DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-7 ( Jul, 2022 ) | |||||||||
Paper Title |
SecuroPoint for the Application of Malware Detection in Android apps | |||||||||
Author Name |
Kalaivani. D, Vinay Hegde, Prajwal P, Praveen Hegde, Chrisel Fernandes | |||||||||
Affilition |
1Assistant Professor, Department of Information Science and Engineering, New Horizon College of Engineering, Bangalore, Karnataka, India 2,3,4,5Department of Information Science and Engineering, New Horizon College of Engineering, Bangalore, Karnataka, India | |||||||||
Pages |
18-24 | |||||||||
Abstract |
Abstract - Malware is quite possibly the main dangers in the present figuring world since the quantity of website circulating Malware is expanding quickly. Malware examination and avoidance strategies are progressively becoming essential for Computer frameworks associated with the web. SecuroPoint is a software using python for the application of Determining the probability of an Android Application having malware insideit. The product is tried on certifiable information, and it can effectively distinguish which application has malware inside. It will Increase the security of Android clients. For instance, assuming you download an application that isn't in PlayStore, this device can assist with deciding if the application has malwares or not. With this usefulness, you will know which application is protected to Download, and if the application has malware, you will actually want to erase it. Assuming you are a scientist or designer working in Android security, you can utilize this instrument for doing your exploration. The reason for the venture is to plan a Neural Network that could decide the malwares. Since the Neural organization is prepared on a large number of existing Android Applications, it can effectively anticipate the Possibility of any new application having malware regardless of whether the malware is recently evolved. In this undertaking, We are utilizing AI calculations like Random Forest, Logistic Regression calculation, and Kaggle MalwareDataset. Keywords - Android Mobile Security, Malware Analysis, Machine Learning. | |||||||||
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