Abstract. A good number of android applications are available in markets on the Internet. Among them a good number of applications are law quality apps (or malware) and therefore it is difficult for android users to decide whether particular application is malware or benign at installation time. In this paper, we propose a design of system to classify android applications into two classes i.e. malware or benign. We have used hybrid approach by combining application analysis and machine learning technique to classify the applications. Application analysis is performed by both static and live analysis techniques. Genetic algorithm based machine learning technique is used to create rules for creating rule base for the system. The system is tested with applications collected from the various markets on the Internet and two datasets. We have obtained 96.43 % detection rate to classify the applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.