DocumentCode :
2992924
Title :
Behavior-Based Malware Analysis and Detection
Author :
Liu Wu ; Ren Ping ; Liu Ke ; Duan Hai-xin
Author_Institution :
Network Res. Center, Tsinghua Univ., Beijing, China
fYear :
2011
fDate :
24-28 Sept. 2011
Firstpage :
39
Lastpage :
42
Abstract :
Malware, such as Trojan Horse, Worms and Spy ware severely threatens Internet. We observed that although malware and its variants may vary a lot from content signatures, they share some behavior features at a higher level which are more precise in revealing the real intent of malware. This paper investigates the technique of malware behavior extraction, presents the formal Malware Behavior Feature (MBF) extraction method, and proposes the malicious behavior feature based malware detection algorithm. Finally we designed and implemented the MBF based malware detection system, and the experimental results show that it can detect newly appeared unknown malwares.
Keywords :
invasive software; MBF; Malware behavior feature; Trojan Horse; behavior based Malware detection; behavior based malware analysis; malware behavior extraction; Data mining; Detection algorithms; Educational institutions; Feature extraction; Internet; Malware; Malicious Behavior; Malware Analysis; Malware Detection; Network Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complexity and Data Mining (IWCDM), 2011 First International Workshop on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4577-2007-9
Type :
conf
DOI :
10.1109/IWCDM.2011.17
Filename :
6128413
Link To Document :
بازگشت