joint obfuscation of location and its semantic information for privacy protection

被引:11
|
作者
Bostanipour, Behnaz [1 ]
Theodorakopoulos, George [1 ]
机构
[1] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, Wales
关键词
Privacy; Social networks; Location-based services; Location semantics; Bayesian networks; Probabilistic graphical models; Utility;
D O I
10.1016/j.cose.2021.102310
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Location-based social networks (LBSNs) such as Foursquare and Facebook enable users to share with each other, their (geographical) locations together with the semantic information associated with their locations. The semantic information captures the type of a location and is usually represented by a semantic tag like "restaurant", "museum", "school", etc. Semantic tag sharing increases the threat to users' location privacy (which is already at risk because of location sharing) and it also puts users' semantic location privacy at risk. The existing solution to protect the location privacy and the semantic location privacy of users in such LBSNs is to obfuscate the location and the semantic tag independently of each other in a so called disjoint obfuscation approach. Thus, in this approach, the semantic tag is obfuscated i.e., replaced by a more general tag. Also, the location is obfuscated i.e., replaced by a generalized area (called the cloaking area ) made of the actual location and some of its nearby locations. However, since in this approach the location obfuscation is performed in a semantic-oblivious manner, an adversary can still increase his chance to infer the actual location and the actual semantic tag by filtering out the locations in the cloaking area that are not semantically compatible with the obfuscated semantic tag. In this work, we address this issue by proposing a joint obfuscation approach in which the location obfuscation is performed based on the result of the semantic tag obfuscation. We also provide a formal framework for evaluation and comparison of our joint approach with the disjoint approach. By running an experimental evaluation on a dataset of real-world user traces collected from six different cities, we show that in almost all cases (i.e., in different cities and with different obfuscation parameters), the joint approach outperforms the disjoint approach in terms of location privacy protection and the semantic location privacy protection. Based on the evaluation results, we also discuss how different obfuscation parameters and the choice of the city can affect the performance of the obfuscation approaches. In particular, we show how changing these parameters can improve the performance of the joint approach. (c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数:22
相关论文
共 50 条
  • [41] Query Obfuscation for Information Retrieval Through Differential Privacy
    Faggioli, Guglielmo
    Ferro, Nicola
    ADVANCES IN INFORMATION RETRIEVAL, ECIR 2024, PT I, 2024, 14608 : 278 - 294
  • [42] A semantic k-anonymity privacy protection method for publishing sparse location data
    Yang, Xudong
    Gao, Ling
    Wang, Hai
    Zheng, Jie
    Guo, Hongbo
    2019 SEVENTH INTERNATIONAL CONFERENCE ON ADVANCED CLOUD AND BIG DATA (CBD), 2019, : 216 - 222
  • [43] Semantic analysis in location privacy preserving
    Xiong, Ping
    Zhang, Lefeng
    Zhu, Tianqing
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2016, 28 (06): : 1884 - 1899
  • [44] Location Privacy Protection Considering the Location Safety
    Kasori, Kohei
    Sato, Fumiaki
    PROCEEDINGS 2015 18TH INTERNATIONAL CONFERENCE ON NETWORK-BASED INFORMATION SYSTEMS (NBIS 2015), 2015, : 140 - 145
  • [45] Robust Image Obfuscation for Privacy Protection in Web 2.0 Applications
    Poller, Andreas
    Steinebach, Martin
    Liu, Huajian
    MEDIA WATERMARKING, SECURITY, AND FORENSICS 2012, 2012, 8303
  • [46] On the Implementation of Location Obfuscation in openwifi and Its Performance
    Ghiro, Lorenzo
    Cominelli, Marco
    Gringoli, Francesco
    Lo Cigno, Renato
    2022 20TH MEDITERRANEAN COMMUNICATION AND COMPUTER NETWORKING CONFERENCE (MEDCOMNET), 2022,
  • [47] Protecting location privacy through semantics-aware obfuscation techniques
    Damiani, Maria Luisa
    Bertino, Elisa
    Silvestri, Claudio
    TRUST MANAGEMENT II, 2008, 263 : 231 - +
  • [48] Framework of data privacy preservation and location obfuscation in vehicular cloud networks
    Al-Balasmeh, Hani
    Singh, Maninder
    Singh, Raman
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2022, 34 (05):
  • [49] A Double Obfuscation Approach for Protecting the Privacy of IoT Location Based Applications
    Albouq, Sami Saad
    Sen, Adnan Ahmed Abi
    Namoun, Abdallah
    Bahbouh, Nour Mahmoud
    Alkhodre, Ahmad B.
    Alshanqiti, Abdullah
    IEEE ACCESS, 2020, 8 : 129415 - 129431
  • [50] Location Privacy Protection with a Semi-honest Anonymizer in Information Centric Networking
    Kita, Kentaro
    Kurihara, Yoshiki
    Koizumi, Yuki
    Hasegawa, Toru
    PROCEEDINGS OF THE 5TH ACM CONFERENCE ON INFORMATION-CENTRIC NETWORKING (ICN'18), 2018, : 95 - 105