Enhancing Cyber-Physical System Security through AI-Driven Intrusion Detection and Blockchain Integration

Authors

  • N. Purandhar Assistant Professor, Department of CSE(Artificial Intelligence) School of Computers, Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh - 517325, India
  • M. Rajendrian Professor, Department of Artificial Intelligence and Data Science , VSB Engineering College, Karur,Tamil Nadu, India
  • Ahmed Mudassar Ali Professor Department of Information Technology S.A. Engineering College Chennai
  • M. Sangeetha Assistant Professor, DEPARTMENT OF B.Sc.IT, PSGR KRISHNAMMAL COLLEGE FOR WOMEN,
  • Mukesh Soni Dr. D. Y. Patil Vidyapeeth, Pune, Dr. D. Y. Patil School of Science & Technology, Tathawade, Pune Division of Research and Development, Lovely Professional University, Phagwara, India
  • D. Arul Kumar Associate Professor, Department of ECE, Panimalar Engineering College, Poonamallee, Chennai 600 123.

DOI:

https://doi.org/10.22399/ijcesen.1168

Keywords:

Cyber-Physical Systems (CPS), Blockchain Security, Deep learning, Decentralized Security, Cybersecurity in CPS

Abstract

Cyber-Physical Systems (CPS) play a critical role in modern industries, smart grids, healthcare, and autonomous transportation. However, their increasing connectivity makes them vulnerable to cyber threats. This research proposes an AI-driven Intrusion Detection System (AI-IDS) integrated with Blockchain Technology to enhance CPS security. The AI-IDS employs deep learning models for anomaly detection, leveraging graph-based machine learning and federated learning to improve real-time threat mitigation. Additionally, blockchain ensures data integrity, access control, and decentralized security through smart contracts and consensus mechanisms. The framework is validated using real-world CPS datasets, demonstrating improved detection accuracy, reduced false alarms, and resilience against adversarial attacks. This hybrid approach enhances scalability, trustworthiness, and real-time defense in cyber-physical environments

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Published

2025-03-02

How to Cite

N. Purandhar, M. Rajendrian, Ahmed Mudassar Ali, M. Sangeetha, Mukesh Soni, & D. Arul Kumar. (2025). Enhancing Cyber-Physical System Security through AI-Driven Intrusion Detection and Blockchain Integration. International Journal of Computational and Experimental Science and Engineering, 11(1). https://doi.org/10.22399/ijcesen.1168

Issue

Vol. 11 No. 1 (2025): IJCESEN

Section

Research Article

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