A Novel Unpredictable Temporal based Pseudo Random Number Generator

Khalique, Aqeel; Lone, Auqib Hamid; Ashraf, Syed Shahabuddin

doi:10.5120/20615-3301

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…There are simple arithmetic algorithms like a linear congruential generator, lagged Fibonacci generator, linear feedback shift register generator [8], but many of these early PRNGs have inadequacies [9] [10]. There are many proposed pseudorandom numbers generators; some are stream cipher based [11] [12] [13], some are temporal [14], and some are chaotic based [15] [16], and some are cellular automata-based [17] [18], but the problem is there is a trade-off between security, complexity, and the output rate.…”

Section: Related Workmentioning

confidence: 99%

Acoustic Lightweight Pseudo Random Number Generator based on Cryptographically Secure LFSR

AL-khatib¹,

Lone²

2018

IJCNIS

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Abstract-In this paper, we propose a secure, lightweight acoustic pseudo-random number generator (SLA-LFSR-PRNG) that consumes less memory, CPU capacity and adopts the multi-thread parallelization to generate huge random numbers per second by taking the advantages of multi-core CPU and massively parallel architecture of GPU. The generator is based on cryptographically secure Linear Feedback Shift Register(LFSR) and extracts the entropy from sound sources. The major attraction of proposed Pseudo Random Number Generator(PRNG) is its immunity to major attacks on pseudo-random number generators. The paper presents test results of proposed PRNG subjected to NIST SP 800-22 statistical test suite and also shows the performance comparison of proposed generator on different systems.

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Section: Related Workmentioning

confidence: 99%

Acoustic Lightweight Pseudo Random Number Generator based on Cryptographically Secure LFSR

AL-khatib¹,

Lone²

2018

IJCNIS

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Image encryption framework based on multi-chaotic maps and equal pixel values quantization

Kolivand,

Hamood,

Asadianfam

et al. 2024

Multimed Tools Appl

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The importance of image encryption has considerably increased, especially after the dramatic evolution of the internet and network communications, due to the simplicity of capturing and transferring digital images. Although there are several encryption approaches, chaos-based image encryption is considered the most appropriate approach for image applications because of its sensitivity to initial conditions and control parameters. Confusion and diffusion methods have been used in conventional image encryption methods, but the ideal encrypted image has not yet been achieved. This research aims to generate an encrypted image free of statistical information to make cryptanalysis infeasible. Additionally, the motivation behind this work lies in addressing the shortcomings of conventional image encryption methods, which have not yet achieved the ideal encrypted image. The proposed framework aims to overcome these challenges by introducing a new method, Equal Pixel Values Quantization (EPVQ), along with enhancing the confusion and diffusion processes using chaotic maps and additive white Gaussian noise. Key security, statistical properties of encrypted images, and withstanding differential attacks are the most important issues in the field of image encryption. Therefore, a new method, Equal Pixel Values Quantization (EPVQ), was introduced in this study in addition to the proposed confusion and diffusion methods to achieve an ideal image encryption framework. Generally, the confusion method uses Sensitive Logistic Map (SLM), Henon Map, and additive white Gaussian noise to generate random numbers for use in the pixel permutation method. However, the diffusion method uses the Extended Bernoulli Map (EBM), Tinkerbell, Burgers, and Ricker maps to generate the random matrix. Internal Interaction between Image Pixels (IIIP) was used to implement the XOR (Exclusive OR) operator between the random matrix and scrambled image. Basically, the EPVQ method was used to idealize the histogram and information entropy of the ciphered image. The correlation between adjacent pixels was minimized to have a very small value (×10−3). Besides, the key space was extended to be very large (2450) considering the key sensitivity to hinder brute force attacks. Finally, a histogram was idealized to be perfectly equal in all occurrences, and the resulting information entropy was equal to the ideal value (8), which means that the resulting encrypted image is free of statistical properties in terms of the histogram and information entropy. Based on the findings, the high randomness of the generated random sequences of the proposed confusion and diffusion methods is capable of producing a robust image encryption framework against all types of cryptanalysis attacks.

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