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Efficient Machine Learning-Based Security Monitoring and Cyberattack Classification of Encrypted Network Traffic in Industrial Control Systems
Security monitoring is a key aspect to detect cyberattacks against industrial control systems.
However, with the increasing use of encryption in industrial communication protocols …
However, with the increasing use of encryption in industrial communication protocols …
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting
Anomaly detection in network traffic is crucial for maintaining the security of computer
networks and identifying malicious activities. One of the primary approaches to anomaly …
networks and identifying malicious activities. One of the primary approaches to anomaly …
Analysis of statistical distribution changes of input features in network traffic classification domain
This study investigates the evolving landscape of network traffic monitoring, which is crucial
for maintaining computer network services and security. Traditional methods like Deep …
for maintaining computer network services and security. Traditional methods like Deep …
MFWDD: Model-based Feature Weight Drift Detection Showcased on TLS and QUIC Traffic
Machine learning (ML) represents an efficient and popular approach for network traffic
classification. However, network traffic inspection is a challenging domain and trained …
classification. However, network traffic inspection is a challenging domain and trained …
Research on Lightweight Network Traffic Service Classification with Interference Traffic in Large-Scale Networks
B Zhang, W Jiang, Q Zhu, C Liao, W Wang - Available at SSRN 5127367 - papers.ssrn.com
This study puts forward a lightweight framework for traffic classification with interferenced
traffic (LF-ITC) to mitigate the high deployment costs of traffic classification facilities in large …
traffic (LF-ITC) to mitigate the high deployment costs of traffic classification facilities in large …