Detecting Software Keyloggers with Dendritic Cell Algorithm

Jun Fu, Yiwen Liang, Chengyu Tan, Xiaofei Xiong
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引用次数: 15

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.
树突状细胞算法检测软件键盘记录程序
软件键盘记录程序作为一种记录用户击键行为的隐形间谍软件,对用户的隐私和安全构成了极大的威胁。很难检测到键盘记录程序,因为它们以隐藏模式运行。本文采用免疫激发树突状细胞算法(DCA)检测受感染主机上是否存在键盘记录程序。通过键盘记录、文件访问和网络通信等不同行为之间的关联(包括定时关系),为检测提供了基础。实验结果表明,它是一种成功的检测键盘记录程序而不响应正常运行的程序的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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