DocumentCode :
2457011
Title :
Detecting Software Keyloggers with Dendritic Cell Algorithm
Author :
Fu, Jun ; Liang, Yiwen ; Tan, Chengyu ; Xiong, Xiaofei
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan, China
Volume :
1
fYear :
2010
fDate :
12-14 April 2010
Firstpage :
111
Lastpage :
115
Abstract :
As a kind of invisible spyware that records user´s keystrokes, software keyloggers have posed a great threat to user privacy and security. It is difficult to detect keyloggers because they run in a hidden mode. In this paper, an immune-inspired dendritic cell algorithm (DCA) was used to detect the existence of keyloggers on an infected host machine. The basis of the detection is facilitated through the correlation (including the timing relationships) between different behaviors such as keylogging, file access and network communication. The results of the experiments show that it is a successful technique for the detection of keyloggers without responding to normally running programs.
Keywords :
artificial immune systems; data privacy; invasive software; file access; immune inspired dendritic cell algorithm; invisible spyware; network communication; software keyloggers detection; user keystrokes; user privacy; user security; Communication system security; Computer security; Computerized monitoring; Data security; Face detection; Mobile communication; Mobile computing; Privacy; Software algorithms; Timing; API function call; Artificial Immune Systems (AISs); Dendritic Cell Algorithm (DCA); correlation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Mobile Computing (CMC), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-6327-5
Electronic_ISBN :
978-1-4244-6328-2
Type :
conf
DOI :
10.1109/CMC.2010.269
Filename :
5471503
Link To Document :
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