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Title: Advanced encryption standard algorithm versus extreme learning machine based weight: A comparative study
Authors: Hayfaa A. Atee, Robiah Ahmad, Norliza Mohd. Noor, Abidulkarim K. Ilijan
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2017
Volume: 12
Issue: 3
Language: English
Advanced Encryption Standard (AES) is being widely used ciphering/deciphering system has emerged asa standard benchmark. Due to rapid advancement in the hardware specifications, the architecture security of AES became a major concern. Furthermore, the newly developed machine learning dependent encryption architecture called Extreme Learning Machine Based Weight (ELMWi) appears more suitable for sundry cryptographic implementations. This article compares the performance of ELMWi with AES via statistical evaluation, where the parameters such as sensitivity, visual imperceptibility metrics, and key space are determined. Results reveal their similar performances. It is further argued that ELMWi out performs the AES in perspective of architecture implementation.
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