Nada Mohammed Murad¹, Adnan Yousif Dawod², Saadaldeen Rashid Ahmed^3,4,*, Ravi Sekhar⁵, Pritesh Shah⁵

Intelligent Automation & Soft Computing, Vol.40, pp. 1-27, 2025, DOI:10.32604/iasc.2024.058624 - 10 January 2025

Abstract This study introduces an innovative hybrid approach that integrates deep learning with blockchain technology to improve cybersecurity, focusing on network intrusion detection systems (NIDS). The main goal is to overcome the shortcomings of conventional intrusion detection techniques by developing a more flexible and robust security architecture. We use seven unique machine learning models to improve detection skills, emphasizing data quality, traceability, and transparency, facilitated by a blockchain layer that safeguards against data modification and ensures auditability. Our technique employs the Synthetic Minority Oversampling Technique (SMOTE) to equilibrate the dataset, therefore mitigating prevalent class imbalance difficulties… More >

Muhammad Rashid^*, Majid Alotaibi

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6849-6865, 2023, DOI:10.32604/cmc.2023.032849 - 28 December 2022

Abstract We have proposed a flexible coprocessor key-authentication architecture for 80/112-bit security-related applications over field by employing Elliptic-curve Diffie Hellman (ECDH) protocol. Towards flexibility, a serial input/output interface is used to load/produce secret, public, and shared keys sequentially. Moreover, to reduce the hardware resources and to achieve a reasonable time for cryptographic computations, we have proposed a finite field digit-serial multiplier architecture using combined shift and accumulate techniques. Furthermore, two finite-state-machine controllers are used to perform efficient control functionalities. The proposed coprocessor architecture over and is programmed using Verilog and then implemented on Xilinx Virtex-7 FPGA More >