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A Graph Construction Method for Anomalous Traffic Detection with Graph Neural Networks Using Sets of Flow Data.

, , , and . COMPSAC, page 1017-1018. IEEE, (2023)

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Dynamic Inference From IoT Traffic Flows Under Concept Drifts in Residential ISP Networks., , , , , and . IEEE Internet Things J., 10 (17): 15761-15773 (September 2023)Anomaly Traffic Detection with Federated Learning toward Network-based Malware Detection in IoT., , , , , , and . GLOBECOM, page 299-304. IEEE, (2022)Combining Stochastic and Deterministic Modeling of IPFIX Records to Infer Connected IoT Devices in Residential ISP Networks., , , , and . IEEE Internet Things J., 10 (6, March 15): 5128-5145 (2023)Malware detection for IoT devices using hybrid system of whitelist and machine learning based on lightweight flow data., , , , and . Enterp. Inf. Syst., (September 2023)A Liveness Detection Method for Palmprint Authentication., , , , , , and . IHSI, volume 1131 of Advances in Intelligent Systems and Computing, page 385-391. Springer, (2020)Self-adaptive Traffic Anomaly Detection System for IoT Smart Home Environments., , , , , , and . CoRR, (2024)Malware Detection for IoT Devices using Automatically Generated White List and Isolation Forest., , , and . IoTBDS, page 38-47. SCITEPRESS, (2021)Inferring Connected IoT Devices from IPFIX Records in Residential ISP Networks., , , , and . LCN, page 57-64. IEEE, (2021)A Graph Construction Method for Anomalous Traffic Detection with Graph Neural Networks Using Sets of Flow Data., , , and . COMPSAC, page 1017-1018. IEEE, (2023)Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks., , , , , and . CoRR, (2023)