Image encryption using chaotic logistic map

By Narendra K. Pareek, Vinod Patidar, Krishan K. Sud. Image and Vision Computing, 2006

1,275 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/c2074f2d3f03b30b042f7f8187ec34c2f0eb79eb

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In Computer Vision and Pattern Recognition

In Mathematical Physics

Citations in the corpus

An image encryption scheme based on chaotic tent map (2016, methodology): “[22] used two chaotic logistic maps with an external secret key of 80-bit.”
A fast color image encryption algorithm based on coupled two-dimensional piecewise chaotic map (2012, neutral): “[6–11].”
Image encryption using DNA addition combining with chaotic maps (2010, background): “[7] proposed an image encryption algorithmbased on a one dimension chaotic map.”
Discrete chaos in fractional delayed logistic maps (2015, background): “The discrete dynamic behavior and its applications have been paid much attention in various applied areas, such as synchronization control [1–3], secure communication [4,5], biomolecular network evolution [6,7], and so on.”
A general quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks (2008, background): “e data specially become an urgent task. Due to the subtle similarities between cryptography and chaos, a great number of image encryption schemes based on chaos have been proposed in the paste decade [1, 2, 3, 4, 5]. Unfortunately, most of them have been found to be insecure of diﬀerent extents from”
Cryptanalysis of a new image encryption algorithm based on hyper-chaos (2008, background): “So far, many chaos-based image cryptosystems have been proposed [8–18].”
Color image encryption based on one-time keys and robust chaotic maps (2010, methodology): “Algorithm 1 uses a logistic map and a two-value threshold function to generate the 0–1 stream [17].”
Shannon Entropy based Randomness Measurement and Test for Image Encryption (2011, methodology): “Image randomness can be measured using a variety of methods, such as histogram analysis [6,12,16,22,28,29,35,37,40,42,54,55,57,60,63,64], global Shannon entropy measure [6,12,42,55,64,66], adjacent pixel correlations [6,12,16,35,42,57,64,66].”
A novel chaotic block image encryption algorithm based on dynamic random growth technique (2015, background): “Many other algorithms are also proposed [14–20], and some of them are analyzed [21,22].”