JOURNAL ARTICLE

AI-Powered Cybersecurity: Detecting and Preventing Modern Threat

Gopalakrishnan Arjunan

Year: 2024 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

This paper explores upon the area of artificial intelligence and cybersecurity, emphasizing the transformative potential of AI in identifying and mitigating modern cyber threats. Some of the key applications are AI-powered threat detection, anti- phishing, defense against malware and ransomware, and real-time network traffic analysis. With the integration of ML algorithms, the platforms like Darktrace, Cylance, Proofpoint, and IBM QRadar are progressing with threat intelligence and automated incident response, making it easier for organizations to predict and thwart evolving threats. The use of AI is improving endpoint protection, fraud detection, and cloud security -proactive measures to vulnerabilities. Investment trend shows that funding does positively correlate with AI-based cybersecurity apps efficiency. This report underlines the crucial role that AI plays today in modern cybersecurity, tackling increasing sophisticated cyber-attacks, while simultaneously noting opportunities for further developments in threat mitigation strategies.

Keywords:
Transformative learning Malware Key (lock) Investment (military) IBM Cloud computing Business intelligence

Metrics

1
Cited By
1.31
FWCI (Field Weighted Citation Impact)
0
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Optimization Algorithms Research
Physical Sciences →  Mathematics →  Numerical Analysis
Metaheuristic Optimization Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Stochastic Gradient Optimization Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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