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- W3213413736 abstract "The world is seeing a rapid growth in mobile malware applications. Traditional computer malware programmers are shifting to android malware applications. Consequently, mobile security specialists are also working very hard to obtain a robust explication to this current problem. Many anti malware applications have also been launched to tackle this problem. In this paper we have tried to propose a system for detection of malware application based on Blockchain with help of machine learning. We use one internal permissioned blockchain with feature extractor model and one external permissioned blockchain feedback to another machine learning model to accomplish this task. We use dedicated internal blockchain for each application to make our system error free and more accurate." @default.
- W3213413736 created "2021-11-22" @default.
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- W3213413736 date "2021-10-01" @default.
- W3213413736 modified "2023-09-25" @default.
- W3213413736 title "Malware Mobile Application Detection Using Blockchain and Machine Learning" @default.
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- W3213413736 doi "https://doi.org/10.1109/gcat52182.2021.9587880" @default.
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