Cybersecurity Incidents on Digital Infrastructure and Industrial Networks
Keywords:
Cybersecurity incidents, digital infrastructure, industrial networks, anomaly detection, machine learning, network security, DDoS attacks.Abstract
Cybersecurity incidents pose significant threats to digital infrastructure and industrial networks,leading to operational disruptions, financial losses, and data breaches. With the increasing sophistication of cyberattacks, including DDoS attacks, malware infiltration, and unauthorized access, it is crucial to develop efficient detection mechanisms to safeguard critical systems. This study applies unsupervised machine learning, specifically K-Means clustering, to detect cybersecurity anomalies within network traffic data. By analyzing key network flow features, such as Flow Bytes/s, Packet Length, and Flow Inter-Arrival Time (IAT), this study aims to classify
normal and abnormal traffic patterns to enhance cybersecurity monitoring.
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