. Yang,et al.  A Cloud-Edge Computing Framework for Cyber-Physical-Social Services , 2017, IEEE Communications Magazine.

[38]  Hui Li,et al.  3PLUS: Privacy-preserving pseudo-location updating system in location-based services , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[39]  Arun Kumar Sangaiah,et al.  PCCA: Position Confidentiality Conserving Algorithm for Content-Protection in e-Governance Services and Applications , 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.

[40]  Vinh Tran Quang,et al.  A Lateration-localizing Algorithm for Energy-efficient Target Tracking in Wireless Sensor Networks , 2016, Ad Hoc Sens. Wirel. Networks.

[41]  Xiao Chen,et al.  Location privacy-preserving k nearest neighbor query under user's preference , 2016, Knowl. Based Syst..

[42]  Sarvesh Tanwar,et al.  Extended Design and Implementation of Certificate Authorities , 2017 .