no code implementations • 12 Dec 2023 • Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina Adam, Nathaniel D. Bastian, Tian Lan
Many cybersecurity problems that require real-time decision-making based on temporal observations can be abstracted as a sequence modeling problem, e. g., network intrusion detection from a sequence of arriving packets.
no code implementations • 27 Nov 2023 • Jingdi Chen, Lei Zhang, Joseph Riem, Gina Adam, Nathaniel D. Bastian, Tian Lan
Deep Learning (DL) based methods have shown great promise in network intrusion detection by identifying malicious network traffic behavior patterns with high accuracy, but their applications to real-time, packet-level detections in high-speed communication networks are challenging due to the high computation time and resource requirements of Deep Neural Networks (DNNs), as well as lack of explainability.