期刊文献+

一种Android应用程序恶意行为的静态检测方法 被引量:10

Static Detection Method for Malicious Behavior in Android Apps
下载PDF
导出
摘要 目前Android应用程序的安全问题得到越来越多的关注.提出一种检测Android应用程序中恶意行为的静态分析方法,该方法采用静态数据流分析技术,并实现了常量分析算法,通过跟踪应用程序对常量值的使用来检测恶意订购、资费消耗等多种类型的恶意行为.实验结果表明,该方法可以有效检测出Android应用程序的恶意行为,具有较高的实用性. Currently, the issues on Android application's security have attracted more and more attentions. This paper presents a static analysis method to detect malicious behavior in Android applications. The method uses static data flow analysis technology, and implements a const analysis algorithm that tracing how the const value is used by the application to detect different kinds of malicious behavior, such as ordering services and consuming payments maliciously. The result of experiments shows that the method is practical, and can detect the malicious behavior in Android applications effectively.
出处 《计算机系统应用》 2013年第7期148-151,共4页 Computer Systems & Applications
基金 高等学校博士学科点专项科研基金新教师类资助课题(20113402120026) 安徽省自然科学基金(1208085QF112) 安徽省高等学校优秀青年人才基金(2012SQRL001ZD) 中央高校基本科研业务费专项资金(WK0110000007)
关键词 静态分析 恶意行为 常量分析 Android安全 数据流分析 static analysis malicious behavior const analysis Android security data flow analysis
  • 相关文献

参考文献7

  • 1移动终端白皮书(2012年1.http://www.cttl.cn/txyy/ggl/201204/P020120413505417116578.pdf.
  • 22012年第三季度全球手机安全报告.http://cn.nq.com/neirong/2012Q3.pdf.
  • 3Zhou Y J, Wang Z, Zhou W, Jiang XX. Hey, You, Get off of My Market: Detecting Malicious Apps in Official and Alternative Android Markets. Proc. of the 19th Network and Distributed System Security Symposium(NDSS 2012). San Diego, CA, February 2012.
  • 4Enck W, Gilbert P, Chun B, Cox LP, Jung J, McDaniel P, Sheth AN. Taint Droid: an information-flow tracking system for realtime privacy monitoring on smartphones Proc. of the 9th USENIX. Vancouver, BC, Canada. 2010: 1-6. Gilbert P, Chun B Cox LP, Jung J. Vision: Automated Security Validation of Mobile Apps at App Markets. Proc. of the International Workshop on Mobile Cloud Computing and Services. USA: ACM. 2011: 21-26.
  • 5Chess B, McGraw Ct Static analysis for security. IEEE Security and Privacy, 2004, 2(6): 76-79.
  • 6Cheng S, Yang J, Wang J, Wang J, Jiang E Loongchecker: Practical summary-based semi-simulation to detect vulnerability in binary code. Proc. 10th Int. Conf. on Trust Security and Privacy in Computing ana Communications. IEEE, 2011: 150-159.
  • 7Android SDK.http://developer.android.com/sdk/index.html.

同被引文献75

  • 1杨博,唐祝寿,朱浩谨,沈备军,林九川.基于静态数据流分析的Android应用权限检测方法[J].计算机科学,2012,39(S3):16-18. 被引量:8
  • 2杨欢,张玉清,胡予濮,刘奇旭.基于权限频繁模式挖掘算法的Android恶意应用检测方法[J].通信学报,2013,34(S1):106-115. 被引量:47
  • 3牛雪莲.基于Android的英语听力移动学习平台设计与实现[J].自动化与仪器仪表,2016(2):41-42. 被引量:22
  • 4张俊晖.Android即时通信系统的设计与实现[J].自动化与仪器仪表,2016(2):64-66. 被引量:9
  • 5网秦.2013年上半年网秦全球手机安全报告[R/OL].[2013-07-23].http://cn.nq.com/neirong/2013Q2.pdf.
  • 6JIANG X,ZHOU Y.A survey of Android malware[M].New York:Springer,2013:3-20.
  • 7SCHMIDT A D,BYE R,SCHMIDT H G,et al.Static analysis of executables for collaborative malware detection on Android[C]//Proceedings of the 2009 IEEE International Conference on Communications.Piscataway:IEEE Press,2009:631-635.
  • 8BURGUERA I,ZURUTUZA U,NADJM-TEHRANI S.Crowdroid:behavior-based malware detection system for Android[C]//Proceedings of the 1st ACM Workshop on Security and Privacy in Smartphones and Mobile Devices.New York:ACM,2011:15-26.
  • 9CHIANG H S,TSAUR W.Mobile malware behavioral analysis and preventive strategy using ontology[C]//Proceedings of the 2010IEEE Second International Conference on Social Computing.Piscataway:IEEE Press,2010:1080-1085.
  • 10SHABTAI A,ELOVICI Y.Applying behavioral detection on Android-based devices[C]//Proceedings of the Mobile Wireless Middleware,Operating Systems,and Applications.Berlin:Springer,2010,48:235-249.

引证文献10

二级引证文献60

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部