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Project detail
Duration: 01.01.2011 — 31.12.2013
Funding resources
Technologická agentura ČR - Program aplikovaného výzkumu a experimentálního vývoje ALFA
- whole funder (2011-01-01 - 2013-12-31)
On the project
Projekt je zaměřen na získání nových poznatků o šíření malware z dat, které pomocí antivirového software anonymně sbírá firma AVG Technologies CZ, s.r.o. Díky těmto poznatkům pak bude možné efektivněji se bránit proti škodlivému kódu a snížit míru škod, které působí.
Description in EnglishThe project is focused on discovering of new information about malware spreading from data anonymously collected by antivirus software from AVG Technologies CZ. Thanks to this new knowledge it will be possible to fight against malware more effectively and decrease damages caused by its activities.
Keywordspočítačová bezpečnost, škodlivý kód, malware, analýza dat, dolování z dat, vizualizace
Key words in Englishcomputer security, malicious software, malware, data analysis, data mining, visualization
Mark
TA01010858
Default language
Czech
People responsible
Hruška Tomáš, prof. Ing., CSc. - fellow researcherKrčma Pavel - principal person responsibleObluk Karel, Ing., Ph.D. - principal person responsible
Units
Department of Information Systems- co-beneficiary (2011-01-01 - 2013-12-31)
Results
ŠEBEK, M.; HLOSTA, M.; KUPČÍK, J.; ZENDULKA, J.; HRUŠKA, T. Multi-level Sequence Mining Based on GSP. Proceedings of the Eleventh International Conference on Informatics INFORMATICS'2011. 1. Košice: Faculty of Electrical Engineering and Informatics, University of Technology Košice, 2011. p. 185-190. ISBN: 978-80-89284-94-8.Detail
ŠEBEK, M.; HLOSTA, M.; KUPČÍK, J.; ZENDULKA, J.; HRUŠKA, T. Multi-level Sequence Mining Based on GSP. Acta Electrotechnica et Informatica, 2012, vol. 2012, no. 2, p. 31-38. ISSN: 1335-8243.Detail
KUPČÍK, J.; HRUŠKA, T. Towards Online Data Mining System for Enterprises. Proceedings of the 7th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2012). Wrocław: SciTePress - Science and Technology Publications, 2012. p. 187-192. ISBN: 978-989-8565-13-6.Detail
HLOSTA, M.; STRÍŽ, R.; KUPČÍK, J.; ZENDULKA, J.; HRUŠKA, T. Constrained Classification of Large Imbalanced Data by Logistic Regression and Genetic Algorithm. International Journal of Machine Learning and Computing, 2013, vol. 2013, no. 3, p. 214-218. ISSN: 2010-3700.Detail
ŠEBEK, M.; HLOSTA, M.; ZENDULKA, J.; HRUŠKA, T. MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns. 9th International Conference, ADMA 2013. Lecture Notes in Computer Science. Hangzhou: Springer Verlag, 2013. p. 157-168. ISBN: 978-3-642-53913-8.Detail
ŠEBEK, M.; ZENDULKA, J. Generator of Synthetic Datasets for Hierarchical Sequential Pattern Mining Evaluation. Proceedings of the Twelfth International Conference on Informatics 2013. Košice: The University of Technology Košice, 2013. p. 289-292. ISBN: 978-80-8143-127-2.Detail
HLOSTA, M.; STRÍŽ, R.; ZENDULKA, J.; HRUŠKA, T. PSO-based Constrained Imbalanced Data Classification. Proceedings of the Twelth International Conference on Informatics INFORMATICS'2013. Spišská Nová Ves: The University of Technology Košice, 2013. p. 234-239. ISBN: 978-80-8143-127-2.Detail
HLOSTA, M.; ŠEBEK, M.; ZENDULKA, J. Approach to Visualisation of Evolving Association Rule Models. Proceedings of The Second International Conference on Informatics & Applications (ICIA 2013). Łódź: The Society of Digital Information and Wireless Communications, 2013. p. 47-52. ISBN: 978-1-4673-5255-0.Detail
HLOSTA, M.; KUPČÍK, J.; ŠEBEK, M.; PEŠEK, M.; STRÍŽ, R.; HRUŠKA, T.; ZENDULKA, J.; HALFAR, P.; MASAŘÍK, K.; KRČMA, P.: AVGMAS; Malware Analysis System. Domovská stránka nástroje Malware Analysis System se nachází na adrese http://www.fit.vutbr.cz/research/grants/AVGMAS/.. URL: https://www.fit.vut.cz/research/product/352/. (software)Detail