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Maria Rigaki
Maria Rigaki
Verified email at aic.fel.cvut.cz - Homepage
Title
Cited by
Cited by
Year
Bringing a GAN to a Knife-fight: Adapting Malware Communication to Avoid Detection
M Rigaki, S Garcia
IEEE Security and Privacy Workshops (SPW), pp. 70-75, 2018
1022018
A survey of privacy attacks in machine learning
M Rigaki, S Garcia
arXiv preprint arXiv:2007.07646, 2020
872020
Adversarial Deep Learning Against Intrusion Detection Classifiers
M Rigaki
Luleå University of Technology, 2017
382017
DNS tunneling: A deep learning based lexicographical detection approach
F Palau, C Catania, J Guerra, S Garcia, M Rigaki
arXiv preprint arXiv:2006.06122, 2020
122020
Detecting DNS threats: A deep learning model to rule them all
F Palau, C Catania, J Guerra, SJ García, M Rigaki
XX Simposio Argentino de Inteligencia Artificial (ASAI 2019)-JAIIO 48 (Salta), 2019
32019
Machete: Dissecting the Operations of a Cyber Espionage Group in Latin America
V Valeros, M Rigaki, S Garcia
2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW …, 2019
12019
A study of machete cyber espionage operations in Latin America
V Valeros, M Rigaki, K Babayeva, S García
Virus Bulletin International Conference, 2019
12019
Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152-RTG
A Kott, R Thomas, M Drasar, M Kont, A Poylisher, B Blakely, P Theron, ...
https://arxiv.org/abs/1804.07646, 2018
12018
Stealing Malware Classifiers and AVs at Low False Positive Conditions
M Rigaki, S Garcia
arXiv preprint arXiv:2204.06241, 2022
2022
Adversarial Machine Learning
M Rigaki
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