Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity
Due to the shared nature of wireless communication media, a powerful adversary can eavesdrop on the entire radio communication in the network and obtain the contextual communication statistics, for example, traffic volumes, transmitter locations, and so forth. Such information can reveal the locatio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2012/648058 |
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| _version_ | 1849695491872260096 |
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| author | Guofei Chai Miao Xu Wenyuan Xu Zhiyun Lin |
| author_facet | Guofei Chai Miao Xu Wenyuan Xu Zhiyun Lin |
| author_sort | Guofei Chai |
| collection | DOAJ |
| description | Due to the shared nature of wireless communication media, a powerful adversary can eavesdrop on the entire radio communication in the network and obtain the contextual communication statistics, for example, traffic volumes, transmitter locations, and so forth. Such information can reveal the location of the sink around which the data traffic exhibits distinctive patterns. To protect the sink-location privacy from a powerful adversary with a global view, we propose to achieve k-anonymity in the network so that at least k entities in the network are indistinguishable to the nodes around the sink with regard to communication statistics. Arranging the location of k entities is complex as it affects two conflicting goals: the routing energy cost and the achievable privacy level, and both goals are determined by a nonanalytic function. We model such a positioning problem as a nonlinearly constrained nonlinear optimization problem. To tackle it, we design a generic-algorithm-based quasi-optimal (GAQO) method that obtains quasi-optimal solutions at quadratic time. The obtained solutions closely approximate the optima with increasing privacy requirements. Furthermore, to solve k -anonymity sink-location problems more efficiently, we develop an artificial potential-based quasi-optimal (APQO) method that is of linear time complexity. Our extensive simulation results show that both algorithms can effectively find solutions hiding the sink among a large number of network nodes. |
| format | Article |
| id | doaj-art-9d225afb79cf4ef98cd6487fb436517a |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2012-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9d225afb79cf4ef98cd6487fb436517a2025-08-20T03:19:46ZengWileyInternational Journal of Distributed Sensor Networks1550-14772012-04-01810.1155/2012/648058Enhancing Sink-Location Privacy in Wireless Sensor Networks through -AnonymityGuofei Chai0Miao Xu1Wenyuan Xu2Zhiyun Lin3 College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA College of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaDue to the shared nature of wireless communication media, a powerful adversary can eavesdrop on the entire radio communication in the network and obtain the contextual communication statistics, for example, traffic volumes, transmitter locations, and so forth. Such information can reveal the location of the sink around which the data traffic exhibits distinctive patterns. To protect the sink-location privacy from a powerful adversary with a global view, we propose to achieve k-anonymity in the network so that at least k entities in the network are indistinguishable to the nodes around the sink with regard to communication statistics. Arranging the location of k entities is complex as it affects two conflicting goals: the routing energy cost and the achievable privacy level, and both goals are determined by a nonanalytic function. We model such a positioning problem as a nonlinearly constrained nonlinear optimization problem. To tackle it, we design a generic-algorithm-based quasi-optimal (GAQO) method that obtains quasi-optimal solutions at quadratic time. The obtained solutions closely approximate the optima with increasing privacy requirements. Furthermore, to solve k -anonymity sink-location problems more efficiently, we develop an artificial potential-based quasi-optimal (APQO) method that is of linear time complexity. Our extensive simulation results show that both algorithms can effectively find solutions hiding the sink among a large number of network nodes.https://doi.org/10.1155/2012/648058 |
| spellingShingle | Guofei Chai Miao Xu Wenyuan Xu Zhiyun Lin Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity International Journal of Distributed Sensor Networks |
| title | Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity |
| title_full | Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity |
| title_fullStr | Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity |
| title_full_unstemmed | Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity |
| title_short | Enhancing Sink-Location Privacy in Wireless Sensor Networks through -Anonymity |
| title_sort | enhancing sink location privacy in wireless sensor networks through anonymity |
| url | https://doi.org/10.1155/2012/648058 |
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