A hybrid AI-Blockchain security framework for smart grids.

Journal: Scientific reports
Published Date:

Abstract

This study delves into the vulnerability of the smart grid to infiltration by hackers and proposes methods to safeguard it by leveraging blockchain and artificial intelligence (AI). A categorization and analysis of cyberattacks against smart grids will be conducted, focusing on those targeting their communication layers. The main goal of the work is to address the challenges in this area by implementing novel detection and defense strategies. The authors categorize attacks on smart grid networks based on the communication classes they want to compromise. They propose novel taxonomies specifically designed to detect and implement defense strategies. The study investigates artificial intelligence and blockchain techniques to identify cyber-attacks that employ deceptive data injection. The study indicates that cyberattacks against smart grids are increasing in frequency and complexity. The paper proposes innovative strategies for defense, such as enhancing cybersecurity with artificial intelligence and blockchain technology. The research further enumerates several challenges, such as counterfeit topological data, imprecise data identification, and combining big data with blockchain technology. Given the increasing risks, the study emphasizes the crucial need for robust cybersecurity safeguards in smart grids. This work contributes to the protection of smart grid infrastructures by categorizing attacks, suggesting novel defenses, and exploring solutions integrating artificial intelligence and blockchain technology. Research should prioritize enhancing technology to maximize security and counter emerging attack methods. The intended audience of our paper comprises graduate-level academics and independent researchers.

Authors

  • Yazeed Yasin Ghadi
    Department of Computer Science and Software Engineering, Al Ain University, Abu Dhabi, UAE.
  • Tehseen Mazhar
    Department of Computer Science, Virtual University of Pakistan, Lahore, Punjab, Pakistan.
  • Tariq Shahzad
    Department of Computer Sciences, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, 57000, Pakistan.
  • Ines Hilali Jaghdam
    Department of Computer Science and Information Technology,Applied College, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
  • Sanwar Khan
    School of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan.
  • Muhammad Amir Khan
    Dow College of Biotechnology, Dow University of Health Sciences, Karachi, Pakistan / Department of Pharmacology, Dow College of Pharmacy, Dow University of Health Sciences, Karachi, Pakistan.
  • Habib Hamam
    School of Electrical Engineering, Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South Africa.

Keywords

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