Abstract
Android apps are fast evolving throughout the mobile ecosystem, yet Android malware is always appearing. Various researchers have looked at the issue related with detection of Android malware and proposed hypothesis and approaches from various angles. According to existing studies, machine learning and deep learning seems to be an effective and promising method for detecting Android malware. Despite this, machine learning is used to detect Android malware from various angles. By evaluating a broader variety of facets of the issue, the review work complements prior evaluations. The review process undertakes a systematic literature review to discuss a number of machine learning and deep learning technology that might be used to detect and prevent Android malware from infecting mobile devices. This is a strategy to cope with the rising threat of malware in the Android apps.
Publisher
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Subject
Management of Technology and Innovation,General Engineering
Cited by
1 articles.
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1. Investigation of Malware & Threat Analysis on APKs Using SVM & ANN Algorithm. -A New Approach;2023 International Conference on Recent Advances in Information Technology for Sustainable Development (ICRAIS);2023-11-06