Mohammed A. F. Al-Husainy, Department of Computer Science, Middle East University, Amman, Jordan
Hamza A. A. Al-Sewadi, Department of Communication Engineering, Iraq University College, Iraq
So many cryptographic systems are secure and in use today, such as AES, 3DES, Blowfish, RC4, etc., however, new ideas and innovations are still highly required due to the ever-growing threats to data security. This paper presents a novel idea for symmetric image encryption utilizing binary search tree mechanism for generating the encryption/decryption key. This key consists of local and global parts with free user controlled key length, hence, it provides good flexibility for high security, which is manifested in the encrypted images. For every single byte of the encrypted image, the substitution and transposition operations involve all the image contents, fulfilling Shannon’s diffusion and confusion concept. Experimental computations of the proposed encryption method have shown satisfactory visual and image energy distribution histogram. Besides, the Peak Signal to Noise Ratio (PSNR) and Normalized Mean Absolute Error (NMAE) measurement results were comparable with the widely used cryptosystems such as DES and AES. On the other hand, the proposed method has flexible key length and shorter execution time by 10% or more depending on the image contents.
Avalanche effect; security; image encryption
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APA:
Al-Husainy, M. A. F., & Al-Sewadi, H. A. A. (2019). Implementing Binary Search Tree Concept for Image Cryptography. International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, 130, 21-32. doi: 10.33832/ijast.2019.130.03.
MLA:
Al-Shargabi, Bassam, et al. “Enhancing Multi-Layer Perceptron for Breast Cancer Prediction.” International Journal of Advanced Science and Technology, ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 130, 2019, pp. 11-20. IJAST, http://article.nadiapub.com/IJAST/Vol130/2.html.
IEEE:
[1] B. Al-Shargabi, F. Al-Shami, and R. S. Alkhawaldeh, “Enhancing Multi-Layer Perceptron for Breast Cancer Prediction.” International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238(Print); 2207-6360 (Online), NADIA, vol. 130, pp. 11-20, Sep. 2019.
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