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

机译:基于多个API调用序列方程的恶意软件检测

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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:开发和传播恶意软件需要创建新的检测方法。因此,我们开始使用主动技术,这些主动技术使用测试程序来检测某些症状,这些症状通常出现在恶意软件中。对执行的研究程序进行动态分析。有一项有关程序如何与特定注册表项,文件,网络活动(使用某些API调用)进行读写的软件环境交互的研究。由于研究程序有潜在危害的事实,因此必须在孤立的环境中执行程序。本文讨论了基于API调用分析的主动方法,并提出了一种使用多序列比对识别恶意软件共同特征的新方法。本文考虑了基于API调用的恶意软件检测方案,每个API调用都在软件中实现。还提出了一种基于多序列API调用比对的全新恶意软件检测方案。详细描述了该方案,并以软件实现。对一套软件的测试以及病毒性质的合法性。测试表明,已建立的竞争方案可以准确显示和识别恶意软件。

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