CNN-LSTM: Hybrid Deep Neural Network for Network Intrusion Detection System

Network security becomes indispensable to our daily interactions and networks. As attackers continue to develop new types of attacks and the size of networks continues to grow, the need for an effective intrusion detection system has become critical. Numerous studies implemented machine learning algorithms to develop an effective IDS; however, with the advent of deep learning algorithms and artificial neural networks that can generate features automatically without human intervention, researchers began to rely on deep learning. In our research, we took advantage of the Convolutional Neural Network’s ability to extract spatial features and the Long Short-Term Memory Network’s ability to extract temporal…

• UO
  University of New South Wales
• MO
  Ministry of Higher Education, Malaysia

  Award: FRGS/1/2019/TK10/UTM/02/16