Abstract
A trajectory is a spatio-temporal movement trace that couples location with timestamp. Due to the pervasive nature of location-aware devices, such as GPS-enabled smartphones, moving individuals are generating movement traces when taking a trip. Whether the moving individual is walking, cycling, driving, or using public transportation, such traces may contain sensitive information, such as sensitive locations or habits. Many privacy laws are being developed around the world to regulate the processing and dissemination of private data. On the other hand, collecting trajectories of moving individuals is fundamental for various applications, such as city infrastructure planning and traffic analysis because mining collected trajectories greatly enhances decision-making. Consequently, a need arises to find a way to mine trajectory data while considering the privacy of individuals sharing their trajectories. This is the objective of anonymizing trajectory data.
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Al-Hussaeni, K. (2021). Anonymizing Trajectory Data. In: Phung, D., Webb, G.I., Sammut, C. (eds) Encyclopedia of Machine Learning and Data Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7502-7_983-1
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DOI: https://doi.org/10.1007/978-1-4899-7502-7_983-1
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