The electronic devices such as a mobile have become popular day by day, which is the major target of malicious applications(malapps). The detection and removal of malicious apps from android is the major issue in now days. So keep the malapps out of the app markets is an ongoing challenge. One major design points of Android security mechanism is control the permission that restricts the access of users having responsibility to the app developers with regard to accurately specifying the requested permissions and to the users with regarding to fully understanding the risk of granting certain combinations of permission. In this report, we have studied different techniques to determine themalapps in android. In permission induced risk first, analyse the risk of an individual permission and the risk of a group of corresponding permissions. Then used different feature ranking methods. Then use different methods to identify risky permission subsets. Secondly, then analyze the usefulness of risky permissions for malapps detection with subset selection. Thirdly, in depth analyze the detection results and determine the feasibility as well as the limitations of malapps detection based on permission requests.

1. W. Enck, D. Octeau, P. McDaniel, and S. Chaudhuri, "A study of Android application security," in Proc. 20th USENIX Secur. Symp. , 2011.
2. Yajin Zhou, Xuxian Jiang" Dissecting Android Malware: Characterization and Evolution" in 2012 IEEE Symposium on Security and Privacy© 2012.
3. John P. Murphy, Vincent H. Berk, Ian Gregorio-de Souza"Decision Support Procedure in the Insider Threat Domain" in IEEE, 2012.
4. H. Peng et al. , "Using probabilistic generative models for ranking risks of Android apps, in Proc. ACM Conf. CCS, 2012.
5. B. P. Sarma, N. Li, C. Gates, R. Potharaju, C. Nita-Rotaru, and I. Molloy, "Android permissions: A perspective combining risks and benefits," in Proc. 17th ACM SACMAT,2012.
6. R. Pandita, X. Xiao, W. Yang, W. Enck, and T. Xie, "WHYPER: Towards automating risk assessment of mobile applications," in Proc. 22nd USENIX Secur. Symp. , 2013.
7. JianlinXu, Yifan Yu, Zhen Chen_, Bin Cao, Wenyu Dong, Yu Guo, and Junwei Cao "MobSafe: Cloud Computing Based Forensic Analysis for Massive Mobile Applications Using Data Mining", inISSNll1007-0214ll10/10llpp418-427,Number 4, August 2013.
8. Wei Wang, Xing Wang, DaweiFeng, Jiqiang Liu, Zhen Han, and Xiangliang Zhang "Exploring Permission-Induced Risk in Android " in IEEE transactions on information forensicsand security, no. 11, november 2014.
9. Yuan Zhang, Min Yang, Zhemin Yang, GuofeiGu, PengNing and BinyuZang "Permission Use Analysis for Vetting Undesirable Behaviors in Android Apps" in IEEE transactions on information forensics and security, vol. 9,no. november 2014.
10. Yajin Zhou Zhi Wang Wu Zhou Xuxian Jiang"Detecting Malicious Apps in Official and Alternative Android Markets"in Department of ComputerScienceNorth Carolina State University 2011.

Android Malapps Detection Permission Control Induced Risk.