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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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Privacy Risks in Publishing Mobile Device Trajectories
IEEE Wireless Communications Letters, 2014Growing availability of mobile devices capable of sensing and transmitting geospatial information has led to a wide range of location based services (LBSs). Sharing location data with others is an intrinsic feature of LBSs. However, publishing location may raise serious privacy concerns due to its close connection with users' sensitive information ...
Alireza Haghnegahdar +2 more
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TGM: A Generative Mechanism for Publishing Trajectories With Differential Privacy
IEEE Internet of Things Journal, 2020We describe a new generative algorithm called trajectory generative mechanism (TGM) for publishing trajectory datasets with $\varepsilon $ -differential privacy guarantee, which achieves substantially higher computational efficiency and utility (practical) than the state-of-the-art algorithms.
Soheila Ghane +2 more
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Trajectory anonymity in publishing personal mobility data
ACM SIGKDD Explorations Newsletter, 2011Recent years have witnessed pervasive use of location-aware devices such as GSM mobile phones, GPS-enabled PDAs, location sensors, and active RFID tags. The use of these devices generates a huge collection of spatio-temporal data, variously called moving object data, trajectory data, or moblity data.
Francesco Bonchi +2 more
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Protecting sensitive place visits in privacy-preserving trajectory publishing
Computers and Security, 2020Abstract The rise of mobile computing has generated huge amount of trajectory data. Since these data are valuable for many people, publishing them while providing adequate individual privacy protection has been a challenging task. In this paper, we present an algorithm for protecting sensitive place visits in privacy-preserving trajectory publishing.
Mohan Kankanhalli
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Privacy Risks in Trajectory Data Publishing: Reconstructing Private Trajectories from Continuous Properties [PDF]
, 2008 Location and time information about individuals can be captured through GPS devices, GSM phones, RFID tag readers, and by other similar means. Such data can be pre-processed to obtain trajectories which are sequences of spatio-temporal data points belonging to a moving object. Recently, advanced data mining techniques have been developed for extracting
Kaplan, Emre +3 more
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Personalized Privacy‐Preserving Trajectory Data Publishing
Chinese Journal of Electronics, 2017Due to the popularity of mobile internet and location-aware devices, there is an explosion of location and trajectory data of moving objects. A few proposals have been proposed for privacy preserving trajectory data publishing, and most of them assume the attacks with the same adversarial background knowledge.
Caimei Wang, Yan Xiong, Wenchao Huang
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A Scheme for Activity Trajectory Dataset Publishing with Privacy Preserved
2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015Facilitated by ubiquitous computing techniques and the wide development of location-based service (LBS) and smart card systems, users' trajectory data, which is usually attached with user activities, are recorded more and more easily. Inappropriate publishing these trajectory data may jeopardize users' privacy.
Xianming Li, Shen Wei, Guangzhong Sun
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STDP: Secure Privacy-Preserving Trajectory Data Publishing
2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2018As the smart devices and cloud services are rapidly expanding, a large amount of location information can easily be gathered. However, there is a conflict between collecting location information and protecting personal information since obtaining and utilizing the information may be restricted due to privacy concerns. In fact, various methods which use
Chris Soo-Hyun Eom +2 more
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Suppression techniques for privacy-preserving trajectory data publishing
Knowledge-Based Systems, 2020Abstract In this paper, we study the problem of protecting privacy in trajectory datasets from adversaries who can exploit their partial knowledge to infer unknown locations. To efficiently solve this problem, we propose a tree-based indexing structure to store all trajectory data and develop pruning strategies.
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