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An Advanced Computing Approach for IoT-Botnet Detection in Industrial Internet of Things.

, , , and . IEEE Trans. Ind. Informatics, 18 (11): 8298-8306 (2022)

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The average cut-rank of graphs., and . Eur. J. Comb., (2020)A novel graph-based approach for IoT botnet detection., , and . Int. J. Inf. Sec., 19 (5): 567-577 (2020)Towards an efficient approach using graph-based evolutionary algorithm for IoT botnet detection., and . Informatica (Slovenia), (2023)A survey of IoT malware and detection methods based on static features., , , and . ICT Express, 6 (4): 280-286 (2020)Towards effectively feature graph-based IoT botnet detection via reinforcement learning., , and . J. Intell. Fuzzy Syst., 41 (6): 6801-6814 (2021)Towards a rooted subgraph classifier for IoT botnet detection., , , , and . ICCCM, page 247-251. ACM, (2019)A Graph-Based Approach for IoT Botnet Detection Using Reinforcement Learning., , , , , , and . ICCCI, volume 12496 of Lecture Notes in Computer Science, page 465-478. Springer, (2020)An Advanced Computing Approach for IoT-Botnet Detection in Industrial Internet of Things., , , and . IEEE Trans. Ind. Informatics, 18 (11): 8298-8306 (2022)PSI-rooted subgraph: A novel feature for IoT botnet detection using classifier algorithms., , , and . ICT Express, 6 (2): 128-138 (2020)Anomaly Detection in Internet of Things Based on Logs Using Machine Learning and Deep Learning Techniques., and . CNIOT, page 969-974. ACM, (2023)