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

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 4 | April 2026

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Published in:

Volume 11 Issue 3
March-2024
eISSN: 2349-5162

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

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2403708


Registration ID:
534761

Page Number

h38-h45

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Title

Transforming Incident Responses, Automating Security Measures, and Revolutionizing Defence Strategies through AI-Powered Cybersecurity

Abstract

Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (Industry 4.0), which can protect Internet-connected systems from cyber threats, attacks, damage, or unauthorized access. To intelligently solve cybersecurity issues, popular AI techniques can use machine learning and deep learning methods, the concept of natural language processing, knowledge representation and reasoning, and the concept of knowledge or rule-based expert systems modeling. Based on these AI methods, in this paper, we present a comprehensive view of AI-driven Cybersecurity that can play an important role in intelligent cybersecurity services and management. Security intelligence modelling based on AI methods can make cybersecurity computing more automated and intelligent than conventional security systems. This paper also highlights several research directions within the scope of our study, which can help researchers do future research in the area. Overall, this paper’s ultimate objective is to serve as a reference point and guidelines for cybersecurity researchers and industry professionals, especially from an intelligent computing or AI-based technical point of view. This paper highlights how AI revolutionizes cybersecurity by enhancing threat detection, automating processes, and providing intelligent defence strategies. By leveraging machine learning, deep learning, and other AI techniques, it aims to empower cybersecurity professionals in safeguarding digital assets against evolving cyber threats.

Key Words

Incident Responses, Automating security measures, AI cyber security, Defence strategies, AI-powered IR

Cite This Article

"Transforming Incident Responses, Automating Security Measures, and Revolutionizing Defence Strategies through AI-Powered Cybersecurity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.h38-h45, March-2024, Available :http://www.jetir.org/papers/JETIR2403708.pdf

ISSN


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

"Transforming Incident Responses, Automating Security Measures, and Revolutionizing Defence Strategies through AI-Powered Cybersecurity", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. pph38-h45, March-2024, Available at : http://www.jetir.org/papers/JETIR2403708.pdf

Publication Details

Published Paper ID: JETIR2403708
Registration ID: 534761
Published In: Volume 11 | Issue 3 | Year March-2024
DOI (Digital Object Identifier):
Page No: h38-h45
Country: Yardley, PA, United States of America .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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