This survey provides a thorough examination of privacy in indoor location fingerprinting systems. It begins by introducing the fundamentals of indoor positioning systems, including the various ranging techniques and localization methods employed. The authors then delve into the diverse applications of indoor localization and the associated privacy concerns.
The core of the survey focuses on identifying the sources of privacy leakage in these systems. It examines the privacy vulnerabilities from multiple perspectives, including the entities involved (access points, users, trusted third parties, etc.), the data structure (identity, location, time), and the inferences that can be drawn from the location data.
The survey then presents a comprehensive overview of the adversary models, ranging from fully trusted to fully malicious, and the corresponding attack models targeting location privacy and data privacy. This provides a structured understanding of the potential threats faced by indoor location fingerprinting systems.
The authors also extensively review the existing privacy-preserving mechanisms, categorizing them based on the underlying techniques, such as cryptographic, anonymization, differential privacy, and federated learning approaches. They discuss the strengths, limitations, and trade-offs of these methods, offering insights for future research directions.
Finally, the survey highlights the datasets and evaluation metrics used in the existing studies, aiming to establish a robust benchmark for empirical investigations in this domain. The authors conclude by outlining numerous prospective research opportunities to advance the field of indoor location fingerprinting privacy.
Till ett annat språk
från källinnehåll
arxiv.org
Djupare frågor