Journal of Primeasia

Integrative Disciplinary Research | Online ISSN 3064-9870 | Print ISSN 3069-4353
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Journal of Primeasia

Volume 3 Number 1 2022

Article Contents

RESEARCH ARTICLE   (Open Access)
Contents Vol 3 (1)

Artificial Intelligence Driven Threat Detection for Strengthening Cyber Defense

Anik Biswas1*, Md Nazmuddin Moin Khan2

+ Author Affiliations

Journal of Primeasia 3 (1) 1-8 https://doi.org/10.25163/ primeasia.3110485

Submitted: 03 January 2022 Revised: 01 March 2022  Published: 10 March 2022 

Abstract

Background: The frequency of cyberattacks against U.S. networks has risen by 43% since 2018 which reveals ongoing weaknesses in traditional defense systems. Traditional rule-based systems fail to detect new and zero-day threats which makes Artificial Intelligence (AI) the most promising solution for handling complex cyber threats through prediction and prevention.

Methods: The study combines survey data from 270 cybersecurity experts with laboratory tests of experimental models to assess how Artificial Intelligence strengthens United States cyber defense systems. The researchers trained three algorithms Random Forest (RF) and Support Vector Machine (SVM) and Deep Neural Network (DNN) using actual intrusion data. The evaluation process measured Precision (P), Recall (R), F1-score and computational efficiency through statistical validation which used cross-validation and ANOVA methods.

Results: AI-based systems demonstrated substantial performance improvements. The DNN model delivers precision at 93.6% and recall at 92.8% which performs better than both RF with precision 89.2% and recall 87.5% and SVM with precision 91.4% and recall 90.2%. The system accomplished a 36% decrease in false-positive detection rates while identifying threats at a speed 38% quicker. The survey shows 84% of participants experienced improved operational efficiency through automation yet 79% of them reported quicker incident handling.

Conclusion: The United States achieves better cyber defense readiness through AI threat detection systems which combine real-time anomaly detection with machine learning capabilities. AI frameworks combination into national cybersecurity substructure leads to automated organizations which bring better prediction abilities and improved digital scheme resilience.

Keywords: Machine Learning, Artificial Intelligence, Cybersecurity, Threat Detection, U.S, Cyber Defense

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