Deep reinforcement learning-based intrusion detection scheme for software-defined networking
The proposed methodology for the IDS uses Deep Reinforcement Learning to increase the accuracy of intrusion detection as well as...
intrusion
Hybrid Intrusion Detection System Optimizes Resource-Constrained Networks With Genetic Algorithms And Self-Supervised Learning
The proliferation of interconnected devices in the Internet of Things and wireless sensor networks creates ever-expanding opportunities for cyberattacks, yet...
Network-based intrusion detection using deep learning technique
The dataset considered for the current research is UNSW-NB155, which has 175,341 records and is also imbalanced with a higher...
Signature-based intrusion detection using machine learning and deep learning approaches empowered with fuzzy clustering
In intrusion detection, machine learning methods have proven to be rather requisite in the mainstays of all approaches. Some of...
Hybrid bagging and boosting with SHAP based feature selection for enhanced predictive modeling in intrusion detection systems
The result section demonstrates the proposed model’s efficacy in predicting reasonably accurate outcomes across various test scenarios. Key performance metrics,...
