Comparative Assessment of Hash Functions in Securing Encrypted Images
Received: 9 September 2024 | Revised: 3 October 2024 and 13 October 2024 | Accepted: 16 October 2024 | Online: 10 November 2024
Corresponding author: Mohammed Al-Husainy
Abstract
Different encryption methods have been developed to securely transmit confidential images over the Internet and combat the increasing cybercrime. Many of these methods use hash functions to enhance encryption strength. Due to the lack of a comprehensive evaluation of how different hash functions affect image encryption, this study presents a comparative analysis of the performance of various hash functions as encryption keys and analyzes their security, speed, and efficiency. The source image is first processed as a series of bytes. The bytes are divided into byte vectors, each with a length that matches the length of the hash value of a specified hash function. An XOR operation is performed between the hash value bytes and the associated byte vector. The bytes are reordered in each vector according to the ascending order of the associated hash value. Several metrics, such as Normalized Mean Absolute Error (NMAE), Peak Signal to Noise Ratio (PSNR), entropy, key size, and hash time, were used to evaluate the performance of different hash functions in image encryption. The results showed a clear variation in using various hash functions in terms of security, speed, and efficiency. With NMAE>72%, PSNR<6.62 dB, and Entropy>7.999 bpp, the use of the SHA family and MD5 is recommended in applications that need to achieve a high level of distortion in encrypted images. To resist brute-force attacks on the key, Blake2b, SHA512, and Whirlpool are the best choices with a key size of 512 bits. The Tiger is the fastest hash function, requiring the least average time of 0.372 seconds to complete the encryption process, making it the best choice for real-time applications. These findings help to choose the appropriate hash function in developing cryptographic techniques for a particular area.
Keywords:
cryptography, secure image, hash functions, XOR operation, cybersecurityDownloads
References
M. N. Alenezi, H. Alabdulrazzaq, and N. Q. Mohammad, "Symmetric Encryption Algorithms: Review and Evaluation study," International Journal of Communication Networks and Information Security (IJCNIS), vol. 12, no. 2, 2020.
U. Diaa, "A Deep Learning Model to Inspect Image Forgery on SURF Keypoints of SLIC Segmented Regions," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 12549–12555, Feb. 2024.
H. Gao and T. Gao, "Double verifiable image encryption based on chaos and reversible watermarking algorithm," Multimedia Tools and Applications, vol. 78, no. 6, pp. 7267–7288, Mar. 2019.
H. M. Ghadirli, A. Nodehi, and R. Enayatifar, "An overview of encryption algorithms in color images," Signal Processing, vol. 164, pp. 163–185, Nov. 2019.
A. K. Chattopadhyay, S. Saha, A. Nag, and J. P. Singh, "A verifiable multi-secret image sharing scheme based on DNA encryption," Multimedia Tools and Applications, Apr. 2024.
I. Bashir, F. Ahmed, J. Ahmad, W. Boulila, and N. Alharbi, "A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids," Entropy, vol. 21, no. 11, Nov. 2019, Art. no. 1132.
S. Dhall and K. Yadav, "Cryptanalysis of substitution-permutation network based image encryption schemes: a systematic review," Nonlinear Dynamics, vol. 112, no. 17, pp. 14719–14744, Sep. 2024.
M. Sedighi, S. K. Mahmoudi, and A. S. Amini, "Proposing a new method for encrypting satellite images based ON hash function and chaos parameters," The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-4-W18, pp. 949–953, Oct. 2019.
H. Lan and R. Ye, "A Novel Image Encryption Algorithm Based on Secure Hash Function and Galois Field," in 2019 2nd International Conference on Safety Produce Informatization (IICSPI), Chongqing, China, Nov. 2019, pp. 98–102.
S. Zhou, P. He, and N. Kasabov, "A Dynamic DNA Color Image Encryption Method Based on SHA-512," Entropy, vol. 22, no. 10, Oct. 2020, Art. no. 1091.
E. Z. Zefreh, "An image encryption scheme based on a hybrid model of DNA computing, chaotic systems and hash functions," Multimedia Tools and Applications, vol. 79, no. 33, pp. 24993–25022, Sep. 2020.
M. Gafsi, M. A. Hajjaji, J. Malek, and A. Mtibaa, "Efficient Encryption System for Numerical Image Safe Transmission," Journal of Electrical and Computer Engineering, vol. 2020, no. 1, 2020, Art. no. 8937676.
C. Zhu, Z. Gan, Y. Lu, and X. Chai, "An image encryption algorithm based on 3-D DNA level permutation and substitution scheme," Multimedia Tools and Applications, vol. 79, no. 11, pp. 7227–7258, Mar. 2020.
"Support, Image Databases - ImageProcessingPlace.Com." [Online]. Available: https://www.imageprocessingplace.com/downloads_V3/root_downloads/image_databases/standard_test_images.zip.
A. Saini and R. Sehrawat, "Enhancing Data Security through Machine Learning-based Key Generation and Encryption," Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 14148–14154, Jun. 2024.
M. Abbas Fadhil Al-Husainy, H. A. A. Al-Sewadi, and B. Al-Shargabi, "Image Encryption using a Binary Search Tree Structure-Based Key," International Journal of Computing and Digital Systems, vol. 12, no. 1, pp. 823–836, Sep. 2022.
E. Aruna and A. Sahayadhas, "Blockchain-Inspired Lightweight Dynamic Encryption Schemes for a Secure Health Care Information Exchange System," Engineering, Technology & Applied Science Research, vol. 14, no. 4, pp. 15050–15055, Aug. 2024.
M. A. F. Al-Husainy, H. A. A. Al-Sewadi, and A. M. Sayed, "Using the 3D Protein Structure as Key to Encrypt Images," Journal of Information and Organizational Sciences, vol. 47, no. 2, Dec. 2023.
L. Yang, S. Bi, M. G. R. Faes, M. Broggi, and M. Beer, "Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric," Mechanical Systems and Signal Processing, vol. 162, Jan. 2022, Art. no. 107954.
M. Alawida, A. Samsudin, N. Alajarmeh, J. S. Teh, M. Ahmad, and W. H. Alshoura, "A Novel Hash Function Based on a Chaotic Sponge and DNA Sequence," IEEE Access, vol. 9, pp. 17882–17897, 2021.
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Copyright (c) 2024 Ghayth Al-Asad, Mohammed Al-Husainy, Mohammad Bani-Hani, Ala’eddin Al-Zu’bi, Sara Albatienh, Hazem Abuoliem
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