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Found 3 papers, 2 papers with code
Leveraging Siamese Networks for One-Shot Intrusion Detection Model
Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to re-train the model for every unseen cyber-attack class.
Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning
Like other Internet of Things (IoT) implementations, SCADA systems are vulnerable to cyber-attacks, therefore, a robust anomaly detection is a major requirement.
A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection Systems
This manuscript aims to pinpoint research gaps and shortcomings of current datasets, their impact on building Network Intrusion Detection Systems (NIDS) and the growing number of sophisticated threats.
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