Research Repository

TWMAN+: A Type-2 fuzzy ontology model for malware behavior analysis

Huang, Hsien-De and Lee, Chang-Shing and Hagras, Hani and Kao, Hung-Yu (2012) TWMAN+: A Type-2 fuzzy ontology model for malware behavior analysis. In: 2012 IEEE International Conference on Systems, Man and Cybernetics - SMC, 2012-10-14 - 2012-10-17.

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Classical ontology is not sufficient to deal with vague or imprecise knowledge for real world applications such as malware behavioral analysis. In addition, malware has grown into a pressing problem for governments and commercial organizations. Anti-malware applications represent one of the most important research topics in the area of information security threat. As a countermeasure, enhanced systems for analyzing the behavior of malware are needed in order to predict malicious actions and minimize computer damages. Many researchers use Virtual Machine (VM) systems to monitor malware behavior, but there are many Anti-VM techniques which are used to counteract the collection, analysis, and reverse engineering features of the VM based malware analysis platform. Therefore, malware researchers are likely to obtain inaccurate analysis from the VM based approach. For this reason, we have developed the Taiwan Malware Analysis Net (TWMAN) which uses a real operating system environment to improve the accuracy of malware behavior analysis and has integrated Type-1 Fuzzy Set (T1FS), Ontology, and Fuzzy Markup Language (FML) on 2010. In this paper, we use Interval Type-2 Fuzzy Set (IT2FS), eggdrop, and glftpd as a cloud service (software as a service) on the Google App Engine along with Python and Android. We believe this system can help improve the correctness of malware analysis results and reduce the rate of malware misdiagnosis. © 2012 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Uncontrolled Keywords: malware behavioral analysis; ontology; fuzzy ontology; interval type-2 fuzzy set
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 25 Mar 2014 16:48
Last Modified: 15 Jan 2022 00:38

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