An Image Encryption Algorithm Based on Logistic-Fibonacci Cascade Chaos and 3D Bit Scrambling

Guo, Yongqing; Jing, Shiwei; Zhou, Yanyan; Xu, Xingguang; Wei, Liansuo

doi:10.1109/access.2019.2963717

Cited by 18 publications

(11 citation statements)

References 27 publications

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“…Since our goal is to effectively resist various attacks on image data while also limiting the hardware complexity, we combine hyperchaotic masking with an additional easyto-implement confusion process. In particular, we add Arnold cat mapping [40] for Scheme 1 , and bit scrambling [41] for Scheme 2 . We choose the Arnold cap map since only pixel positions are scrambled.…”

Section: B Potential Image Encryption Methodsmentioning

confidence: 99%

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Encrypted Physical Layer Communications Using Synchronized Hyperchaotic Maps

Tang

Mandal

2021

IEEE Access

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With the proliferation of Internet-of-Things (IoT) devices at public facilities, work places, homes, and beyond, securing data communications is becoming increasingly challenging. This paper describes the analysis and practical implementation of synchronized hyperchaotic maps for securing short-range data links in IoT devices. The data is stream-encrypted in the physical layer using chaotic masking and decrypted using a synchronized chaotic map. Two different energy-efficient chaotic encryption schemes are proposed: 1) direct sampling and masking of analog sensor outputs, thus avoiding the need for analog-to-digital (ADC) conversion; and 2) bit scrambling and masking of digital data. Both schemes were initially investigated and simulated in MATLAB. The effective number of encryption keys when using such hyperchaotic maps was also studied. Simulation results were validated by implementing two maps on circuit boards using high-speed discrete components. Experimental results for digital communication show a bit error rate (BER) of ≈ 2 × 10 −6 at a bit rate of 10 kbps and a clock frequency of 0.5 MHz, making the approach feasible for high-fidelity real-time speech and image transmission without additional error control coding. An energy-efficient on-chip chaotic encryption system was developed using analog current-mode circuits and has a simulated power consumption of <100 µW in the TSMC 180 nm CMOS process, which is sufficiently low for use in many battery-less miniaturized IoT sensor nodes.

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Section: B Potential Image Encryption Methodsmentioning

confidence: 99%

“…To achieve improved encryption performance using Scheme 2 , we adopt 3D bit scrambling to remove inter-pixel correlations [41]. Let us define m and n as the plaintext image dimensions, and k as the number of higher (i.e., more significant) bits.…”

Section: B 3d Bit Scramblingmentioning

confidence: 99%

Encrypted Physical Layer Communications Using Synchronized Hyperchaotic Maps

Tang

Mandal

2021

IEEE Access

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“…The key space of this work is at least

200^{3} \times {(10^{14})}^{6} \times 2^{256} \approx 9.2634 \times 10^{167}

. From the security point of view, the key space

\geq 2^{100} \approx 10^{30}

can meet the higher security level [24, 37], so the key space of this algorithm is safe for brute‐force attack.…”

Section: Experimental Analysismentioning

confidence: 99%

“…However, the scrambling effect of some particularly bright or dark images is not ideal. Although the high-order and low-order bits are separated and scrambled in literature works [24,25], the number of bits with different weights is exchanged to some extent, resulting in the decrease of robustness of the algorithm. The ciphertext encrypted by the above encryption methods is all noise-like images or texture-like images.…”

Section: Introductionmentioning

confidence: 99%

Meaningful ciphertext encryption algorithm based on bit scrambling, discrete wavelet transform, and improved chaos

Jing

Guo

Chen

2020

IET Image Processing

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This paper proposes a meaningful ciphertext encryption algorithm of good practicability and strong robustness. The plaintext undergoes pre-encryption of bit scrambling and secondary encryption of discrete wavelet transform (DWT) to obtain meaningful ciphertext. In the pre-encryption stage, only the higher three bit pages that are not all 0 or 1 are scrambled. The embedding method in the secondary encryption process is to add the hundreds and tens' digit and ones' digit of the middle ciphertext to the scrambled detail information obtained by DWT of the cover image. The information entropy of the intermediate ciphertext obtained by this method can reach 7.997, the correlation coefficient between the ciphertext and the cover image can reach 0.99, and the decrypted image of the ciphertext under high-intensity pollution can still be identified. It shows that the pre-encryption can conceal the plaintext information well, and the secondary encryption can eliminate the ciphertext texture characteristics while retaining the good robustness. Finally, the improved three one-dimensional chaos are used to generate random sequences, and the plaintext hash value is associated with the chaotic key. The improved chaos greatly improves the randomness of the sequence and broadens the range of parameters. The hash value SHA-256 of the plaintext is added to make the key stream adaptively change with the plaintext, which greatly improves the sensitivity of the plaintext and the ability to resist selected plaintext and ciphertext attacks. Experiments have also verified that the encryption algorithm can encrypt images of different types and shapes and has strong practicability, good bit scrambling effect, and high sensitivity to scrambling. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The scrambling operation can not only change the pixel value but also break the correlation with the original pixel value, making the image encryption more secure [13], [14], [15], [16]. Many bit-based encryption methods have been proposed to reduce the correlation between adjacent pixels [17], [18]. However, these encryption techniques have some limitations.…”

Section: Introductionmentioning

confidence: 99%