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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Ahmed M. Hasan
University of Technology
Computer Science & IT Electrical & Electronics Engineering

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Design and implementation of proposed 320 bit RC6-cascaded encryption/decryption cores on altera FPGA Ashwaq T. Hashim; Ahmed M. Hasan; Hayder M. Abbas
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v10i6.pp6370-6379

Abstract

This paper attempts to build up a simple, strong and secure cryptographic algorithm. The result of such an attempt is “RC6-Cascade” which is 320-bits RC6 like block cipher. The key can be any length up to 256 bytes. It is a secret-key block cipher with precise characteristics of RC6 algorithm using another overall structure design. In RC6-Cascade, cascading of F-functions will be used instead of rounds. Moreover, the paper investigates a hardware design to efficiently implement the proposed RC6-Cascade block cipher core on field programmable gate array (FPGA). An efficient compact iterative architecture will be designed for the F-function of the above algorithm. The goal is to design a more secure algorithm and present a very fast encryption core for low cost and small size applications.
Automated brain tumor detection of MRI image based on hybrid image processing techniques Lina A. Salman; Ashwaq T. Hashim; Ahmed M. Hasan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 4: August 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i4.22760

Abstract

Primary challenges are the identification, segmentation, and extraction of the afflicted area from the scanning of magnetic resonance. However, it is a time-consuming and tiresome for clinical specialists. In this paper, an automated brain tumor system is proposed. The proposed system employs hybrid image processing techniques such as contrast correction, histogram normalization, thresholding techniques, arithmetic, and morphological operations to quarantine nearby organs and other tissue from the brain for improving the localization of the affected region. At first, the skull stripping process is proposed to segregate the non-designated regions to extract the designated brain regions. Those resultant brain region images are further subjected to discover the brain tumor. The planned scheme is studied on the magnetic resonance (MR) images with the use of T1, T2, T1c, and fluid-attenuated inversion recovery (FLAIR). The proposed hybrid method employed. The results reveal that the proposed method is quite efficient to extract the tumor region. The accuracy rate for segmentation and separation of area of interest in brain tumor reached to 95%. Finally, the significance of the proposed procedure is confirmed using the real image clinical dataset got from ten patients were diagnosed as begin, malignant, and metastatic brain tumors in Al-Yarmouk and Baghdad teaching hospital in Baghdad, Iraq.
Co-Authors Ashwaq T. Hashim Hayder M. Abbas Lina A. Salman