Differentially private data release based on clustering anonymization
Based on the theory of anonymization,the DBSCAN method was applied to divide all the data records into different groups to cover individuals.To provide priv enhancement,the Laplace noise was added to the anonymized partitioned data to perturb the real value of data record so that the requirements of...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2016-05-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016100/ |
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| _version_ | 1841539612714991616 |
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| author | Xiao-qian LIU Qian-mu LI |
| author_facet | Xiao-qian LIU Qian-mu LI |
| author_sort | Xiao-qian LIU |
| collection | DOAJ |
| description | Based on the theory of anonymization,the DBSCAN method was applied to divide all the data records into different groups to cover individuals.To provide priv enhancement,the Laplace noise was added to the anonymized partitioned data to perturb the real value of data record so that the requirements of differential privacy model were satis-fied.With the clustering operation,the sensitivity of the query function has been partitioned to improve data utility.The proof of privacy has been given and experimental results have been provided to evaluate the utility of the released data. |
| format | Article |
| id | doaj-art-ce7e68bca2714f38ae25ecda28a27360 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2016-05-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-ce7e68bca2714f38ae25ecda28a273602025-01-14T06:55:26ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2016-05-013712512959701088Differentially private data release based on clustering anonymizationXiao-qian LIUQian-mu LIBased on the theory of anonymization,the DBSCAN method was applied to divide all the data records into different groups to cover individuals.To provide priv enhancement,the Laplace noise was added to the anonymized partitioned data to perturb the real value of data record so that the requirements of differential privacy model were satis-fied.With the clustering operation,the sensitivity of the query function has been partitioned to improve data utility.The proof of privacy has been given and experimental results have been provided to evaluate the utility of the released data.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016100/differential privacyprivacy preservationclusteringdata releaseanonymization |
| spellingShingle | Xiao-qian LIU Qian-mu LI Differentially private data release based on clustering anonymization Tongxin xuebao differential privacy privacy preservation clustering data release anonymization |
| title | Differentially private data release based on clustering anonymization |
| title_full | Differentially private data release based on clustering anonymization |
| title_fullStr | Differentially private data release based on clustering anonymization |
| title_full_unstemmed | Differentially private data release based on clustering anonymization |
| title_short | Differentially private data release based on clustering anonymization |
| title_sort | differentially private data release based on clustering anonymization |
| topic | differential privacy privacy preservation clustering data release anonymization |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016100/ |
| work_keys_str_mv | AT xiaoqianliu differentiallyprivatedatareleasebasedonclusteringanonymization AT qianmuli differentiallyprivatedatareleasebasedonclusteringanonymization |