移动终端恶意软件流量行为自动化检测方法研究

Research on automatic detection method of mobile terminal malware traffic behavior

为解决传统移动设备恶意软件检测方法对入侵数据定位不准、分辨效果不佳的问题,提出了移动终端恶意软件流量行为自动化检测方法。首先结合特征采集原理提取常见的恶意软件行为特征因子,并根据特征因子定位恶意软件入侵范围,结合动态分析原理筛查定位区域恶意入侵行为影响度及潜在威胁,从而实现对移动终端恶意软件流量行为的准确检测。最后通过实验证实,移动终端恶意软件流量行为自动化检测方法定位精准性相对更高,且具有较高的数据分辨效果,充分满足研究要求。

In order to solve the problem that the mobile device malware detection method has poor immunity to intrusion data and poor resolution effect,an automatic detection method for mobile terminal malware traffic behavior is proposed.Firstly,common mobile terminal malware traffic behavior characteristics are extracted based on the principle of feature collection,malware intrusion impact factors are calculated according to the extracted feature data,and screening and positioning are carried out according to the calculation results.Thereby accurately detecting the malicious software flow behavior of the mobile terminal is realized.Finally,experiments prove that the mobile terminal malware traffic behavior automatic detection method has high immunity and intrusion data analysis effect,and it fully meets the research requirements.