Applying FML and Fuzzy Ontologies to malware behavioural analysis

Hsien De Huang, Giovanni Acampora, Vincenzo Loia, Chang Shing Lee, Hung-Yu Kao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Antimalware applications represent one of the most important research topic in the area of information security threat. Indeed, most computer network issues have malwares as their underlying cause. As a consequence, enhanced systems for analyzing the behavior of malwares are needed in order to try to predict their malicious actions and minimize eventual computer damages. However, because the environments where malwares operate are characterized by high levels of imprecision and vagueness, the conventional data analysis tools lack to deal with these computer safety applications. This work tries to bridge this gap by integrating semantic technologies and computational intelligence methods, such as the Fuzzy Ontologies and Fuzzy Markup Language (FML), in order to propose an advanced semantic decision making system that, as shown by experimental results, achieves good performances in terms of malicious programs identification.

Original languageEnglish
Title of host publicationFUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Pages2018-2025
Number of pages8
DOIs
Publication statusPublished - 2011
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
Duration: 2011 Jun 272011 Jun 30

Other

Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
CountryTaiwan
CityTaipei
Period11-06-2711-06-30

Fingerprint

Markup languages
Malware
Ontology
Semantics
Vagueness
Computational Intelligence
Information Security
Imprecision
Computer Networks
Security of data
Computer networks
Artificial intelligence
Data analysis
Damage
Safety
Decision making
Decision Making
Minimise
Predict
Experimental Results

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Software
  • Artificial Intelligence
  • Applied Mathematics

Cite this

Huang, H. D., Acampora, G., Loia, V., Lee, C. S., & Kao, H-Y. (2011). Applying FML and Fuzzy Ontologies to malware behavioural analysis. In FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 2018-2025). [6007716] https://doi.org/10.1109/FUZZY.2011.6007716
Huang, Hsien De ; Acampora, Giovanni ; Loia, Vincenzo ; Lee, Chang Shing ; Kao, Hung-Yu. / Applying FML and Fuzzy Ontologies to malware behavioural analysis. FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. 2011. pp. 2018-2025
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Huang, HD, Acampora, G, Loia, V, Lee, CS & Kao, H-Y 2011, Applying FML and Fuzzy Ontologies to malware behavioural analysis. in FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings., 6007716, pp. 2018-2025, 2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011, Taipei, Taiwan, 11-06-27. https://doi.org/10.1109/FUZZY.2011.6007716

Applying FML and Fuzzy Ontologies to malware behavioural analysis. / Huang, Hsien De; Acampora, Giovanni; Loia, Vincenzo; Lee, Chang Shing; Kao, Hung-Yu.

FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. 2011. p. 2018-2025 6007716.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Huang HD, Acampora G, Loia V, Lee CS, Kao H-Y. Applying FML and Fuzzy Ontologies to malware behavioural analysis. In FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings. 2011. p. 2018-2025. 6007716 https://doi.org/10.1109/FUZZY.2011.6007716