Image Encryption Scheme Based on Non-autonomous Chaotic Systems

Volos, Christos; Kyprianidis, I. Μ.; Stouboulos, I. N.; Pham, Viet–Thanh

doi:10.1007/978-3-319-18275-9_25

Cited by 5 publications

(2 citation statements)

References 40 publications

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“…The inherent properties of chaotic systems, such as sensitivity to initial conditions, unpredictability, and complex behavior, make them suitable for many applications, including image encryption [29][30][31]. These complex dynamics can be useful in generating pseudo-random numbers as encryption keys.…”

Section: Introductionmentioning

confidence: 99%

A Fractional-Order Memristive Two-Neuron-Based Hopfield Neuron Network: Dynamical Analysis and Application for Image Encryption

Venkatesh,

Pchelintsev,

Karthikeyan

et al. 2023

Mathematics

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This paper presents a study on a memristive two-neuron-based Hopfield neural network with fractional-order derivatives. The equilibrium points of the system are identified, and their stability is analyzed. Bifurcation diagrams are obtained by varying the magnetic induction strength and the fractional-order derivative, revealing significant changes in the system dynamics. It is observed that lower fractional orders result in an extended bistability region. Also, chaos is only observed for larger magnetic strengths and fractional orders. Additionally, the application of the fractional-order model for image encryption is explored. The results demonstrate that the encryption based on the fractional model is efficient with high key sensitivity. It leads to an encrypted image with high entropy, neglectable correlation coefficient, and uniform distribution. Furthermore, the encryption system shows resistance to differential attacks, cropping attacks, and noise pollution. The Peak Signal-to-Noise Ratio (PSNR) calculations indicate that using a fractional derivative yields a higher PSNR compared to an integer derivative.

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Section: Introductionmentioning

confidence: 99%

A Fractional-Order Memristive Two-Neuron-Based Hopfield Neuron Network: Dynamical Analysis and Application for Image Encryption

Venkatesh,

Pchelintsev,

Karthikeyan

et al. 2023

Mathematics

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“…Security and communications systems today, including financial security, RFID, and cryptography, rely on this idea of randomness Sundaresan et al (2015); Volos (2013). Specifically, these technologies depend heavily on random bits being readily available to process into various encryption schemes.…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation of a Chaotic Jerk Circuit Based True Random Number Generator

Harrison

Rhea

OLDAG

et al. 2022

Chaos Theory and Applications

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A method for true random number generation by directly sampling a high frequency chaotic jerk circuit is explored. A method for determination of the maximum Lyapunov exponent, and thus the maximum bit rate for true random number generation, of the jerk system of interest is shown. The system is tested over a wide range of sampling parameters in order to simulate possible hardware configurations. The system is then implemented in high speed electronics on a small printed circuit board to verify its performance over the chosen parameters. The resulting circuit is well suited for random number generation due to its high dynamic complexity, long term aperiodicity, and extreme sensitivity to initial conditions. This system passes the Dieharder RNG test suite at 3.125 Mbps.

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