To develop an application in android for smart phones tasks processing to the cloud to detect malware in application and generate reports
Keywords:
Android, Permissions, Security, Instrumentation, Privacy, Risk assessmentAbstract
Most of us use android phones these days and also uses the multiple applications and facilities frequently. Play store provides great number of application but unfortunately few of those applications are fraud. Such applications dose damage to phone and also possibly data thefts. Hence such applications must be marked, so that they will be recognizable for play store users. So we are proposing a web application which will process the information, comments and the reviews of the application on cloud server. As we are handling the big data here so the process is done on cloud server and malware is detected. So it will be easier to decide which application is fraud or not. Multiple applications can be processed at a time with the web application.
References
W. Enck, M. Ongtang, and P. McDaniel, “On lightweight mobile phone application certification,” in Proc. 16th ACM Conf. Comput. Commun. Security, 2009, pp. 235–245.
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 Symp. Access Control Models Technol., 2012, pp. 13–22.
H. Peng, C. Gates, B. Sarma, N. Li, Y. Qi, R. Potharaju, C. Nita- Rotaru, and I. Molloy, “Using probabilistic generative models for ranking risks of Android apps,” in Proc. ACM Conf. Comput. Commun. Security, 2012, pp. 241–252.
Ali K, Lhot_ak O. Application-only call graph construction. In:Proceedings of the 26th European onference onObject-Oriented Programming. Springer-Verlag; 2012.p. 688e712. “A tool for reverse engineering android apk files.”
A.-D. Schmidt, R. Bye, H.-G. Schmidt, J. Clausen, O. Kiraz, K. A. Yuksel, S. A. Camtepe, and S. Albayrak, “Static analysis of executables for collaborative malware detection on Android,” in Proc. IEEE Int. Conf. Commun., 2009, pp. 1–5.
I. Burguera, U. Zurutuza, and S. Nadjm-Tehrani, “Crowdroid: Behavior-based malware detection system for Android,” in Proc. 1st ACM Workshop Security Privacy Smartphones Mobile Devices, 2011, pp. 15–26.
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