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- 1.0533909 - ÚI 2021 RIV DE eng C - Conference Paper (international conference)
Tumpach, Jiří - Holeňa, Martin
Online Malware Detection with Variational Autoencoders.
Proceedings of the 20th Conference Information Technologies - Applications and Theory. Aachen: Technical University & CreateSpace Independent Publishing, 2020 - (Holeňa, M.; Horváth, T.; Kelemenová, A.; Mráz, F.; Pardubská, D.; Plátek, M.; Sosík, P.), s. 122-129. CEUR Workshop Proceedings, 2718. ISSN 1613-0073.
[ITAT 2020: Information Technologies - Applications and Theory /20./. Oravská Lesná (SK), 18.09.2020-22.09.2020]
R&D Projects: GA ČR(CZ) GA18-18080S
Institutional support: RVO:67985807
Keywords : Neural networks * Deep learning * Variational autoencoder * Online learning * Malware detection
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-2718/paper19.pdf
Permanent Link: http://hdl.handle.net/11104/0312142File Download Size Commentary Version Access 0533909-aw.pdf 2 354.5 KB CC BY 4.0 Publisher’s postprint open-access - 2.0522793 - ÚI 2021 RIV CH eng B - Monography
Holeňa, Martin - Pulc, P. - Kopp, M.
Classification Methods for Internet Applications.
Springer: Cham, 2020. 281 s. Studies in Big Data, 69. ISBN 978-3-030-36961-3
Institutional support: RVO:67985807
Keywords : Spam filtering * Recommender systems * Malware detection * Network intrusion detection * Random forests * Classifier comprehensibility * Support vector machines * Nearest neighbours classification * Bayesian classifiers
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Permanent Link: http://hdl.handle.net/11104/0307224 - 3.0512092 - ÚI 2020 RIV DE eng C - Conference Paper (international conference)
Tumpach, J. - Krčál, M. - Holeňa, Martin
Deep networks in online malware detection.
ITAT 2019: Information Technologies – Applications and Theory. Aachen: Technical University & CreateSpace Independent Publishing, 2019 - (Barančíková, P.; Holeňa, M.; Horváth, T.; Pleva, M.; Rosa, R.), s. 90-98. CEUR Workshop Proceeding, 2473. ISSN 1613-0073.
[ITAT 2019: Conference Information Technologies - Applications and Theory /19./. Donovaly (SK), 20.09.2019-24.09.2019]
R&D Projects: GA ČR(CZ) GA18-18080S
Grant - others:GA MŠk(CZ) LM2015042
Institutional support: RVO:67985807
Keywords : artificial neural networks * multilayer perceptrons * deep networks * semi-supervised learning * malware detection
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-2473/paper7.pdf
Permanent Link: http://hdl.handle.net/11104/0302298File Download Size Commentary Version Access 0512092-aoa.pdf 3 581.3 KB OpenAccess Publisher’s postprint open-access - 4.0507120 - ÚTIA 2020 RIV US eng C - Conference Paper (international conference)
Pevný, T. - Somol, Petr
Discriminative models for multi-instance problems with tree-structure.
Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security (AISec'16). New York: ACM, 2016, s. 83-91. ISBN 978-1-4503-4573-6.
[the 2016 ACM Workshop on Artificial Intelligence and Security (AISec'16). Vienna (AT), 28.10.2016-28.10.2016]
Institutional support: RVO:67985556
Keywords : big data * learning indicators of compromise * malware detection * neural network * user modeling
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2019/RO/somol-0507120.pdf
Permanent Link: http://hdl.handle.net/11104/0298524 - 5.0507114 - ÚTIA 2020 RIV US eng C - Conference Paper (international conference)
Komárek, T. - Somol, Petr
End-node Fingerprinting for Malware Detection on HTTPS Data.
Proceedings of the 12th International Conference on Availability, Reliability and Security (ARES'17). New York: ACM, 2017, s. 1-7, č. článku 77. ISBN 978-1-4503-5257-4.
[the 12th International Conference on Availability, Reliability and Security (ARES'17). Reggio Calabria (IT), 29.08.2017-01.09.2017]
Institutional support: RVO:67985556
Keywords : HTTPS data * Malware detection * Supervised learning
OECD category: Robotics and automatic control
http://library.utia.cas.cz/separaty/2019/RO/somol-0507114.pdf
Permanent Link: http://hdl.handle.net/11104/0298533 - 6.0492065 - ÚI 2019 CA eng C - Conference Paper (international conference)
Krčál, Marek - Švec, O. - Jašek, O. - Bálek, M.
Deep Convolutional Malware Classifiers Can Learn from Raw Executables and Labels Only.
ICLR 2018 Workshop Track. Vancouver, 2018.
[ICLR 2018: International Conference on Learning Representations /6./. Vancouver (CA), 30.04.2018-03.05.2018]
Institutional support: RVO:67985807
Keywords : malware detection * convolutional networks * end-to-end learning
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://openreview.net/forum?id=HkHrmM1PM
Permanent Link: http://hdl.handle.net/11104/0285636File Download Size Commentary Version Access a0492065.pdf 8 220.1 KB OA Publisher’s postprint open-access - 7.0463379 - ÚTIA 2017 RIV US eng C - Conference Paper (international conference)
Somol, Petr - Pevný, T.
Discriminative Models for Multi-instance Problems with Tree Structure.
Proceedings of the 9th ACM Workshop on Artificial Intelligence and Security 2016. New York: ACM, 2016. ISBN 978-1-4503-4573-6.
[9th ACM Workshop on Artificial Intelligence and Security. Vienna (AT), 28.10.2016]
Institutional support: RVO:67985556
Keywords : Neural netwrok * User modeling * Malware detection * Big data * Learning indicators of compromise
Subject RIV: IN - Informatics, Computer Science
http://library.utia.cas.cz/separaty/2016/RO/somol-0463379.pdf
Permanent Link: http://hdl.handle.net/11104/0263127