International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 6 (November-December 2025) Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 6
November-December 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Artificial Intelligence in Cybersecurity: The Risk, Governance, and Trust Frameworks

Author(s) Mr. Ayotunde Oyatomi
Country United States
Abstract Artificial Intelligence (AI) is increasingly becoming a part of cybersecurity solutions, which provide superior threat detection, predictive analytics, and automated protection. Nevertheless, implementing AI also introduces specific weaknesses, including adversarial attacks, data poisoning, and model drift, as well as more global issues of accountability, compliance, and stakeholder trust. This paper proposes the Risk-Governance-Trust (RGT) Framework, which is operationalized through a new Risk-Trust Scoring Algorithm (RTSA) to evaluate AI-enabled cybersecurity systems holistically. It is a framework that brings together three pillars: (a) risk assessment, which assesses technical vulnerabilities based on likelihood, impact, and detectability; (b) governance, which ensures accountability, compliance with standards, and lifecycle monitoring; and (c) trust, which is measured in terms of transparency, fairness, and accountability. The RTSA is a composite indicator with a range of -1 to +1, indicating the resilience and trustworthiness of AI-driven systems. The algorithm has proven to be useful in financial services, healthcare, and critical infrastructure, with case-based validation providing interpretable, scalable, and actionable insights. Findings indicate that AI plays a significant role in enhancing cyber defense; however, its application should be accompanied by robust governance and trust systems. The RGT framework provides organizations and policymakers with a practical and structured tool for assessing and implementing AI in cybersecurity responsibly.
Keywords Artificial Intelligence, Cybersecurity, Risk Assessment, Governance, Trust Frameworks, Risk–Trust Scoring Algorithm (RTSA)
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-02
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.57626
Short DOI https://doi.org/hbdrfh
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 5Cover Page Vol 7 Isu 4Cover Page Vol 7 Isu 3

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com