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Network Intrusion Detection Using SNMP MIB Data: A Multi-Device Machine Learning Approach

The increasing complexity and volume of network traffic have made the accurate and timely detection of cyber-attacks a critical challenge. This study proposes a machine learning-based intrusion detection approach using Simple Network Management Protocol - Management Information Base (SNMP-MIB) data collected from four...

Bearing Fault Diagnosis under Small-Sample Conditions Based on Unsupervised Representation Learning

Early detection of bearing faults in rotating machinery is essential for predictive maintenance. Although deep learning-based methods have achieved strong results in fault diagnosis, they usually require large amounts of labeled data. In industrial settings, however, faulty samples are limited, which restricts the appl...

Vibration-Based Fault Detection in Rotating Machinery: The Effect of Accelerometer Position and Ensemble Learning