A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks
Mobile traces, collected by vehicular sensor networks (VSNs), facilitate various business applications and services. However, the traces can be used to trace and identify drivers or passengers, which raise significant privacy concerns. Existing privacy protecting techniques may not be suitable, due...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/838391 |
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| _version_ | 1832559089848156160 |
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| author | Yunhua He Limin Sun Weidong Yang Hong Li |
| author_facet | Yunhua He Limin Sun Weidong Yang Hong Li |
| author_sort | Yunhua He |
| collection | DOAJ |
| description | Mobile traces, collected by vehicular sensor networks (VSNs), facilitate various business applications and services. However, the traces can be used to trace and identify drivers or passengers, which raise significant privacy concerns. Existing privacy protecting techniques may not be suitable, due to their inadequate considerations for the data accuracy requirements of different applications and the adversary's knowledge and strategies. In this paper, we analyze data privacy issues in VSNs with a game theoretic model, where a defender uses the privacy protecting techniques against the attack strategies implemented by an adversary. We study both the passive and active attack scenarios, and in each scenario we consider the effect of different data accuracy requirements on the performance of defense measures. Through the analysis results on real-world traffic data, we show that more inserted bogus traces or deleted recorded samples show a better performance when the cost of defense measures is small, whereas doing nothing becomes the best strategy when the cost of defense measures is very large. In addition, we present the optimal defense strategy that provides the defender with the maximum utility when the adversary implements the optimal attack strategy. |
| format | Article |
| id | doaj-art-9d96d4d0a63b45138968bd5897a29609 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9d96d4d0a63b45138968bd5897a296092025-02-03T01:30:50ZengWileyInternational Journal of Distributed Sensor Networks1550-14772014-01-011010.1155/2014/838391838391A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor NetworksYunhua He0Limin Sun1Weidong Yang2Hong Li3 School of Computer Science, Xidian University, Xi'an, China State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Science, Beijing, China College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Science, Beijing, ChinaMobile traces, collected by vehicular sensor networks (VSNs), facilitate various business applications and services. However, the traces can be used to trace and identify drivers or passengers, which raise significant privacy concerns. Existing privacy protecting techniques may not be suitable, due to their inadequate considerations for the data accuracy requirements of different applications and the adversary's knowledge and strategies. In this paper, we analyze data privacy issues in VSNs with a game theoretic model, where a defender uses the privacy protecting techniques against the attack strategies implemented by an adversary. We study both the passive and active attack scenarios, and in each scenario we consider the effect of different data accuracy requirements on the performance of defense measures. Through the analysis results on real-world traffic data, we show that more inserted bogus traces or deleted recorded samples show a better performance when the cost of defense measures is small, whereas doing nothing becomes the best strategy when the cost of defense measures is very large. In addition, we present the optimal defense strategy that provides the defender with the maximum utility when the adversary implements the optimal attack strategy.https://doi.org/10.1155/2014/838391 |
| spellingShingle | Yunhua He Limin Sun Weidong Yang Hong Li A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks International Journal of Distributed Sensor Networks |
| title | A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks |
| title_full | A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks |
| title_fullStr | A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks |
| title_full_unstemmed | A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks |
| title_short | A Game Theory-Based Analysis of Data Privacy in Vehicular Sensor Networks |
| title_sort | game theory based analysis of data privacy in vehicular sensor networks |
| url | https://doi.org/10.1155/2014/838391 |
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