CYBER SECURITY AND ARTIFICIAL INTELLIGENCE: REVOLUTIONARY TRENDS CREATING THE FUTURE

Artificial intelligence (AI) has transformed the landscape of digital security with its most advanced technologies designed to enhance threat detection, incident response, and systems resilience. AI-powered systems equipped with machine learning (ML)/deep learning (DL) enable real-time anomaly detection, malicious activity detection, and cyber threat mitigation, among other capabilities. But this technical evolution presents two problems: while AI is enhancing cybersecurity defences, it is also providing malicious actors with the ability to automate intricate cyberattacks. Adversarial attacks, data dependence and computation barrier make AI systems much less effective. The ethical consequences as to algorithmic bias and privacy concerns highlight the importance of deploying AI responsibly.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-20
DOI
https://doi.org/10.5281/zenodo.14899833
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

CYBER SECURITY AND ARTIFICIAL INTELLIGENCE: REVOLUTIONARY TRENDS CREATING THE FUTURE

Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

CYBER SECURITY AND ARTIFICIAL INTELLIGENCE: REVOLUTIONARY TRENDS CREATING THE FUTURE

article en

Abstract

Artificial intelligence (AI) has transformed the landscape of digital security with its most advanced technologies designed to enhance threat detection, incident response, and systems resilience. AI-powered systems equipped with machine learning (ML)/deep learning (DL) enable real-time anomaly detection, malicious activity detection, and cyber threat mitigation, among other capabilities. But this technical evolution presents two problems: while AI is enhancing cybersecurity defences, it is also providing malicious actors with the ability to automate intricate cyberattacks. Adversarial attacks, data dependence and computation barrier make AI systems much less effective. The ethical consequences as to algorithmic bias and privacy concerns highlight the importance of deploying AI responsibly.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 74%
Adversarial Robustness in Machine Learning
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