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A Method of Mutating Windows Malwares using Reinforcement Learning with Functionality Preservation., , , , , и . SoICT, стр. 142-149. ACM, (2022)A federated threat hunting system with big data analysis for SDN-enabled networks., , , , и . RIVF, стр. 35-40. IEEE, (2022)Strengthening IDS against Evasion Attacks with GAN-based Adversarial Samples in SDN-enabled network., , , , и . RIVF, стр. 1-6. IEEE, (2021)A Secure and Privacy Preserving Federated Learning Approach for IoT Intrusion Detection System., , , и . NSS, том 13041 из Lecture Notes in Computer Science, стр. 353-368. Springer, (2021)Federated Learning-Based Intrusion Detection in the Context of IIoT Networks: Poisoning Attack and Defense., , , и . NSS, том 13041 из Lecture Notes in Computer Science, стр. 131-147. Springer, (2021)A Deep Transfer Learning Approach for Flow-Based Intrusion Detection in SDN-Enabled Network., , , , , , и . SoMeT, том 337 из Frontiers in Artificial Intelligence and Applications, стр. 327-339. IOS Press, (2021)MalDEX: An Explainable Malware Detection System Based on Ensemble Learning., , , и . MAPR, стр. 1-6. IEEE, (2023)On the effectiveness of transferability of adversarial Android malware samples against learning-based detectors., , , , , и . MAPR, стр. 1-6. IEEE, (2023)XFedGraph-Hunter: An Interpretable Federated Learning Framework for Hunting Advanced Persistent Threat in Provenance Graph., , , и . ISPEC, том 14341 из Lecture Notes in Computer Science, стр. 546-561. Springer, (2023)Federated Learning-Based Cyber Threat Hunting for APT Attack Detection in SDN-Enabled Networks., , , и . ISCIT, стр. 1-6. IEEE, (2022)