基于API参数语义分析的安卓应用行为细粒度表征方法  

FINE-GRAINED BEHAVIOR REPRESENTATION FOR ANDROID APPLICATIONSBASED ON API PARAMETER SEMANTIC ANALYSIS

作　　者：贺瑞 张晓寒 张源 He Rui;Zhang Xiaohan;Zhang Yuan(School of Computer Science,Fudan University,Shanghai 200438,China)

机构地区：[1]复旦大学计算机科学技术学院,上海200438

出　　处：《计算机应用与软件》2024年第7期6-12,48,共8页Computer Applications and Software

基　　金：国家自然科学基金项目(61972099,U1836210,U1836213,U1736208);上海市自然科学基金项目(19ZR1404800)。

摘　　要：基于API(Application Programming Interface)的行为表征是主流安卓恶意应用检测和分类方法的重要环节。然而,安卓API的笼统化发展导致该表征方法面临粗粒度、无法精确表征应用行为的问题。针对该问题,基于程序分析和自然语言处理技术,提出自动化的方法对API参数进行语义分析,将表征粒度从API提升至其参数,实现对应用行为的细粒度表征。实验结果表明该方法可显著提高安卓应用行为表征的精确性,提升恶意应用检测和分类等任务的效果。API-based behavior representation is currently an important part of mainstream Android malware detection and classification.However,due to the rough development of Android APIs,this method faces the problem of coarse granularity and is unable to precisely describe application behaviors.In response to this problem,an automatic API parameter semantic analysis method is proposed,which is based on program analysis and natural language processing technology.It refined the representation granularity from API to its parameters and realized a fine-grained representation of application behaviors.Experimental results show that this method can significantly improve the precision of Android application behavior representation,and enhance the effectiveness of tasks such as malware detection and classification.

关 键 词：行为细粒度表征 恶意软件检测 参数语义分析 自然语言处理 

分 类 号：TP310[自动化与计算机技术—计算机软件与理论]