A survey on deep learning for human mobility

M Luca, G Barlacchi, B Lepri… - ACM Computing Surveys …, 2021 - dl.acm.org
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …

Survey on privacy-preserving techniques for microdata publication

T Carvalho, N Moniz, P Faria, L Antunes - ACM Computing Surveys, 2023 - dl.acm.org
The exponential growth of collected, processed, and shared microdata has given rise to
concerns about individuals' privacy. As a result, laws and regulations have emerged to …

Scikit-mobility: A Python library for the analysis, generation, and risk assessment of mobility data

L Pappalardo, F Simini, G Barlacchi… - Journal of Statistical …, 2022 - jstatsoft.org
The last decade has witnessed the emergence of massive mobility datasets, such as tracks
generated by GPS devices, call detail records, and geo-tagged posts from social media …

CATS: Conditional Adversarial Trajectory Synthesis for privacy-preserving trajectory data publication using deep learning approaches

J Rao, S Gao, S Zhu - International Journal of Geographical …, 2023 - Taylor & Francis
The prevalence of ubiquitous location-aware devices and mobile Internet enables us to
collect massive individual-level trajectory dataset from users. Such trajectory big data bring …

Sok: Privacy-preserving data synthesis

Y Hu, F Wu, Q Li, Y Long, GM Garrido… - … IEEE Symposium on …, 2024 - ieeexplore.ieee.org
As the prevalence of data analysis grows, safeguarding data privacy has become a
paramount concern. Consequently, there has been an upsurge in the development of …

Generative models for synthetic urban mobility data: A systematic literature review

A Kapp, J Hansmeyer, H Mihaljević - ACM Computing Surveys, 2023 - dl.acm.org
Although highly valuable for a variety of applications, urban mobility data are rarely made
openly available, as it contains sensitive personal information. Synthetic data aims to solve …

Evaluation of home detection algorithms on mobile phone data using individual-level ground truth

L Pappalardo, L Ferres, M Sacasa, C Cattuto… - EPJ data …, 2021 - epjds.epj.org
Inferring mobile phone users' home location, ie, assigning a location in space to a user
based on data generated by the mobile phone network, is a central task in leveraging …

Reinforcement learning-based sensitive semantic location privacy protection for VANETs

M Min, W Wang, L **ao, Y **ao… - China Communications, 2021 - ieeexplore.ieee.org
Location-based services (LBS) in vehicular ad hoc networks (VANETs) must protect users'
privacy and address the threat of the exposure of sensitive locations during LBS requests …

Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility

G Papyshev, M Yarime - Data & Policy, 2021 - cambridge.org
This article discusses the technology of city digital twins (CDTs) and its potential applications
in the policymaking context. The article analyzes the history of the development of the …

A survey and experimental study on privacy-preserving trajectory data publishing

F **, W Hua, M Francia, P Chao… - … on Knowledge and …, 2022 - ieeexplore.ieee.org
Trajectory data has become ubiquitous nowadays, which can benefit various real-world
applications such as traffic management and location-based services. However, trajectories …