A novel deep learning-based framework with particle swarm optimisation for intrusion detection in computer networks.

ABSTRACT: Intrusion detection plays a significant role in the provision of information security. The most critical element is the ability to precisely identify different types of intrusions into the network. However, the detection of intrusions poses a important challenge, as many new types of intrusion are now generated by cyber-attackers every day. A robust system is still elusive, despite the various strategies that have been proposed in recent years. Hence, a novel deep-learning-based architecture for detecting intrusions into a computer network is proposed in this paper. The aim is to construct a hybrid system that enhances the efficiency and accuracy of intrusion detection. The main contribution of our work is a novel deep learning-based hybrid architecture in which PSO is used for hyperparame

SUBMITTER: Yılmaz AA 

PROVIDER: S-EPMC11819531 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature