DCNNBiLSTM: An Efficient Hybrid Deep Learning-Based Intrusion Detection System

In recent years, all real-world processes have been shifted to the cyber environment practically, and computers communicate with one another over the Internet. As a result, there is a rising number of network security vulnerabilities, and network administrators are unable to secure their networks from all forms of cyberattacks. Many techniques for network intrusion detection have also been developed. However, they encounter significant challenges as a result of the ongoing emergence of new vulnerabilities that present systems cannot comprehend. We are motivated by deep learnings exceptional performance in various detection and identification tasks, we present an intelligent and efficient network intrusion…