ENSURING CYBERSECURITY WITH ARTIFICIAL INTELLIGENCE

The relentless evolution of cyber threats, from ransomware to advanced persistent threats (APTs), has exposed the limitations of traditional cybersecurity approaches. Artificial Intelligence (AI) has emerged as a cornerstone technology, offering sophisticated tools for threat detection, predictive analytics, automated response, and threat intelligence. By leveraging machine learning, deep learning, and natural language processing, AI enables adaptive and scalable defenses against increasingly complex attacks. This article provides an in-depth exploration of AI’s transformative role in cybersecurity, detailing its applications, addressing challenges such as adversarial attacks, data biases, and ethical concerns, and envisioning future advancements. Through a comprehensive analysis, it underscores AI’s potential to fortify digital ecosystems while highlighting the need for robust strategies to mitigate its limitations.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-06
DOI
https://doi.org/10.5281/zenodo.15348004
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ENSURING CYBERSECURITY WITH ARTIFICIAL INTELLIGENCE

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

ENSURING CYBERSECURITY WITH ARTIFICIAL INTELLIGENCE

article en

Abstract

The relentless evolution of cyber threats, from ransomware to advanced persistent threats (APTs), has exposed the limitations of traditional cybersecurity approaches. Artificial Intelligence (AI) has emerged as a cornerstone technology, offering sophisticated tools for threat detection, predictive analytics, automated response, and threat intelligence. By leveraging machine learning, deep learning, and natural language processing, AI enables adaptive and scalable defenses against increasingly complex attacks. This article provides an in-depth exploration of AI’s transformative role in cybersecurity, detailing its applications, addressing challenges such as adversarial attacks, data biases, and ethical concerns, and envisioning future advancements. Through a comprehensive analysis, it underscores AI’s potential to fortify digital ecosystems while highlighting the need for robust strategies to mitigate its limitations.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 76%
Adversarial Robustness in Machine Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.