Evidence map›Paper›PMID 40594089›Full record

ArticleScientific reports2025

A hybrid AI-Blockchain security framework for smart grids.

Yazeed Yasin Ghadi, Tehseen Mazhar, Tariq Shahzad, Ines Hilali Jaghdam, Sanwar Khan, Muhammad Amir Khan, Habib Hamam

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yazeed Yasin GhadiDepartment of Computer Science and Software Engineering, Al Ain University, Abu Dhabi, 12555, United Arab Emirates.
Tehseen MazharSchool of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan. tehseenmazhar719@gmail.com.
Tariq ShahzadDepartment of Computer Engineering, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, 57000, Pakistan.
Ines Hilali JaghdamDepartment of Computer Science and Information Technology,Applied College, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Sanwar KhanSchool of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan.
Muhammad Amir KhanSchool of Computing Sciences Faculty of Computer Science and Mathematics,, Universiti Teknologi MARA, Shah Alam, 40450, Selangor, Malaysia. amirkhan@uitm.edu.my.
Habib HamamFaculty of Engineering, Uni de Moncton, Moncton, NB, E1A3E9, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial intelligenceBlockchainMachine learningRenewable energySmart gridsSmart meters

Identifiers

PMID40594089
PMCPMC12217142

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.