New color image encryption technique based on three-dimensional logistic map and Grey wolf optimization based generated substitution boxes

Khan, Hamza; Hazzazi, Mohammad Mazyad; Jamal, Sajjad Shaukat; Hussain, Iqtadar; Khan, Majid

doi:10.1007/s11042-022-13612-6

Cited by 17 publications

(13 citation statements)

References 27 publications

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“…Against Khan et. al [40], the observed increase is minimal at 0.04%, emphasizing the proposed approach's ability to uphold the desired level of entropy for effective image encryption. Overall, the proposed method's consistently high IE values affirm its positive performance and suitability for applications requiring secure and robust image encryption.…”

Section: E Comparison Of Image Entropy (Ie)mentioning

confidence: 83%

“…Similar trends are observed in the comparison with Hussain et.al [42], where the proposed method showcases an improvement of about 0.882%, and against Khan et. al [40], with a slight improvement of 0.011%. Overall, the proposed approach demonstrates competitive performance in terms of NPCR, suggesting its effectiveness in image encryption.…”

Section: Comparison Of Normalized Pixel Change Rate (Npcr)mentioning

confidence: 93%

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A Novel Framework for Image Encryption by Integrating Modified Moth Flame Optimization and Logistic Chaotic Map for Enhanced Security

Aggarwal,

Awasthi,

Kukreja

et al. 2024

Preprint

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Preserving the confidentiality of sensitive image data is of paramount importance in the digital world. Therefore, an optimized image encryption algorithm is proposed in this paper for securing image-based communication. The proposed Modified Moth Flame Optimization Algorithm (MMFO) delved along with a Logistic Chaotic Map is used to obtain improved values of evaluation parameters such as Correlation Coefficient(CC), Image Entropy (IE), Unified Average Changing Intensity (UACI) and Normalized Pixel Change Rate (NPCR) along with Uniform Histograms for the encrypted image that outperforms various state-of-the-art metaheuristic algorithms coupled with diverse chaotic maps. Using multiple plain image-dependent session keys and a Logistic Chaotic map, several encrypted images are generated which act as an initial population for the Modified algorithm. The results are presented to validate the performance of the proposed algorithm. It has been observed that the proposed algorithm has a substantial de-correlation of adjacent pixels in the encrypted image, achieving values on the order of 10−6.

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Section: E Comparison Of Image Entropy (Ie)mentioning

confidence: 83%

Section: Comparison Of Normalized Pixel Change Rate (Npcr)mentioning

confidence: 93%

A Novel Framework for Image Encryption by Integrating Modified Moth Flame Optimization and Logistic Chaotic Map for Enhanced Security

Aggarwal,

Awasthi,

Kukreja

et al. 2024

Preprint

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show abstract

“…From the results of the above scholars, although high-dimensional chaos achieves better encryption than low-dimensional chaos, the complexity of the structure makes it more difficult to realize, and the time cost is higher. Literature [15] proposes an encryption scheme that utilizes three-dimensional (3D) logistic and S-boxes for obfuscation. Simulation results illustrate the advantages of this proposal in the design of encryption schemes.…”

Section: Related Researchmentioning

confidence: 99%

Research on Chaotic Image Encryption Based on Fibonacci-ILogistic-IHenon

Yang,

Chen,

et al. 2024

JCSANDM

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To further improve the security of image encryption, we propose an image encryption algorithm that combines Fibonacci with improved logistic and improved Henon chaotic mapping, i.e., the Fibonacci-ILogistic-IHenon algorithm. The algorithm addresses that the existing logistic chaotic algorithm is controlled by the parameter resulting in an uneven distribution, and the Henon chaotic algorithm may have the problem of periodic orbits. Using the mode-taking and sinusoidal functions for optimization, the output sequence region generated by the logistic chaotic mapping is adjusted to the input of the Henon chaotic mapping, which enables the construction of a new chaotic system (ILogistic-IHenon). In the image encryption implementation, Fibonacci is used to cure the chaos, and ILogistic-IHenon is utilized to generate chaotic sequences to complete the encryption. In the simulation experiments, we choose the improved logistic encryption algorithm, the improved Henon encryption algorithm, and the improved logistic-ent encryption algorithm as the comparison algorithms, and the results illustrate that the Fibonacci-ILogistic-IHenon algorithm has better performance in image encryption statistical analysis, encryption speed, pixel correlation analysis, information entropy analysis, differential attack analysis and other metrics.

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“…Central to the SubBytes step is the S-box, which is a critical nonlinear element to create turmoil. There are various studies on the optimization [16,17] of the S-box and its applications [18][19][20][21]. For the original AES S-box, Huang et al [22] proposed two garbling schemes aimed at minimizing the total and online times, respectively.…”

Section: Our Ideamentioning

confidence: 99%

“…Since the final truth values of the output are determined by the lsb of the output wire labels, and there are only XOR operations between wire labels in other parts of the AES circuit, flipping the lsb of the input wire labels of the S-box can eventually produce the correct output, thus reducing the number of ciphertexts by converting the encryption of eight output wire labels into only one flip bit string. Furthermore, by introducing optimized S-box structures [16][17][18][19][20][21], where each flip bit string is almost exclusively mapped to an input byte, the security of our garbling scheme can be effectively improved without additional overhead.…”

Section: Our Ideamentioning

confidence: 99%

A Ciphertext Reduction Scheme for Garbling an S-Box in an AES Circuit with Minimal Online Time

Yan,

Lian,

Yang

et al. 2024

Symmetry

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The secure computation of symmetric encryption schemes using Yao’s garbled circuits, such as AES, allows two parties, where one holds a plaintext block m and the other holds a key k, to compute Enc(k,m) without leaking m and k to one another. Due to its wide application prospects, secure AES computation has received much attention. However, the evaluation of AES circuits using Yao’s garbled circuits incurs substantial communication overhead. To further improve its efficiency, this paper, upon observing the special structures of AES circuits and the symmetries of an S-box, proposes a novel ciphertext reduction scheme for garbling an S-box in the last SubBytes step. Unlike the idea of traditional Yao’s garbled circuits, where the circuit generator uses the input wire labels to encrypt the corresponding output wire labels, our garbling scheme uses the input wire labels of an S-box to encrypt the corresponding “flip bit strings”. This approach leads to a significant performance improvement in our garbling scheme, which necessitates only 28 ciphertexts to garble an S-box and a single invocation of a cryptographic primitive for decryption compared to the best result in previous work that requires 8×28 ciphertexts to garble an S-box and multiple invocations of a cryptographic primitive for decryption. Crucially, the proposed scheme provides a new idea to improve the performance of Yao’s garbled circuits. We analyze the security of the proposed scheme in the semi-honest model and experimentally verify its efficiency.

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New color image encryption technique based on three-dimensional logistic map and Grey wolf optimization based generated substitution boxes

Cited by 17 publications

References 27 publications

A Novel Framework for Image Encryption by Integrating Modified Moth Flame Optimization and Logistic Chaotic Map for Enhanced Security

A Novel Framework for Image Encryption by Integrating Modified Moth Flame Optimization and Logistic Chaotic Map for Enhanced Security

Research on Chaotic Image Encryption Based on Fibonacci-ILogistic-IHenon

A Ciphertext Reduction Scheme for Garbling an S-Box in an AES Circuit with Minimal Online Time

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