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Multi-keyword parallel ciphertext retrieval scheme in distributed environment
DAI Houle, YANG Geng, MIN Zhao'e
Journal of Computer Applications 2019, 39 (
10
): 2948-2954. DOI:
10.11772/j.issn.1001-9081.2019020376
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374
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For searchable encryption, balancing the security and retrieval efficiency of data is important. Aiming at the low retrieval performance and the lack of single keyword search mode in SSE-1 ciphertext retrieval scheme, and the problems such as the limitation of single-machine resources in the traditional single-server architecture, a multi-keyword parallel ciphertext retrieval system was designed and implemented. Different index encryption strategies were used to improve the ciphertext retrieval performance. The block search of the inverted index was realized by partitioning the ciphertext inverted index, which solves the limitation of single-machine resources and improves the retrieval efficiency. The traditional single-machine retrieval architecture was extended and the parallel retrieval of multiple keywords was realized by combining the characteristic of distribution. Experimental results show that compared with the SSE-1 scheme, the proposed scheme has the efficiency of retrieval and update operations improved under the premise of ensuring ciphertext data security and realizes multi-keyword retrieval. At the same time, the distributed architecture of the system is dynamically expanded to improve the system load capacity.
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Parallel algorithm for homomoriphic encryption base on MapReduce
HU Chi, YANG Geng, YANG Beisi, MIN Zhao'e
Journal of Computer Applications 2015, 35 (
12
): 3408-3412. DOI:
10.11772/j.issn.1001-9081.2015.12.3408
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According to the distributed feature of cloud computing, a parallel homomorphic encryption scheme based on the MapReduce Hadoop was proposed with the combination of homomorphic encryption and MapReduce parallel framework under Hadoop environment. The concrete parallel homomorphic encrypting algorithm was implemented, and the theoretical analysis was given to prove the security and correctness of the proposed algorithm. The evaluation experiments on the cloud cluster consisting of 4 computing nodes with total 16 Central Processing Units (CPUs) show that the data encryption of the parallel homomorphic encryption algorithm can reach the speed-up radio of 13. The experimental result shows that the proposed algorithm can reduce the time cost of data encryption and can be applied to real-time applications.
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Parallel algorithm of AES encryption based on MapReduce
FU Yadan, YANG Geng, HU Chi, MIN Zhao'e
Journal of Computer Applications 2015, 35 (
11
): 3079-3082. DOI:
10.11772/j.issn.1001-9081.2015.11.3079
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In order to protect privacy of consumers in cloud computing, encrypted data storage is a feasible way. To speed up process of encryption and decryption, a parallel Advanced Encryption Standard (AES) encryption algorithm was proposed taking the characteristic of multi-nodes in cloud computing into account. The performance of the algorithm was analyzed in theory, and then experiments were conducted to demonstrate the efficiency of the designed algorithm. The experimental results show that the speed-up radio of the proposed encryption scheme can reach 15.9, and the total time cost of AES encryption can be reduced by 72.7% on the cloud cluster consisting of 4 compute nodes of total 16 CPUs.
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