Abstract: Given the distributed nature of the massively connected “Things” in IoT, IoT networks have been a primary target for cyberattacks. Although machine learning based network intrusion detection ...

enhancing network intrusion detection, challenges remain in sample collection, traffic feature expression, and gateway resource constraints. To address these, we propose FIR-GNN. It constructs a FIRG ...

This paper proposes a new approach to intrusion detection modeling based on CNN and transfer learning to reduce updating overhead. Its implementation is twofold. First, CNN is implemented using ...

This repository extends the work presented in the original IEEE ICC 2022 paper: "A Transfer Learning and Optimized CNN Based Intrusion Detection ... and inter-vehicle network intrusion detection, ...

They aimed to address the unique challenges posed by virtualized environments and proposed a convolutional neural network ...

I am excited to share that our paper "Analysis of lightweight CNN-Based Intrusion Detection Models in IoT" was published in IEEE in the 2024 IEEE/ACM International Conference on Big Data Computing ...