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A Novel Immune Based Approach for Detection of Windows PE Virus

机译:一种基于免疫的Windows PE病毒检测新方法

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Generic computer virus detection is the absolute need of the hour as most commercial antivirus products fail to detect unknown and new Windows PE viruses. Motivated by the success of immune-based techniques in intrusion detection systems, recent research in detecting computer viruses is directed towards devising efficient non-signature-based techniques. We observe that each Windows PE virus whether or not it is encrypted must have a relocation module to relocate its variables or constants in the infected programs. Due to its unique characteristic, the virus relocation module can be extracted as an antibody in the immune systems to detect the specific antigens. In this paper, we presented a novel Windows PE virus detection approach that draws inspiration from artificial immune system and the structure of the relocation module of the virus. The structure of Windows PE virus is sufficiently analyzed. The dynamic evolution of self and nonself, the presentation of the antigen, and the generation of the antibody are proposed. The experiment is conducted and its results indicate that this approach not only has relatively higher detection rate of unknown Windows PE virus than the earlier known methods, but also has better capability of self-adaptive and self-learning.
机译:由于大多数商业防病毒产品无法检测到未知的和新的Windows PE病毒,因此常规的计算机病毒检测是小时的绝对需要。受入侵检测系统中基于免疫的技术成功的推动,检测计算机病毒的最新研究旨在开发有效的基于非签名的技术。我们注意到,每种Windows PE病毒(无论是否已加密)都必须具有一个重定位模块,才能在受感染的程序中重定位其变量或常量。由于其独特的特性,病毒重定位模块可以作为免疫系统中的抗体提取出来,以检测特定的抗原。在本文中,我们提出了一种新颖的Windows PE病毒检测方法,该方法从人工免疫系统和病毒重定位模块的结构中汲取了灵感。 Windows PE病毒的结构已得到充分分析。提出了自我和非自我的动态进化,抗原的呈递以及抗体的产生。进行了实验,结果表明该方法不仅比已知的方法具有更高的未知Windows PE病毒检测率,而且具有更好的自适应和自学习能力。

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