Privacy protection method for fine-grained urban traffic modeling using mobile sensors |
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Affiliation: | 1. Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu 611731, China;2. Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu 611731, China;3. Xi''an Jiaotong-Liverpool University, Suzhou 215123, China |
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Abstract: | With the ubiquitous nature of mobile sensing technologies, privacy issues are becoming increasingly important, and need to be carefully addressed. Data needs for transportation modeling and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms that would simultaneously satisfy privacy protection and data needs for fine-grained urban traffic modeling applications using mobile sensors. To accomplish this, a virtual trip lines (VTLs) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed and tested to evaluate the effectiveness of such a privacy protection system by making privacy attacks. The results show that in addition to ensuring an acceptable level of privacy, the released datasets from the privacy-enhancing system can also be applied to urban traffic modeling with satisfactory results. Albeit application-specific, such a “Privacy-by-Design” approach would hopefully shed some light on other transportation applications using mobile sensors. |
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Keywords: | Mobile traffic sensors Fine-grained urban traffic modeling Privacy protection Privacy by design Adversary model |
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