Predicting cyberspace intrusions using machine learning algoritms

The article presents possible strategies and approaches to address the growing cybersecurity threat landscape, new trends and innovations, such as artificial intelligence and machine learning for cyber threat detection and automation. The paper presents well-known machine learning classifiers for data classification. The dataset has been taken from a report by the Center for Strategic and International Studies. The presented model accuracy assessment study has been significant variation among algorithms based on different network intrusion detection systems.

Authors

Publication Details

Journal
Advances in Cyber-Physical Systems
Published
2025-05-02
DOI
https://doi.org/10.23939/acps2025.01.059
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting cyberspace intrusions using machine learning algoritms

Tinatin Mshvidobadze
Advances in Cyber-Physical Systems
Network Security and Intrusion Detection
article

Predicting cyberspace intrusions using machine learning algoritms

Tinatin Mshvidobadze
article en

Abstract

The article presents possible strategies and approaches to address the growing cybersecurity threat landscape, new trends and innovations, such as artificial intelligence and machine learning for cyber threat detection and automation. The paper presents well-known machine learning classifiers for data classification. The dataset has been taken from a report by the Center for Strategic and International Studies. The presented model accuracy assessment study has been significant variation among algorithms based on different network intrusion detection systems.

Advances in Cyber-Physical SystemsVol. 10(1)
Openalex Percentile: Top 86%
Network Security and Intrusion Detection
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Predicting cyberspace intrusions using machine learning algoritms — Tinatin Mshvidobadze · Advances in Cyber-Physical Systems (2025) | TGRS Research Map | TGRS