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Detection of malicious software on based on multiple equations of API-calls sequences

机译:基于API呼叫序列的多方程式检测恶意软件

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Development and dissemination of malicious software requires the creation of new methods for their detection. Therefore we began to use proactive technologies that use the test program to detect the presence of certain symptoms, often occurring in malware. Dynamic analysis of the studied program launched for execution. There is a study of how the program interacts with the software environment that is read/write at certain registry keys, files, network activity the use of certain API calls. Due to the fact that studied the program is potentially harmful, to make its execution must be in an isolated environment. This paper discusses proactive methods based on API call analysis and propose a new method using a multiple sequence alignment to identify common traits in malware. The paper considers the scheme to detect malicious software, based on API calls, each of which is implemented in software. Also presented a completely new malware detection scheme based on multiple sequence API calls alignment. This scheme is described in detail and implemented in software. A test on a set of software and the legitimacy of the viral nature. Testing has shown that the established scheme of competitive shows and identifies malicious software with high accuracy.
机译:恶意软件的开发和传播需要创建新方法的检测。因此,我们开始使用使用测试程序的主动技术来检测某些症状的存在,通常发生在恶意软件中。研究开发的研究动态分析。有研究程序如何与在某些注册表项,文件,网络活动的使用中读/写的软件环境进行互动,使用某些API调用。由于研究了该计划可能有害的事实,以使其执行必须处于孤立的环境中。本文讨论了基于API呼叫分析的主动方法,并使用多个序列对齐提出新方法,以识别恶意软件中的常见特征。本文考虑了基于API调用来检测恶意软件的方案,每个都在软件中实现。还基于多个序列API调用对齐呈现了一个全新的恶意软件检测方案。该方案详细描述并在软件中实现。关于一组软件的测试和病毒性质的合法性。测试表明,具有高精度的竞争力的竞争方案和识别恶意软件。

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