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