Process Calculus for Modeling and Quantifying Location Privacy
Author(s) -
Jingquan Ding,
Xiao Li,
Yunchuan Guo,
Lihua Yin,
Huibing Zhang
Publication year - 2019
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2019.01.257
Subject(s) - computer science , probabilistic logic , obfuscation , process (computing) , measure (data warehouse) , entropy (arrow of time) , process calculus , computer security , theoretical computer science , data mining , artificial intelligence , programming language , physics , quantum mechanics
In the mobile wireless Internet, location privacy is serious concerns. As a response to these concerns, many (formal) location-privacy protection mechanisms (LPPMs) and evaluation metrics for LPPMs have been proposed. It is necessary to integrate formal models into assessments, because this integration can deduce the gap between them: after designing a LPPM, we adopt this integration to formalize and measure it. In this paper, we propose a probabilistic process calculus to model the obfuscation-based schemes (OBS, one LPPM ) and use the relative entropy to measure the degree of location privacy OBS can leak. We integrate the two approaches into one unified model. Examples demonstrate the accuracy of our model. Our work decreases the gap between the formalization and the measurement for OBS.
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