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Found 2 papers, 2 papers with code
EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion Detection
Fully Connected Neural Networks (FCNNs) have been the core of most state-of-the-art Machine Learning (ML) applications in recent years and also have been widely used for Intrusion Detection Systems (IDSs).
SparseIDS: Learning Packet Sampling with Reinforcement Learning
To minimize the computational expenses of the RL-based sampling we show that a shared neural network can be used for both the classifier and the RL logic.
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