A recombination generative adversarial network for intrusion detection - Luo, Haoqi; Wan, Liang (Zielona Góra: Uniwersytet Zielonogórski)
The imbalance and complexity of network traffic data are hot issues in the field of intrusion detection. To improve the detection rate of minority class attacks in network traffic, this paper presents a method for intrusion detection based on the recombination generative adversarial network (RGAN).
Keywords: intrusion detection; generative adversarial networks; class imbalance; RGAN