DocumentCode :
2254300
Title :
Automatically identifying technology in malware based on mass samples
Author :
Chen, Jian-min ; Feng, Yu-meng ; Mei, Yin-ming
Author_Institution :
Coll. of Comput. Sci., Beijing Univ. of Technol., Beijing, China
Volume :
3
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
1090
Lastpage :
1094
Abstract :
With the rapid development of Internet application, malware detection becomes more and more important and tremendous. There are tens of thousands of new malware samples especially associated with economic interests. Manual inspection is difficult to identify the samples with high-speed response. We designed and implemented an automatically identifying system based on the mass samples. It has high accuracy and good speed improving the efficiency of detecting malware.
Keywords :
Internet; identification technology; invasive software; Internet application; automatically identifying system; automatically identifying technology; malware detection; manual inspection; mass sample; Artificial neural networks; Computers; Malware; Servers; automatically identifying technology; malware; mass samples;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
Type :
conf
DOI :
10.1109/ICMLC.2010.5580940
Filename :
5580940
Link To Document :
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