AI-Powered Security Information and Event Management: A Review of Deep Learning Approaches for Modern Cybersecurity

Cyber threats are increasing with rapidly emerging digital infrastructure. In that scenario, even a reasonable pace cannot be maintained by traditional SIEM systems. Deep learning technologies such as Variational Autoencoders and Graph Neural Networks have to be embedded into SIEMbased systems so that anomaly activity might be detected and zero-day threats also identified with accurate and timely generation of the alerts. We critically compare recent advances in deep learning-based SIEM with their more practical applications in detecting complex cyberattacks and focus on how AI improves the effectiveness of the efficacy of reports from SIEMs and technical challenges associated with those methodologies.

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2025-12-17
DOI
https://doi.org/10.64388/irev9i6-1712992
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Security Information and Event Management: A Review of Deep Learning Approaches for Modern Cybersecurity

Iconic Research and Engineering Journals
Network Security and Intrusion Detection
article

AI-Powered Security Information and Event Management: A Review of Deep Learning Approaches for Modern Cybersecurity

article en

Abstract

Cyber threats are increasing with rapidly emerging digital infrastructure. In that scenario, even a reasonable pace cannot be maintained by traditional SIEM systems. Deep learning technologies such as Variational Autoencoders and Graph Neural Networks have to be embedded into SIEMbased systems so that anomaly activity might be detected and zero-day threats also identified with accurate and timely generation of the alerts. We critically compare recent advances in deep learning-based SIEM with their more practical applications in detecting complex cyberattacks and focus on how AI improves the effectiveness of the efficacy of reports from SIEMs and technical challenges associated with those methodologies.

Iconic Research and Engineering JournalsVol. 9(6)
Industry, innovation and infrastructure
Openalex Percentile: Top 36%
Network Security and Intrusion Detection
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