UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

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Published in:

Volume 12 Issue 8
August-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRHC06015


Registration ID:
568522

Page Number

120-124

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Title

BEYOND RULES: HOW AI IS REDEFINING FRAUD DETECTION AND CYBER SECURITYDEFENCES

Authors

Abstract

The escalating sophistication of financial fraud and cyber threats has outpaced the capabilities of conventional, rule-based security systems. This paper examines how Artificial Intelligence (AI) is fundamentally redefining fraud detection and cyber security by moving from static rules to a dynamic, predictive, and adaptive paradigm. While traditional systems rely on a limited set of known indicators, AI leverages sophisticated machine learning models to analyze massive, complex datasets, identifying subtle anomalies and patterns that human analysts or rule engines would miss. In fraud detection, AI's transformative power is evident in real-time anomaly detection, where algorithms instantly flag transactions that deviate from established baselines, drastically reducing the window of opportunity for fraudulent actors. Techniques like graph neural networks are also uncovering intricate fraud rings by analyzing relationships between accounts and devices. In cyber security, AI has enabled a similar leap forward. Predictive threat intelligence allows systems to anticipate and neutralize potential attacks before they launch, while AI-powered malware detection and automated incident response significantly reduce containment time. This shift, however, brings challenges like the need for explainable AI to build trust and the threat of adversarial AI—where attackers use AI to craft evasive attacks. Ultimately, AI represents a fundamental shift from a reactive, rule-based approach to a proactive, intelligent defense strategy, creating a powerful symbiosis between human expertise and automated intelligence.

Key Words

Artificial Intelligence, Machine Learning, Fraud Detection, Cyber security, Anomaly Detection, Predictive Analytics, Explainable AI, Adversarial AI, Behavioral Biometrics.

Cite This Article

"BEYOND RULES: HOW AI IS REDEFINING FRAUD DETECTION AND CYBER SECURITYDEFENCES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.120-124, August-2025, Available :http://www.jetir.org/papers/JETIRHC06015.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"BEYOND RULES: HOW AI IS REDEFINING FRAUD DETECTION AND CYBER SECURITYDEFENCES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. pp120-124, August-2025, Available at : http://www.jetir.org/papers/JETIRHC06015.pdf

Publication Details

Published Paper ID: JETIRHC06015
Registration ID: 568522
Published In: Volume 12 | Issue 8 | Year August-2025
DOI (Digital Object Identifier):
Page No: 120-124
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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