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Privacy preserving vehicular trajectory prediction
2016 International Conference on Computing, Analytics and Security Trends (CAST), 2016Location based services (LBS) provide many valuable and important services for end users but reveal information about personal location to potentially untrustworthy service providers which could pose privacy concerns. The information about exact path followed by a person is highly personal and can be used to uniquely identify a person. Such information
Purwa Gaikwad +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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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.
Al-Hussaeni, Khalil +2 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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Privacy of Spatial Trajectories
2011The ubiquity of mobile devices with global positioning functionality (e.g., GPS and Assisted GPS) and Internet connectivity (e.g., 3G and Wi-Fi) has resulted in widespread development of location-based services (LBS). Typical examples of LBS include local business search, e-marketing, social networking, and automotive traffic monitoring.
Chi-Yin Chow, Mohemad F. Mokbel
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Privacy-Preserving Spatial Trajectory Prediction
2014 National Wireless Research Collaboration Symposium, 2014One of the location-based services, spatial trajectory prediction, can be used in a variety of purposes such as travel recommendations and traffic control and planning, but at the same time, just like most location-based services, the concern of user privacy is a major issue.
Wen Chen Hu +3 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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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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Privacy-Preserving Trajectory Collection
2008In 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.
Gidofalvi, Gyozo +2 more
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2010
In this era of significant advances in telecommunications and GPS sensors technology, a person can be tracked down to proximity of less than 5 meters. This remarkable progress enabled the offering of services that depend on user location (the so-called location-based services—LBSs), as well as the existence of applications that analyze movement data ...
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In this era of significant advances in telecommunications and GPS sensors technology, a person can be tracked down to proximity of less than 5 meters. This remarkable progress enabled the offering of services that depend on user location (the so-called location-based services—LBSs), as well as the existence of applications that analyze movement data ...
openaire +1 more source