Color Image Encryption using Single Layer Artificial Neural Network and Buffer Shuffling

Dey, Dipankar; Paul, Soumen

doi:10.26438/ijcse/v7i3.202211

Cited by 2 publications

(1 citation statement)

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“…In 2019, Dey and Paul [53] proposed ANN based scheme that encrypts a color image for secure image transmission. Their proposed scheme is divided into three steps, initially the input image is partitioned into RGB factors, and using the chaotic map, a random shuffle is done on these RGB factors to get the first encrypted image, then the first encrypted image is processed through the single-layer ANN to get the second encrypted image and finally the pixels of the second encrypted image are shuffled using the exclusive-or (XOR) operation to get the final encrypted image for transmission over insecure channel.…”

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%