The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things
In order to enhance the enthusiasm of the data provider in the process of data interaction and improve the adequacy of data interaction, we put forward the concept of the ego of data and then analyzed the characteristics of the ego of data in the Internet of Things (IOT) in this paper. We implement...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2017/2970673 |
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| author | Mingshan Xie Mengxing Huang Yong Bai Zhuhua Hu |
| author_facet | Mingshan Xie Mengxing Huang Yong Bai Zhuhua Hu |
| author_sort | Mingshan Xie |
| collection | DOAJ |
| description | In order to enhance the enthusiasm of the data provider in the process of data interaction and improve the adequacy of data interaction, we put forward the concept of the ego of data and then analyzed the characteristics of the ego of data in the Internet of Things (IOT) in this paper. We implement two steps of data clustering for the Internet of things; the first step is the spatial location of adjacent fuzzy clustering, and the second step is the sampling time fuzzy clustering. Equivalent classes can be obtained through the two steps. In this way we can make the data with layout characteristics to be classified into different equivalent classes, so that the specific location information of the data can be obscured, the layout characteristics of tags are eliminated, and ultimately anonymization protection would be achieved. The experimental results show that the proposed algorithm can greatly improve the efficiency of protection of the data in the interaction with others in the incompletely open manner, without reducing the quality of anonymization and enhancing the information loss. The anonymization data set generated by this method has better data availability, and this algorithm can effectively improve the security of data exchange. |
| format | Article |
| id | doaj-art-d41416109d7146959acff301de4e73c3 |
| institution | DOAJ |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-d41416109d7146959acff301de4e73c32025-08-20T03:23:47ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552017-01-01201710.1155/2017/29706732970673The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of ThingsMingshan Xie0Mengxing Huang1Yong Bai2Zhuhua Hu3State Key Laboratory of Marine Resource Utilization in South China Sea, Haikou 570228, ChinaState Key Laboratory of Marine Resource Utilization in South China Sea, Haikou 570228, ChinaState Key Laboratory of Marine Resource Utilization in South China Sea, Haikou 570228, ChinaState Key Laboratory of Marine Resource Utilization in South China Sea, Haikou 570228, ChinaIn order to enhance the enthusiasm of the data provider in the process of data interaction and improve the adequacy of data interaction, we put forward the concept of the ego of data and then analyzed the characteristics of the ego of data in the Internet of Things (IOT) in this paper. We implement two steps of data clustering for the Internet of things; the first step is the spatial location of adjacent fuzzy clustering, and the second step is the sampling time fuzzy clustering. Equivalent classes can be obtained through the two steps. In this way we can make the data with layout characteristics to be classified into different equivalent classes, so that the specific location information of the data can be obscured, the layout characteristics of tags are eliminated, and ultimately anonymization protection would be achieved. The experimental results show that the proposed algorithm can greatly improve the efficiency of protection of the data in the interaction with others in the incompletely open manner, without reducing the quality of anonymization and enhancing the information loss. The anonymization data set generated by this method has better data availability, and this algorithm can effectively improve the security of data exchange.http://dx.doi.org/10.1155/2017/2970673 |
| spellingShingle | Mingshan Xie Mengxing Huang Yong Bai Zhuhua Hu The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things Journal of Electrical and Computer Engineering |
| title | The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things |
| title_full | The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things |
| title_fullStr | The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things |
| title_full_unstemmed | The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things |
| title_short | The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things |
| title_sort | anonymization protection algorithm based on fuzzy clustering for the ego of data in the internet of things |
| url | http://dx.doi.org/10.1155/2017/2970673 |
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