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The Integration of Artificial Intelligence (AI) Into Cybersecurity
Subject area: Science,Engineering and Technology · Area of research: Digital Technology
Abstract
The rapid evolution of cyber threats demands advanced defence mechanisms beyond traditional security approaches. Artificial Intelligence (AI) has emerged as a transformative force in cybersecurity, enhancing threat detection, response, and prevention through machine learning (ML), behavioural analytics, and automation. AI-powered systems analyse vast datasets in real-time, identifying anomalies, predicting attacks, and mitigating risks faster than human analysts. Key applications include malware detection, phishing prevention, network intrusion detection, and automated incident response. AI also strengthens authentication through behavioural biometrics and adaptive security policies. However, challenges such as adversarial AI attacks, data privacy concerns, and high implementation costs remain significant hurdles. The future of AI in cybersecurity lies in deep learning advancements, quantum-resistant encryption, and autonomous security systems. While AI offers unparalleled advantages in combating cyber threats, its integration requires a balanced approach, combining machine intelligence with human expertise to ensure robust and ethical cybersecurity frameworks. This abstract explores the benefits, challenges, and future trends of AI-driven cybersecurity, highlighting its critical role in safeguarding digital ecosystems.
How to cite this paper
@article{1707706,
author = {Dhiraj Prabhakar Shisat},
title = {The Integration of Artificial Intelligence (AI) Into Cybersecurity},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {10},
pages = {1-2},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1707706.pdf},
abstract = {The rapid evolution of cyber threats demands advanced defence mechanisms beyond traditional security approaches. Artificial Intelligence (AI) has emerged as a transformative force in cybersecurity, enhancing threat detection, response, and prevention through machine learning (ML), behavioural analytics, and automation. AI-powered systems analyse vast datasets in real-time, identifying anomalies, predicting attacks, and mitigating risks faster than human analysts. Key applications include malware detection, phishing prevention, network intrusion detection, and automated incident response. AI also strengthens authentication through behavioural biometrics and adaptive security policies. However, challenges such as adversarial AI attacks, data privacy concerns, and high implementation costs remain significant hurdles. The future of AI in cybersecurity lies in deep learning advancements, quantum-resistant encryption, and autonomous security systems. While AI offers unparalleled advantages in combating cyber threats, its integration requires a balanced approach, combining machine intelligence with human expertise to ensure robust and ethical cybersecurity frameworks. This abstract explores the benefits, challenges, and future trends of AI-driven cybersecurity, highlighting its critical role in safeguarding digital ecosystems.},
month = {April},
}