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Towards a Robust and Scalable TCP Flavors Prediction Model from Passive Traffic.

, , , and . ICCCN, page 1-11. IEEE, (2018)

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Enhancing Security Attacks Analysis Using Regularized Machine Learning Techniques., , , and . AINA, page 909-918. IEEE Computer Society, (2017)Advanced Passive Operating System Fingerprinting Using Machine Learning and Deep Learning., , , , and . ICCCN, page 1-11. IEEE, (2020)A machine learning approach to TCP state monitoring from passive measurements., , , and . Wireless Days, page 164-171. IEEE, (2018)Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives., and . Sensors, 22 (24): 9916 (2022)COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics., , , and . SAM, page 216-220. IEEE, (2022)Dynamic Model Selection for Asynchronous Federated Learning in IoBT Scenarios., , and . IEEE Big Data, page 8025-8034. IEEE, (2024)Recurrent Neural Network-Based Prediction of TCP Transmission States from Passive Measurements., , , and . NCA, page 1-10. IEEE, (2018)NexTrend: Context-Aware Music-Relay Corridors Using NFC Tags., , , , , and . IMIS, page 573-578. IEEE Computer Society, (2013)Discovering the Dynamic Complexity of TCP Using Machine Learning and Deep Learning Techniques.. University of Oslo, Norway, (2020)base-search.net (ftoslouniv:oai:www.duo.uio.no:10852/74519).A Deep Learning Approach to Dynamic Passive RTT Prediction Model for TCP., , , and . IPCCC, page 1-10. IEEE, (2019)