Sanjeev Ghosh

A Comparative Evaluation of Deep Learning Architectures for Binary Network Intrusion Detection Using the NSL-KDD Dataset

Investigation of deep learning models for binary network intrusion detection using the NSL-KDD benchmark dataset indicates that carefully designed standalone architectures can match or exceed the performance of more complex hybrid and ensemble models for binary intrusion detection, while incurring substantially lower computational cost.