Discover and Analyzes Whether Mobile Applications Downloaded From the Internet Are Good or Bad
G. Kalaimani1, G. Kavitha2
1Dr. G. Kalaimani, Professor, Department of Computer Science and Engineering, shadan women’s college of Engineering & Technology, Hyderabad, Telangana India.
2Dr. G. Kavitha, Professor, Department of Computer Science and Engineering, Muthayammal Engineering College, Kakkaveri, Rasipuram, Tamil Nadu, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 4939-4943 | Volume-8 Issue-4, November 2019. | Retrieval Number: C5883098319/2019©BEIESP | DOI: 10.35940/ijrte.C5883.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Android Malware is pernicious software. It is configured to attack the hardware such as android or mobile phone or smart phone. It is designed to exploit the flaw in specific mobile phone software technologies and operating systems. Nowadays, the mobile phone is the number one most vulnerable to malware attacks. Malware can be in the form of adware, Trojans, viruses, root kits and spyware. They delete important documents or steal protected data or bring software that is not authorized by the user. To solve this problem you need to categorize the applications on the mobile. The techniques used in machine learning are used here to differentiate between applications in mobile as good or bad. In this paper, present two methods as using the Genetic algorithm for feature selection and the Nearest Neighbor for classification.
Keywords: Mobile Malware, Feature Selection, Classification, Genetic Algorithm, Nearest Neighbor.
Scope of the Article: Classification.