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Privacy Preservation for Trajectory Publication Based on Differential Privacy
ACM Transactions on Intelligent Systems and Technology, 2022With the proliferation of location-aware devices, trajectory data have been used widely in real-life applications. However, trajectory data are often associated with sensitive labels, such as users’ purchase transactions and planned activities. As such, inappropriate sharing or publishing of these data could threaten users’ privacy, especially when an ...
Lin Yao 0001 +4 more
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A personalized trajectory privacy protection method
Computers & Security, 2021Abstract Trajectory data of sports or activities are usually collected and shared into social apps like Wechat moments, Sina weibo in public to provide health services and recommendation, while a large number of friends with weak ties in social circle will cause privacy leakage of users’ locations and life habits. To solve the problem, a personalized
Jiachun Li, Guoqian Chen
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Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems, 2008
In order to provide context--aware Location--Based Services, real location data of mobile users must be collected and analyzed by spatio--temporal data mining methods. However, the data mining methods need precise location data, while the mobile users want to protect their location privacy.
Gyözö Gidófalvi +2 more
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In order to provide context--aware Location--Based Services, real location data of mobile users must be collected and analyzed by spatio--temporal data mining methods. However, the data mining methods need precise location data, while the mobile users want to protect their location privacy.
Gyözö Gidófalvi +2 more
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Enhancing the Trajectory Privacy with Laplace Mechanism
2015 IEEE Trustcom/BigDataSE/ISPA, 2015Mobile-aware service systems are dramatically increasing the amount of personal data released to service providers as well as to third parties. Data may reveal individuals' physical conditions, habits, and sensitive information. It raises serious privacy concerns. Current approaches to mitigate the privacy concerns rely on the randomization.
Daiyong Quan, Lihua Yin, Yunchuan Guo
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Revealing Privacy Vulnerabilities of Anonymous Trajectories
IEEE Transactions on Vehicular Technology, 2018The proliferation of various mobile devices equipped with GPS positioning modules makes the collection of trajectories more easier than ever before, and more and more trajectory datasets have been available for business applications or academic researches.
Shan Chang +4 more
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Preserving Trajectory Privacy in Driving Data Release
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Agency for Science, Technology and Research (A*STAR)
Xu, Yi +3 more
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Privacy Preserving Trajectory Data Publishing with Personalized Differential Privacy
2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), 2020With the development of location-based applications, more and more trajectory data are collected and applied. Trajectory data often contains user's sensitive information, and direct release may pose a threat to users' privacy. Differential privacy, as a privacy preserving method with solid mathematical foundation, has been widely used in trajectory ...
Ruxue Wen +4 more
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Publishing trajectories with differential privacy guarantees
Proceedings of the 25th International Conference on Scientific and Statistical Database Management, 2013The pervasiveness of location-acquisition technologies has made it possible to collect the movement data of individuals or vehicles. However, it has to be carefully managed to ensure that there is no privacy breach. In this paper, we investigate the problem of publishing trajectory data under the differential privacy model.
Kaifeng Jiang +4 more
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SST: Privacy Preserving for Semantic Trajectories
2015 16th IEEE International Conference on Mobile Data Management, 2015To preserve privacy in trajectory data, most existing approaches adapt cloaking techniques to protect individual location points or clustering and perturbation techniques to protect entire trajectories. To confirm to the k-anonymity model, they first group locations/trajectories and then modify location points to ensure a cluster of k location points ...
Pin-I Han, Hsiao-Ping Tsai
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Privacy-preserving trajectory stream publishing
Data & Knowledge Engineering, 2014Recent advancement in mobile computing and sensory technology has facilitated the possibility of continuously updating, monitoring, and detecting the latest location and status of moving individuals. Spatio-temporal data generated and collected on the fly are described as trajectory streams.
Khalil Al-Hussaeni +2 more
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