Pseudonym exchange for privacy-preserving publishing of trajectory data set
2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE), 2014 Anonymization is a common technique for publishing a location data set in a privacy-preserving way. However, such an anonymized data set lacks trajectory information of users, which could be beneficial to many location-based analytic services. In this paper, we present a dynamic pseudonym scheme for constructing alternate possible paths of mobile users
Ken Mano +2 more
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Privacy Preservation for Trajectory Data Publishing by Look-Up Table Generalization
, 2018 With the increasing of location-aware devices, it is easy to collect the trajectory of a person which can be represented as a sequence of visited locations with regard to timestamps. For some applications such as traffic management and location-based advertising, the trajectory data may need to be published with other private information.
Nattapon Harnsamut +2 more
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Differential Privacy Trajectory Data Publishing Method Based on RNN
2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS), 2023 Kang Huang
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An Efficient Model and Algorithm for Privacy-Preserving Trajectory Data Publishing
, 2019 Since Abul et al. first proposed the k-anonymity based privacy protection for trajectory data, the researchers have proposed a variety of trajectory privacy-preserving methods, these methods mainly adopt the static anonymity algorithm, which directly anonymize processing and data publishing after initialization.
Songyuan Li, Hong Shen, Yingpeng Sang
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GAN-based Differential Privacy Trajectory Data Publishing with Sensitive Label
2022 8th International Conference on Big Data Computing and Communications (BigCom), 2022 Lin Yao +3 more
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Privacy-aware trajectory data publishing: an optimal efficient generalisation algorithm
International Journal of Grid and Utility Computing, 2023 Nattapon Harnsamut, Juggapong Natwichai
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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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Novel Privacy-preserving algorithm based on frequent path for trajectory data publishing
Knowledge-Based Systems, 2018 Yulan Dong, Dechang Pi
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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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UdpTrace: Utility-enhanced differential privacy scheme for trajectory data publishing
NeurocomputingWei Sun +4 more
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