Android Malware Detection Using Genetic Algorithm based Optimized Feature Selection and Deep Learning

Android Malware Detection Using Genetic Algorithm based Optimized Feature Selection and Deep Learning
Author(s):
Smitha S, Sneha N, Kavya B M, Manasa G R, Heena Kousar
Keywords:
Android malware detection, genetic algorithm, feature selection, deep learning
Abstract
Malware has become a serious threat to Android devices due to the increasing popularity of these devices. In this paper, we propose a novel method for Android malware detection using genetic algorithm based optimized feature selection and deep learning. Our approach aims to select the most relevant features for detecting Android malware using genetic algorithm based optimization. The selected features are then used to train a deep learning model using CNN and LSTM algorithm for accurate malware detection. We evaluate the performance of our proposed method using a dataset of Android malware and benign apps. The results show that our approach achieves high accuracy in detecting Android malware, outperforming existing methods.
Article Details
Unique Paper ID: 159655 Publication Volume & Issue: Volume 9, Issue 12 Page(s): 348 - 354
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