PSO-GA Hybrid Approach in Image Encryption

Das, Subhajit; Mandal, Satyendra Nath; Shynal, Manas

doi:10.1007/978-981-13-1343-1_57

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…At last, the logical operation is performed among the altered image and random sequence to produce the encrypted image. The author indicated that their proposed technique has resistance to various types of attacks In 2018, Das et al [42] proposed a hybrid of particle swarm optimization (PSO) [43] and genetic algorithm approach to encrypt an image. The key is generated using genetic and PSO algorithm.…”

Section: Review On Computational Intelligence Based Image Encryptionmentioning

confidence: 99%

Survey on computational intelligence based image encryption techniques

Ramanathan

Hossen

Sayeed

et al. 2020

IJEECS

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Image encryption is an important area in visual cryptography that helps in protecting images when shared through internet. There is lot of cryptography algorithms applied for many years in encrypting images. In the recent years, artificial intelligence techniques are combined with cryptography algorithms to support image encryption. Some of the benefits that artificial intelligence techniques can provide are prediction of possible attacks on cryptosystem using machine learning algorithms, generation of cryptographic keys using optimization algorithms, etc. Computational intelligence algorithms are popular in enhancing security for image encryption. The main computational intelligence algorithms used in image encryption are neural network, fuzzy logic and genetic algorithm. In this paper, a review is done on computational intelligence-based image encryption methods that have been proposed in the recent years and the comparison is made on those methods based on their performance on image encryption.

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Section: Review On Computational Intelligence Based Image Encryptionmentioning

confidence: 99%

Survey on computational intelligence based image encryption techniques

Ramanathan

Hossen

Sayeed

et al. 2020

IJEECS

View full text Add to dashboard Cite

show abstract

“…Hence, it demands bettersolutions to resolve the security problems of multimedia data effectively [7].The authors described an approach for high-quality image hiding by improving the visual quality of the stego-image with large embedding capacity [8]. In [9], Omar A.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Genetic-fuzzy Encryption Technique

Mousa¹

2018

IJCNIS

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Abstract-As the result of increasing use of internet in daily communication and the importance of information security during data storage and transmission process, we propose iterative Chaotic Genetic-fuzzy Encryption Technique(C-GET) in order to enhance secured encryption technique and less predictable. In this technique,binarize any digital data type. The main encryption stages of C-GET are chaotic map functions, fuzzy logic and genetic operations. Mathematic operations and rotation are also included that increase encryption quality. Images are used for testing propose. For testing C-GET,digitalimagesareusedbecause they become an important resource of communication. The original and reconstructed data are identical. Experimental results show that C-GET technique has multilayer protection stages against various attacks and a powerful security based on the multi-stages, multiple parameters, fuzzy logic and genetic operations. Decrypted data is nearly randomness and has negligible correlation with secret data.

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PSO-GA Hybrid Approach in Image Encryption

Cited by 2 publications

References 12 publications

Survey on computational intelligence based image encryption techniques

Survey on computational intelligence based image encryption techniques

Chaotic Genetic-fuzzy Encryption Technique

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