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- W4385193085 abstract "Because there are so many issues that have had suitable solutions, cybersecurity is now the subject that worries computer scientists and system administrators the most. The rapid development of information technology and its inherent integration into every aspect of our lives have made it possible to analyze and identify a broad variety of harmful software packages and the targets of these programmes. Malware exists.Recently, Android malware has gotten some notice. It seems to attract a lot of attention on the internet. Android is one of the most well-liked operating systems that dominates the operating system market. In 2020, 85% of smartphones will run on the Android operating system, according to statistics from the system. Mobile virus attacks have increased in frequency over time. Known to infect a phone system with applications that seem harmless but really contain malware is one of the most popular approaches. Malware on cellphones has already been detected using machine learning. Deep learning and supervised learning techniques have been used to achieve this. Drawing on consumer rights, this study evaluates the effectiveness of multiple categorization approaches to find virus in Android apps." @default.
- W4385193085 created "2023-07-25" @default.
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- W4385193085 date "2023-05-12" @default.
- W4385193085 modified "2023-10-16" @default.
- W4385193085 title "The Role of Machine Learning Algorithms in Developing Android App and to do Malware Detection" @default.
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- W4385193085 doi "https://doi.org/10.1109/icacite57410.2023.10182785" @default.
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