Open Access

ARTICLE

Unveiling CyberFortis: A Unified Security Framework for IIoT-SCADA Systems with SiamDQN-AE FusionNet and PopHydra Optimizer

Kuncham Sreenivasa Rao¹, Rajitha Kotoju², B. Ramana Reddy³, Taher Al-Shehari⁴, Nasser A. Alsadhan⁵, Subhav Singh^6,7,8, Shitharth Selvarajan^9,10,11,*

1 Department of Computer Science and Engineering, Faculty of Science and Technology (ICFAITech), ICFAI Foundation for Higher Education, Hyderabad, 501203, India
2 Department of Computer Science and Engineering, Mahatma Gandhi Institute of Technology, Hyderabad, 500075, India
3 Department of CSE, Chaitanya Bharathi Institute of Technology, Hyderabad, 500075, India
4 Computer Skills, Department of Self-Development Skill, Common First Year Deanship, King Saud University, Riyadh, 11362, Saudi Arabia
5 Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, 12372, Saudi Arabia
6 Chitkara Centre for Research and Development, Chitkara University, Solan, 174103, India
7 Division of Research & Innovation, Uttaranchal University, Dehradun, 248007, India
8 Division of Research and Development, Lovely Professional University, Phagwara, 144411, India
9 School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, LS6 3HF, UK
10 Department of Computer Science and Engineering, Chennai Institute of Technology, Chennai, 600069, India
11 Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, India

* Corresponding Author: Shitharth Selvarajan. Email:

Computers, Materials & Continua 2025, 85(1), 1899-1916. https://doi.org/10.32604/cmc.2025.064728

Received 22 February 2025; Accepted 21 July 2025; Issue published 29 August 2025

Abstract

Protecting Supervisory Control and Data Acquisition-Industrial Internet of Things (SCADA-IIoT) systems against intruders has become essential since industrial control systems now oversee critical infrastructure, and cyber attackers more frequently target these systems. Due to their connection of physical assets with digital networks, SCADA-IIoT systems face substantial risks from multiple attack types, including Distributed Denial of Service (DDoS), spoofing, and more advanced intrusion methods. Previous research in this field faces challenges due to insufficient solutions, as current intrusion detection systems lack the necessary accuracy, scalability, and adaptability needed for IIoT environments. This paper introduces CyberFortis, a novel cybersecurity framework aimed at detecting and preventing cyber threats in SCADA-IIoT systems. CyberFortis presents two key innovations: Firstly, Siamese Double Deep Q-Network with Autoencoders (Siamdqn-AE) FusionNet, which enhances intrusion detection by combining deep Q-Networks with autoencoders for improved attack detection and feature extraction; and secondly, the PopHydra Optimiser, an innovative solution to compute reinforcement learning discount factors for better model performance and convergence. This method combines Siamese deep Q-Networks with autoencoders to create a system that can detect different types of attacks more effectively and adapt to new challenges. CyberFortis is better than current top attack detection systems, showing higher scores in important areas like accuracy, precision, recall, and F1-score, based on data from CICIoT 2023, UNSW-NB 15, and WUSTL-IIoT datasets. Results from the proposed framework show a 97. 5% accuracy rate, indicating its potential as an effective solution for SCADA-IIoT cybersecurity against emerging threats. The research confirms that the proposed security and resilience methods are successful in protecting vital industrial control systems within their operational environments.

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