PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark
To address the low-efficiency problem for query privacy protection on big data,parallel CPIR-V (PCPIR-V),which had a high level of privacy protection for nearest neighbor query,was presented and implemented based on spark.Two parallel strategies for PCPIR-V,Row strategy and Bit strategy,were propose...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2016-05-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2016.00057 |
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| _version_ | 1850091998702206976 |
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| author | Shi-zhuo DENG Ji-tao YAO Bo-tao WANG Yue-mei CHEN Ye YUAN Yan-hui LI Guo-ren WANG |
| author_facet | Shi-zhuo DENG Ji-tao YAO Bo-tao WANG Yue-mei CHEN Ye YUAN Yan-hui LI Guo-ren WANG |
| author_sort | Shi-zhuo DENG |
| collection | DOAJ |
| description | To address the low-efficiency problem for query privacy protection on big data,parallel CPIR-V (PCPIR-V),which had a high level of privacy protection for nearest neighbor query,was presented and implemented based on spark.Two parallel strategies for PCPIR-V,Row strategy and Bit strategy,were proposed.To avoid redundant multiplications,the repeated products were cached based on a clustering technique while computing CPIR on Spark.According to the evaluation results of PCPIR-V on three datasets,the scalablity of PCPIR-V is good until the number of core is larger than 40.The cost of PCPIR-V with the method of caching partial multiplication results is reduced by 20% averagely. |
| format | Article |
| id | doaj-art-2203f8699bda4daa8230f5156be05bee |
| institution | DOAJ |
| issn | 2096-109X |
| language | English |
| publishDate | 2016-05-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-2203f8699bda4daa8230f5156be05bee2025-08-20T02:42:14ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2016-05-012647659545622PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on SparkShi-zhuo DENGJi-tao YAOBo-tao WANGYue-mei CHENYe YUANYan-hui LIGuo-ren WANGTo address the low-efficiency problem for query privacy protection on big data,parallel CPIR-V (PCPIR-V),which had a high level of privacy protection for nearest neighbor query,was presented and implemented based on spark.Two parallel strategies for PCPIR-V,Row strategy and Bit strategy,were proposed.To avoid redundant multiplications,the repeated products were cached based on a clustering technique while computing CPIR on Spark.According to the evaluation results of PCPIR-V on three datasets,the scalablity of PCPIR-V is good until the number of core is larger than 40.The cost of PCPIR-V with the method of caching partial multiplication results is reduced by 20% averagely.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2016.00057query privacy protection,computational private information retrievalSparklocation based service |
| spellingShingle | Shi-zhuo DENG Ji-tao YAO Bo-tao WANG Yue-mei CHEN Ye YUAN Yan-hui LI Guo-ren WANG PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark 网络与信息安全学报 query privacy protection, computational private information retrieval Spark location based service |
| title | PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark |
| title_full | PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark |
| title_fullStr | PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark |
| title_full_unstemmed | PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark |
| title_short | PCPIR-V:parallel privacy protected algorithms for nearest neighbor query based on Spark |
| title_sort | pcpir v parallel privacy protected algorithms for nearest neighbor query based on spark |
| topic | query privacy protection, computational private information retrieval Spark location based service |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2016.00057 |
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