Results 251 to 260 of about 3,780,326 (325)

Privacy-preserving mechanisms for location privacy in mobile crowdsensing: A survey

Journal of Network and Computer Applications, 2022
Jong Wook Kim, Kennedy Edemacu, Beakcheol Jang   +2 more
exaly   +2 more sources

PPO2: Location Privacy-Oriented Task Offloading to Edge Computing Using Reinforcement Learning for Intelligent Autonomous Transport Systems

IEEE transactions on intelligent transportation systems (Print), 2023
AI-empowered 5G/6G networks play a substantial role in taking full advantage of the Internet of Things (IoT) to perform complex computing by offloading tasks to edge services deployed in intelligent transport systems.
Honghao Gao, Wanqiu Huang, Tong Liu, Yuyu Yin, Youhuizi Li   +4 more
semanticscholar   +1 more source

A Caching-Based Dual K-Anonymous Location Privacy-Preserving Scheme for Edge Computing

IEEE Internet of Things Journal, 2023
Location-based services have become prevalent and the risk of location privacy leakage increases. Most existing schemes use third-party-based or third-party-free system architectures; the former suffers from a single point of failure (SPOF) and the ...
Shiwen Zhang, Biao Hu, W. Liang, Kuan Ching Li, B. Gupta   +4 more
semanticscholar   +1 more source

Geo-Ellipse-Indistinguishability: Community-Aware Location Privacy Protection for Directional Distribution

IEEE Transactions on Knowledge and Data Engineering, 2023
Directional distribution analysis has long served as a fundamental functionality in abstracting dispersion and orientation of spatial datasets. Spatial datasets that describe sensitive information of individuals such as health status and home addresses ...
Ying Zhao, Dong Yuan, J. Du, Jinjun Chen
semanticscholar   +1 more source

Location Privacy Protection via Delocalization in 5G Mobile Edge Computing Environment

IEEE Transactions on Services Computing, 2023
In the past several years, we have witnessed a variety of mechanisms for protecting mobile users’ location privacy, e.g., k-anonymity, cloaking, encryption, etc. Unfortunately, existing techniques suffer from a common limitation - mobile users’ locations
Guangming Cui, Qiang He, Feifei Chen, Hai Jin, Yang Xiang, Yun Yang   +5 more
semanticscholar   +1 more source

Location Privacy-preserving Mechanisms in Location-based Services

ACM Computing Surveys, 2021
Location-based services (LBSs) provide enhanced functionality and convenience of ubiquitous computing, but they open up new vulnerabilities that can be utilized to violate the users’ privacy.
Hongbo Jiang, Jie Li, Ping Zhao, Fanzi Zeng, Zhu Xiao, A. Iyengar   +5 more
semanticscholar   +1 more source

Eclipse: Preserving Differential Location Privacy Against Long-Term Observation Attacks

IEEE Transactions on Mobile Computing, 2022
Mechanisms built upon geo-indistinguishability render location privacy, where a user can submit obfuscated locations to Location-Based Service providers but still be able to correctly utilize services.
Ben Niu, Yahong Chen, Zhibo Wang, Fenghua Li, Boyang Wang, Hui Li   +5 more
semanticscholar   +1 more source

Protecting Location Privacy of Users Based on Trajectory Obfuscation in Mobile Crowdsensing

IEEE Transactions on Industrial Informatics, 2022
In mobile crowdsensing activities, it is usually necessary for participants to upload sensing data and related locations. The existing location privacy-preserving mechanisms cannot well protect a user's trajectory privacy because attackers can mine the ...
Zhigang Gao, Yucai Huang, Leilei Zheng, Huijuan Lu, Bo Wu, Jianhui Zhang   +5 more
semanticscholar   +1 more source

A Decentralized Location Privacy-Preserving Spatial Crowdsourcing for Internet of Vehicles

IEEE transactions on intelligent transportation systems (Print), 2021
With the rapid development of Internet of Vehicles (IoV), vehicle-based spatial crowdsourcing (SC) applications have been proposed and widely applied to various fields. However, location privacy leakage is a serious issue in spatial crowdsourcing because
Junwei Zhang, Fan Yang, Zhuo Ma, Zhuzhu Wang, Ximeng Liu, Jianfeng Ma   +5 more
semanticscholar   +1 more source

Location Privacy-Preserving Task Recommendation With Geometric Range Query in Mobile Crowdsensing

IEEE Transactions on Mobile Computing, 2021
In mobile crowdsensing, location-based task recommendation requires each data requester to submit a task-related geometric range to crowdsensing service providers such that they can match suitable workers within this range. Generally, a trusted server (i.
Chuan Zhang, Liehuang Zhu, Chang Xu, Jianbing Ni, Cheng Huang, X. Shen   +5 more
semanticscholar   +1 more source