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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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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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Adding Noise Trajectory for Providing Privacy in Data Publishing by Vectorization
2020 IEEE International Conference on Big Data and Smart Computing (BigComp), 2020Since trajectory data is widely collected and utilized for scientific research and business purpose, publishing trajectory without proper privacy-policy leads to an acute threat to individual data. Recently, several methods, i.e., k-anonymity, l-diversity, t-closeness have been studied, though they tend to protect by reducing data depends on a feature ...
Rashid Tojiboev +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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Novel trajectory data publishing method under differential privacy
Expert Systems with Applications, 2019Abstract The existing location-based services have collected a large amount of user trajectory data, and if these data are directly released without any processing, the user's personal privacy will be leaked. At present, differential privacy protection technology is favored by many scholars, but how to apply it reasonably to location-based services ...
Xiaodong Zhao, Yulan Dong, Dechang Pi
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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), 2023exaly +2 more sources
Real-Time Trajectory Data Publishing Method with Differential Privacy
2018 14th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN), 2018With the increasing popularity of location technologies and location-based service applications, a large number of user's trajectory data have been collected. Publishing the real-time statistics data of trajectory streams can be useful in many fields such as intelligent transportation system, urban road planning and road congestion detection.
Fengyun Li +3 more
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Privacy Preservation for Trajectory Data Publishing and Heuristic Approach
2017With 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. The trajectory data publishing can be useful in real-life applications, such as location-based advertising, traffic management, and geo-marketing.
Nattapon Harnsamut, Juggapong Natwichai
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Pseudonym exchange for privacy-preserving publishing of trajectory data set
2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE), 2014Anonymization 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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Publishing Sensitive Trajectory Data Under Enhanced l-Diversity Model
2019 20th IEEE International Conference on Mobile Data Management (MDM), 2019With the proliferation of location-aware devices, trajectory data have been widely collected, published, and analyzed in real-life applications. However, published trajectory data often contain sensitive attributes, so an attacker who can identify an individual from such data through record linkage, attribute linkage, or similarity attacks can gain ...
Lin Yao 0001 +4 more
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