如何有效检测未知恶意代码?

Jaehee Lee, Hyoungjun Kim, H. Yoon, Kyungho Lee
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引用次数: 1

摘要

近年来,IT技术的飞速发展导致了各种平台的发展。随着新平台的发展,针对新平台的恶意代码层出不穷。这些新的恶意代码对国家基础设施构成了严重的、新的威胁,特别是严重的可能导致社会混乱。在韩国,韩国水电和核电遭到黑客攻击,蓝图被盗,随后被公布在网上。这造成了很大的问题,因为被黑客攻击的地方是关键的基础设施。因此,作为分析每天不受控制地产生的恶意代码的有效方法,寻找了相关疫苗。但是,与新创建的恶意代码相比,管理恶意代码的个人是有限的。如何有效检测未知的恶意代码?然而,要回答这个问题,就必须关注恶意代码的分析方法,尤其是关键的分析方法。为了有效地分析未知恶意代码,本文引入了未知恶意代码检测模型。然而,该模型有时将正常文件视为恶意代码。这最终降低了其发现和分析恶意代码的有效性。因此,为了提高模型的有效性,有必要降低误检率。因此,在本研究中,我们创造了特定的条件,可以显著降低未检出率。因此,本文提出了一种更有效地检测未知恶意代码的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to detect unknown malicious code efficiently?
Recently, rapid developments of IT technology lead to development of various platforms. With the development of the new platforms, diverse malicious codes are created to target the new platforms. These new malicious code means critical and new threat to national infrastructure, especially the important ones that can lead to social chaos. In Korea, Korea hydro and nuclear power was hacked and blueprint was stolen, which was later posted on-line. This created great problem as the place was hacked was critical infrastructure. Thus, the vaccine related are searched out as effective method to analyze the malicious codes that are created every day uncontrollably. However, Personals that manage malicious codes are limited compared to newly create malicious codes. How to detect unknown malicious code efficiently that remain to be unanswered? However, to answer this question, malicious code analysis method has to be concerned, especially the critical ones first. In order to analyze the Unknown malicious codes effectively, Unknown malicious code detection model was introduced in the previous paper. However, this model sometimes treated normal file as malicious code. This eventually decreased its effectiveness in finding and analyzing the malicious codes. . Thus it became necessary to decrease the misdetection rate in order to increase the effectiveness of the model. As a result in this research, we created specific conditions that lead to decrease the miss detection rate significantly. Hence in this paper, we presented a method that detects the Unknown malicious codes more efficiently.
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