Cyber Threat Attack Level Detection Using Machine Learning

This study focuses on creating a machine learning-based system for identifying cyber-attacks in real time using network data, system logs, and attack history. The work presents a thorough methodology that includes data collection, preprocessing, feature selection, model training, and real-time monit...

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Bibliographische Detailangaben
Veröffentlicht in:	2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) S. 442 - 449
Hauptverfasser:	R, Rahul, Mythili, S.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 05.02.2025
Schlagworte:	Accuracy Alert System Anomaly Detection Automated Threat Mitigation Cyber Threat Detection Data models Django Framework Feature extraction Incident Response Network Traffic Analysis Optimization Prevention and mitigation Real-time Monitoring Real-time systems Security Logs SQL injection Support vector machines Telecommunication traffic Threat assessment Threat Management
Online-Zugang:	Volltext
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