Open Access

ARTICLE

Privacy-Preserving Genetic Algorithm Outsourcing in Cloud Computing

Leqi Jiang^{1, 2}, Zhangjie Fu^{1, 2, *}

1 College of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
2 Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing, 210044, China.

* Corresponding Author: Zhangjie Fu. Email: .

Journal of Cyber Security 2020, 2(1), 49-61. https://doi.org/10.32604/jcs.2020.09308

Abstract

Genetic Algorithm (GA) has been widely used to solve various optimization problems. As the solving process of GA requires large storage and computing resources, it is well motivated to outsource the solving process of GA to the cloud server. However, the algorithm user would never want his data to be disclosed to cloud server. Thus, it is necessary for the user to encrypt the data before transmitting them to the server. But the user will encounter a new problem. The arithmetic operations we are familiar with cannot work directly in the ciphertext domain. In this paper, a privacy-preserving outsourced genetic algorithm is proposed. The user’s data are protected by homomorphic encryption algorithm which can support the operations in the encrypted domain. GA is elaborately adapted to search the optimal result over the encrypted data. The security analysis and experiment results demonstrate the effectiveness of the proposed scheme.

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Keywords

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