[1] |
Gartner. Market share:final PCs,ultramobiles and mobile phones,all countries,4Q17[R]. Connecticut:Gartner, 2018.
|
[2] |
GIBLER C , CRUSSELL J , ERICKSON J ,et al. AndroidLeaks:automatically detecting potential privacy leaks in android applications on a large scale[J]. Trust, 2012,12: 291-307.
|
[3] |
YANG Z , YANG M . Leakminer:detect information leakage on android with static taint analysis[C]// 2012 Third World Congress on Software Engineering (WCSE). 2012: 101-104.
|
[4] |
ARZT S , RASTHOFER S , FRITZ C ,et al. Flowdroid:precise context,flow,field,object-sensitive and lifecycle-aware taint analysis for android apps[J]. ACM Sigplan Notices, 2014,49(6): 259-269.
|
[5] |
ENCK W , GILBERT P , CHUN B G ,et al. Taintdroid:an information-flow tracking system for realtime privacy monitoring on smartphones[C]// The 9th USENIX Conference on Operating Systems Design and Implementation. USENIX Association, 2010.
|
[6] |
HORNYACK P , HAN S , JUNG J ,et al. These aren't the droids you're looking for:Retrofitting Android to protect data from imperious applications[C]// The 18th ACM Conference on Computer and Communications Security. ACM, 2011: 639-652.
|
[7] |
Droidbox[EB/OL]. .
|
[8] |
RASTOGI V , QU Z , MCCLURG J ,et al. Uranine:real-time privacy leakage monitoring without system modification for Android[J]. Security and Privacy in Communication Networks, 2015: 256-276.
|
[9] |
YOU W , LIANG B , SHI W ,et al. TaintMan:an ART-compatible dynamic taint analysis framework on unmodified and non-rooted Android devices[J]. IEEE Transactions on Dependable and Secure Computing, 2017.
|
[10] |
YANG Z , YANG M , ZHANG Y ,et al. Appintent:Analyzing sensitive data transmission in Android for privacy leakage detection[C]// 2013 ACM SIGSAC Conference on Computer & Communications Security. ACM, 2013: 1043-1054.
|
[11] |
XIA M , GONG L , LYU Y ,et al. Effective real-time android application auditing[C]// 2015 IEEE Symposium on Security and Privacy (SP). 2015: 899-914.
|
[12] |
孙博文, 黄炎裔, 温俏琨 ,等. 基于静态多特征融合的恶意软件分类方法[J]. 网络与信息安全学报, 2017,3(11): 68-76.
|
|
SUN B W , HUANG Y Y , WEN Q K ,et al. Malware classification method based on static multiple-feature fusion[J]. Chinese Journal of Network and Information Security, 2017,3(11): 68-76.
|
[13] |
杨欢, 张玉清, 胡予濮 ,等. 基于多类特征的 Android 应用恶意行为检测系统[J]. 计算机学报, 2014,37(1): 15-27.
|
|
YANG H , ZHANG Y Q , HU Y P ,et al. A malware behavior detection system of Android applications based on multi-class features[J]. Chinese Journal of Computers, 2014,37(1): 15-27.
|
[14] |
TALHA K A , ALPER D I , AYDIN C . APK auditor:permission-based Android malware detection system[J]. Digital Investigation, 2015,13: 1-14.
|
[15] |
BHANDARI S , LAXMI V , ZEMMARI A ,et al. Intersection automata based model for android application collusion[C]// 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA). 2016: 901-908.
|
[16] |
BUGIEL S , DAVI L , DMITRIENKO A ,et al. Xmandroid:a new android evolution to mitigate privilege escalation attacks[R]. Technical Report, 2011.
|
[17] |
BUGIEL S , DAVI L , DMITRIENKO A ,et al. Towards taming privilege-escalation attacks on Android[C]// NDSS. 2012:19.
|
[18] |
BLASCO J , CHEN T M . Automated generation of colluding Apps for experimental research[J]. Journal of Computer Virology and Hacking Techniques, 2017: 1-12.
|