Location Privacy Protection Through Obfuscation-Based Techniques

By Claudio Agostino Ardagna, Marco Cremonini, Ernesto Damiani, Sabrina De Capitani di Vimercati, Pierangela Samarati. Database Security, 2007

356 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Science Applications, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/a016888695fab5f979c8499c92aca643782f3152

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Citations in the corpus

Privacy Preserving Image Queries for Camera Localization (2019, background): “Other anonymization approaches for location privacy for mobile systems have been explored [5, 6, 8, 21, 42].”
SpaceTwist: Managing the Trade-Offs Among Location Privacy, Query Performance, and Query Accuracy in Mobile Services (2008, background): “[15] takes location positioning inaccuracy into account, models the user location as a circular region, and develops several geometric operators for deriving cloaked regions.”
Location privacy in pervasive computing (2008, background): “Ardagna et al. [4] [5] [6] address the above shortcomings by presenting a novel solution composed by a management process and several techniques aimed at preserving location privacy by artificially perturbing location information measured by sensing technologies.”
Protecting Locations with Differential Privacy under Temporal Correlations (2014, methodology): “re. They generally use obfuscation methods, such as spatial cloaking, cell merging, location precision reduction or dummy cells, to achieve anonymity based privacy or uncertainty based privacy (e.g., [4, 11, 20, 30]). However, anonymity or ad hoc uncertainty based techniques do not always provide su”
Privacy Preserving Image-Based Localization (2019, positive): “Differential privacy [20] and k-anonymity [56] have been applied to the problem of location privacy [3, 6, 26, 72].”
Geo-indistinguishability: differential privacy for location-based systems (2012, background): “In [5], the real location of the user is assumed to have some level of inaccuracy, due to the specific sensing technology or to the environmental conditions.”
Broadening the Scope of Differential Privacy Using Metrics (2013, methodology): “The notion of relevance is also used to measure location privacy in [25].”
Technical Privacy Metrics (2015, methodology): “ (t,δ)privacy violation Databases [76] 5.8.3 Statistically strong event unobservability Communication [126] 5.8.4 Size of uncertainty region Location [31] 5.8.5 Accuracy of obfuscated region Location [13] 5.8.6 Coverage of sensitive region Location [31] 5.8.1 Confidence Interval Width. According to ”