GPU-Accelerated implementation of a genetically optimized image encryption algorithm
This paper presents a GPU-accelerated implementation of an image encryption algorithm. The algorithm uses the concepts of a modified XOR cipher to encrypt and decrypt the images, with an encryption pad, generated using the shared secret key and some initialization vectors. It uses a genetically opti...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2021, Vol.25 (22), p.14413-14428 |
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| container_title | Soft computing (Berlin, Germany) |
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| creator | Bharadwaj, Brijgopal Saira Banu, J. Madiajagan, M. Ghalib, Muhammad Rukunuddin Castillo, Oscar Shankar, Achyut |
| description | This paper presents a GPU-accelerated implementation of an image encryption algorithm. The algorithm uses the concepts of a modified XOR cipher to encrypt and decrypt the images, with an encryption pad, generated using the shared secret key and some initialization vectors. It uses a genetically optimized pseudo-random generator that outputs a stream of random bytes of the specified length. The proposed algorithm is subjected to a number of theoretical, experimental, and mathematical analyses, to examine its performance and security against a number of possible attacks, using the following metrics - histogram analysis, correlation analysis, information entropy analysis, NPCR and UACI. The performance analysis carried out shows an average speedup-ratio of 3.489 for encryption, and 4.055 for decryption operation, between the serial and parallel implementations using GPU. The algorithm aims to provide better performance benchmarks, which can significantly improve the experience in the relevant use-cases, like real-time media applications. |
| doi_str_mv | 10.1007/s00500-021-06225-y |
| format | Article |
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The algorithm uses the concepts of a modified XOR cipher to encrypt and decrypt the images, with an encryption pad, generated using the shared secret key and some initialization vectors. It uses a genetically optimized pseudo-random generator that outputs a stream of random bytes of the specified length. The proposed algorithm is subjected to a number of theoretical, experimental, and mathematical analyses, to examine its performance and security against a number of possible attacks, using the following metrics - histogram analysis, correlation analysis, information entropy analysis, NPCR and UACI. The performance analysis carried out shows an average speedup-ratio of 3.489 for encryption, and 4.055 for decryption operation, between the serial and parallel implementations using GPU. 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The algorithm uses the concepts of a modified XOR cipher to encrypt and decrypt the images, with an encryption pad, generated using the shared secret key and some initialization vectors. It uses a genetically optimized pseudo-random generator that outputs a stream of random bytes of the specified length. The proposed algorithm is subjected to a number of theoretical, experimental, and mathematical analyses, to examine its performance and security against a number of possible attacks, using the following metrics - histogram analysis, correlation analysis, information entropy analysis, NPCR and UACI. The performance analysis carried out shows an average speedup-ratio of 3.489 for encryption, and 4.055 for decryption operation, between the serial and parallel implementations using GPU. 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| source | ProQuest Central UK/Ireland; SpringerLink Journals - AutoHoldings; ProQuest Central |
| subjects | Artificial Intelligence Computational Intelligence Control Engineering Mathematical Logic and Foundations Mechatronics Optimization Robotics |
| title | GPU-Accelerated implementation of a genetically optimized image encryption algorithm |
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