RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT

30 December 2022

Papers citing "RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT"

3 / 3 papers shown

Title
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation Chao Feng Alberto Huertas Celdrán Pedro Miguel Sánchez Sánchez Jan Kreischer Jan von der Assen Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller 27 1 0 11 Aug 2023
A Lightweight Moving Target Defense Framework for Multi-purpose Malware Affecting IoT Devices Jan von der Assen Alberto Huertas Celdrán Pedro Miguel Sánchez Sánchez Jordan Cedeno Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller 13 6 0 14 Oct 2022
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán T. Schenk A. Iten Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller AAML 12 18 0 31 Jan 2022