基于耗电分析的Android平台恶意软件检测  

Android Malware Detection Based on Power Consumption Analysis

作　　者：杨宏宇[1] 唐瑞文[1] 

机构地区：[1]中国民航大学计算机科学与技术学院,天津东丽区300300

出　　处：《电子科技大学学报》2016年第6期981-985,共5页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(60776807,61179045);国家科技重大专项基金(2012ZX03002002);中国民航科技基金(MHRD201009,MHRD201205);中央高校基本科研业务费专项(3122014D033)

摘　　要：该文提出一种基于电量分析的恶意软件检测方法。首先获取移动终端的耗电状态并利用Mel频谱倒谱系数(MFCC)构建高斯混合模型(GMM)。然后采用GMM模型对电量消耗状态进行分析,进而通过对应用软件的分类处理识别恶意软件。实验证明应用软件的功能与电量消耗关系密切,表明基于软件的电量消耗信息分析可以较准确地检测出移动终端的恶意应用。This paper proposes a malicious software detection method based on power consumption. Firstly, the mobile terminal＇s power consumption status is obtained, and the Gaussian mixture model （GMM） is built by using Mel frequency cepstral coefficients （MFCC）. Then the GMM is used to analyze power consumption, and then identify malicious applications through the application software classification processing. Experiments show that an application software function and its power consumption have a close relationship, and some malicious applications in mobile terminals can be detected accurately through analyzing software power consumption information.

关 键 词：频谱倒谱系数 高斯混合模型 移动终端 电量消耗 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]