Using Reinforcement Learning in order to detect anomalies and maybe a future response The dataset used is NSL-KDD with data of multiple anomalies
Using deep Q-Learning with keras/tensorflow to generate the network
Code associated with the paper: "Adversarial environment reinforcement learning algorithm for intrusion detection", G Caminero, M Lopez-Martin, B Carro, Computer Networks, 2019
Detects only the attack type between normal, DoS, Probe, R2L, U2R
Train set in: typeAD.py
Test set in: type_test.py
Train Dueling DDQN (tensorflow) in typeAD_tf.py
tensorboard --logdir=tmp