Project detail

Improving Security of the Internet by Using System for Analyzing of Malicious Code Spreading

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 English
The 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.

Keywords
počítačová bezpečnost, škodlivý kód, malware, analýza dat, dolování z dat, vizualizace

Key words in English
computer security, malicious software, malware, data analysis, data mining, visualization

Mark

TA01010858

Default language

Czech

People responsible

Hruška Tomáš, prof. Ing., CSc. - fellow researcher
Krčma Pavel - principal person responsible
Obluk 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