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Explainable artificial intelligence for cybersecurity: a literature survey.

, , , , , , , , and . Ann. des Télécommunications, 77 (11-12): 789-812 (2022)

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BAGUETTE: Hunting for Evidence of Malicious Behavior in Dynamic Analysis Reports., , , and . SECRYPT, page 417-424. SCITEPRESS, (2023)Apprentissage de préférences en espace combinatoire et application à la recommandation en configuration interactive. (Preferences learning in combinatorial spaces and application to recommandation in interactive configuration).. Paul Sabatier University, Toulouse, France, (2018)RIDS: Radio Intrusion Detection and Diagnosis System for Wireless Communications in Smart Environment., , , , , and . ACM Trans. Cyber Phys. Syst., 5 (3): 24:1 (2021)Hardware-Performance-Counters-based anomaly detection in massively deployed smart industrial devices., , , , , , and . NCA, page 1-8. IEEE, (2020)Learning Lexicographic Preference Trees From Positive Examples., , and . AAAI, page 2959-2966. AAAI Press, (2018)On-board Diagnosis: A First Step from Detection to Prevention of Intrusions on Avionics Applications., , , , , and . ISSRE, page 358-368. IEEE, (2020)Errors in the CICIDS2017 Dataset and the Significant Differences in Detection Performances It Makes., , , , , and . CRiSIS, volume 13857 of Lecture Notes in Computer Science, page 18-33. Springer, (2022)Conditionally Acyclic CO-Networks for Efficient Preferential Optimization., and . ECAI, volume 372 of Frontiers in Artificial Intelligence and Applications, page 843-850. IOS Press, (2023)Towards Understanding Alerts raised by Unsupervised Network Intrusion Detection Systems., , , , , and . RAID, page 135-150. ACM, (2023)The complexity of unsupervised learning of lexicographic preferences., , , and . CoRR, (2022)