Preserving Differential Privacy for Similarity Measurement in Smart Environments
Advances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people’s life and living styles. However, collecting and storing user’s data in the smart environments pose severe privacy concerns because these data may contain sensiti...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/581426 |
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| _version_ | 1832549916370534400 |
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| author | Kok-Seng Wong Myung Ho Kim |
| author_facet | Kok-Seng Wong Myung Ho Kim |
| author_sort | Kok-Seng Wong |
| collection | DOAJ |
| description | Advances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people’s life and living styles. However, collecting and storing user’s data in the smart environments pose severe privacy concerns because these data may contain sensitive information about the subject. Hence, privacy protection is now an emerging issue that we need to consider especially when data sharing is essential for analysis purpose. In this paper, we consider the case where two agents in the smart environment want to measure the similarity of their collected or stored data. We use similarity coefficient function FSC as the measurement metric for the comparison with differential privacy model. Unlike the existing solutions, our protocol can facilitate more than one request to compute FSC without modifying the protocol. Our solution ensures privacy protection for both the inputs and the computed FSC results. |
| format | Article |
| id | doaj-art-1d5dee6eb9194e16b8c2e571c07eae85 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-1d5dee6eb9194e16b8c2e571c07eae852025-02-03T06:08:12ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/581426581426Preserving Differential Privacy for Similarity Measurement in Smart EnvironmentsKok-Seng Wong0Myung Ho Kim1School of Computer Science and Engineering, Soongsil University, Information Science Building, Sangdo-dong, Dongjak-gu, Seoul 156-743, Republic of KoreaSchool of Computer Science and Engineering, Soongsil University, Information Science Building, Sangdo-dong, Dongjak-gu, Seoul 156-743, Republic of KoreaAdvances in both sensor technologies and network infrastructures have encouraged the development of smart environments to enhance people’s life and living styles. However, collecting and storing user’s data in the smart environments pose severe privacy concerns because these data may contain sensitive information about the subject. Hence, privacy protection is now an emerging issue that we need to consider especially when data sharing is essential for analysis purpose. In this paper, we consider the case where two agents in the smart environment want to measure the similarity of their collected or stored data. We use similarity coefficient function FSC as the measurement metric for the comparison with differential privacy model. Unlike the existing solutions, our protocol can facilitate more than one request to compute FSC without modifying the protocol. Our solution ensures privacy protection for both the inputs and the computed FSC results.http://dx.doi.org/10.1155/2014/581426 |
| spellingShingle | Kok-Seng Wong Myung Ho Kim Preserving Differential Privacy for Similarity Measurement in Smart Environments The Scientific World Journal |
| title | Preserving Differential Privacy for Similarity Measurement in Smart Environments |
| title_full | Preserving Differential Privacy for Similarity Measurement in Smart Environments |
| title_fullStr | Preserving Differential Privacy for Similarity Measurement in Smart Environments |
| title_full_unstemmed | Preserving Differential Privacy for Similarity Measurement in Smart Environments |
| title_short | Preserving Differential Privacy for Similarity Measurement in Smart Environments |
| title_sort | preserving differential privacy for similarity measurement in smart environments |
| url | http://dx.doi.org/10.1155/2014/581426 |
| work_keys_str_mv | AT koksengwong preservingdifferentialprivacyforsimilaritymeasurementinsmartenvironments AT myunghokim preservingdifferentialprivacyforsimilaritymeasurementinsmartenvironments |