摘要
迅速发展的智能手机及移动通信技术在给人们带来极大便利和体验提升的同时,也带来了新的安全问题。总结了智能手机恶意软件的突出特点及危害和当前反恶意软件的发展状况,并结合设备及网络特点,提出了一种基于统计拟合方法的智能手机异常流量与恶意软件检测方法。该方法实时监控设备流量消耗情况,并以正常流量消耗的统计拟合曲线作为标准进行比对。仿真结果表明:该方法可以有效检测出异常流量。
The rapid development of Smart Phone and Mobile Communication Technology not only brings terrific convenience and extraordinary user experience,but also creates new secure issues.This paper summarizes the Smart Phone viruses’characteristic and harm and proposes a Smart Phone anomaly data flow and application detection method based on statistical fit,which collects the dataflow and compare them to the fitting curve in real time.The simulation results show that the method proposed in paper can detect the anomaly data flow effectively.
出处
《计算机安全》
2012年第9期11-14,18,共5页
Network & Computer Security
关键词
异常流量检测
统计拟合
韦布尔分布
智能手机
恶意软件检测
anomaly data flow monitoring
Weibull distribution
statistical fit
Smart Phone
malware detection
