Advanced encryption standard algorithm versus extreme learning machine based weight: a comparative study

• Main Authors: Abdulzahra, Hayfaa Atee, Ahmad, Robiah, Mohd. Noor, Norliza, Abidulkarim, Kadhim Ilijan
• Format: Article
• Published: Asian Research Publishing Network 2017
• Subjects: T Technology
• Online Access: http://eprints.utm.my/id/eprint/66189/; http://www.arpnjournals.org/jeas/research_papers/rp_2017/jeas_0217_5696.pdf

Advanced Encryption Standard (AES) is beingwidely used ciphering/deciphering system has emerged asa standard benchmark. Due to rapid advancement in the hardware specifications, thearchitecture 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 AESvia 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 outperforms the AES in perspective of architecture implementation.