IoT Security Comparison Hub
5 papers - avg viability 4.4
Top Papers
- An Efficient Unsupervised Federated Learning Approach for Anomaly Detection in Heterogeneous IoT Networks(6.0)
Anomaly detection in IoT networks using an efficient unsupervised federated learning framework with explainable AI.
- Explainability-Aware Evaluation of Transfer Learning Models for IoT DDoS Detection Under Resource Constraints(5.0)
Develop an explainability-focused IoT DDoS detection tool leveraging transfer learning models for improved reliability and resource efficiency.
- Incremental Federated Learning for Intrusion Detection in IoT Networks under Evolving Threat Landscape(5.0)
A federated learning approach to enhance intrusion detection systems in resource-constrained IoT networks.
- Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection(3.0)
Evaluating cross-domain feature transferability for improved IoT intrusion detection robustness.
- External entropy supply for IoT devices employing a RISC-V Trusted Execution Environment(3.0)
A solution for secure cryptographic key generation in IoT devices using RISC-V Trusted Execution Environment.