计算机科学 ›› 2012, Vol. 39 ›› Issue (Z6): 12-14.

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基于沙盒技术的恶意程序检测模型

陈丹伟,唐平,周书桃   

  1. (南京邮电大学计算机学院 南京210003)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Malware Detection Model Based on the Sandbox

  • Online:2018-11-16 Published:2018-11-16

摘要: 计算机恶意程序引发的犯罪活动越来越多,因此,恶意程序的有效检测成为了人们研究和关注的焦点。基于 沙盒技术的恶意程序动态分析检测方法成为了目前研究的热点。利用改进的QEMU进程虚拟机,以获取更高的仿真 响应时间和完整的API序列流为目的,基于改进的攻击树提出了一个行为分析算法,并用实例加以说明。实验结果 证明提出的检测方法是可行的、有效的。

关键词: 沙盒,恶意程序检测,动态分析

Abstract: The increasing of computer malware criminal leads researchers to pay attention on the effective detection of malware. The dynamic analysis detection method based on sandbox technology becomes the research spot. This paper proposed a behavior analysis algorithm based on improved attack tree which uses the improved QEML1 process virtual machine to obtain a shorter response time and a complete API sequences flow. And the experiment results demonstrate effective and feasible of this detection method.

Key words: Sandbox, Malware detection, Dynamic analysis

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