Abstract
In recent years, antimalware applications represented one of the most important research topics in the area of network security threat. In addition, malware have become a growing important problem for governments and commercial organizations. The key point of the research on the network security is to judge and validate the similarity metrics among the malicious software. Indeed, most computer network issues are also caused by malware. As a consequence, one enhanced system to analyze the behavior of malwares is needed to try to predict the malicious actions and to minimize the computer damages caused by the malware. However, the conventional data analysis tools lack the ability to deal with the computer safety because the environments malwares operating are with high levels of imprecision and vagueness. For this reason, we have developed Taiwan Malware Analysis Net (TWMAN) to improve the accuracy of malware behavioral analysis. This chapter tries to explorer and deal with these computer security and safety issues by integrating the semantic technologies and computational intelligence methods, such as the fuzzy ontologies and fuzzy markup language (FML). With the proposed approach, the malware identification has achieved a good performance according to the experimental results.
| Original language | English |
|---|---|
| Title of host publication | On the Power of Fuzzy Markup Language |
| Pages | 113-132 |
| Number of pages | 20 |
| Volume | 296 |
| DOIs | |
| Publication status | Published - 2013 |
Publication series
| Name | Studies in Fuzziness and Soft Computing |
|---|---|
| Volume | 296 |
| ISSN (Print) | 1434-9922 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Computer Science (miscellaneous)
- Computational Mathematics
Cite this
}
Fuzzy markup language for malware behavioral analysis. / Huang, Hsien De; Acampora, Giovanni; Loia, Vincenzo; Lee, Chang Shing; Hagras, Hani; Wang, Mei Hui; Kao, Hung-Yu; Chang, Jee Gong.
On the Power of Fuzzy Markup Language. Vol. 296 2013. p. 113-132 (Studies in Fuzziness and Soft Computing; Vol. 296).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - Fuzzy markup language for malware behavioral analysis
AU - Huang, Hsien De
AU - Acampora, Giovanni
AU - Loia, Vincenzo
AU - Lee, Chang Shing
AU - Hagras, Hani
AU - Wang, Mei Hui
AU - Kao, Hung-Yu
AU - Chang, Jee Gong
PY - 2013
Y1 - 2013
N2 - In recent years, antimalware applications represented one of the most important research topics in the area of network security threat. In addition, malware have become a growing important problem for governments and commercial organizations. The key point of the research on the network security is to judge and validate the similarity metrics among the malicious software. Indeed, most computer network issues are also caused by malware. As a consequence, one enhanced system to analyze the behavior of malwares is needed to try to predict the malicious actions and to minimize the computer damages caused by the malware. However, the conventional data analysis tools lack the ability to deal with the computer safety because the environments malwares operating are with high levels of imprecision and vagueness. For this reason, we have developed Taiwan Malware Analysis Net (TWMAN) to improve the accuracy of malware behavioral analysis. This chapter tries to explorer and deal with these computer security and safety issues by integrating the semantic technologies and computational intelligence methods, such as the fuzzy ontologies and fuzzy markup language (FML). With the proposed approach, the malware identification has achieved a good performance according to the experimental results.
AB - In recent years, antimalware applications represented one of the most important research topics in the area of network security threat. In addition, malware have become a growing important problem for governments and commercial organizations. The key point of the research on the network security is to judge and validate the similarity metrics among the malicious software. Indeed, most computer network issues are also caused by malware. As a consequence, one enhanced system to analyze the behavior of malwares is needed to try to predict the malicious actions and to minimize the computer damages caused by the malware. However, the conventional data analysis tools lack the ability to deal with the computer safety because the environments malwares operating are with high levels of imprecision and vagueness. For this reason, we have developed Taiwan Malware Analysis Net (TWMAN) to improve the accuracy of malware behavioral analysis. This chapter tries to explorer and deal with these computer security and safety issues by integrating the semantic technologies and computational intelligence methods, such as the fuzzy ontologies and fuzzy markup language (FML). With the proposed approach, the malware identification has achieved a good performance according to the experimental results.
UR - http://www.scopus.com/inward/record.url?scp=84886615634&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84886615634&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35488-5-7
DO - 10.1007/978-3-642-35488-5-7
M3 - Chapter
AN - SCOPUS:84886615634
SN - 9783642354878
VL - 296
T3 - Studies in Fuzziness and Soft Computing
SP - 113
EP - 132
BT - On the Power of Fuzzy Markup Language
ER -