IDS-INT: Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

A network intrusion detection system is critical for cyber security against illegitimate attacks. In terms of feature perspectives, the network traffic may include a variety of elements such as attack reference, attack type, a sub-category of attack, host information, malicious scripts, etc. In terms of network perspectives, network traffic may contain an imbalanced number of harmful attacks when compared to normal traffic. It is challenging to identify a specific attack due to complex features and data imbalance issues. To address these issues, this paper proposed an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic (IDS-INT). IDS-INT uses transformer-based…