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 |
| Published: |
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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| Summary: | 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. |
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| ISSN: | 2096-109X |