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http://dx.doi.org/10.20465/KIOTS.2020.6.4.065

Design and Implementation of Machine Learning-based Blockchain DApp System  

Lee, Hyung-Woo (Div. of Computer Engineering, Hanshin University)
Lee, HanSeong (Dept. of Computer Engineering, Hanshin University)
Publication Information
Journal of Internet of Things and Convergence / v.6, no.4, 2020 , pp. 65-72 More about this Journal
Abstract
In this paper, we developed a web-based DApp system based on a private blockchain by applying machine learning techniques to automatically identify Android malicious apps that are continuously increasing rapidly. The optimal machine learning model that provides 96.2587% accuracy for Android malicious app identification was selected to the authorized experimental data, and automatic identification results for Android malicious apps were recorded/managed in the Hyperledger Fabric blockchain system. In addition, a web-based DApp system was developed so that users who have been granted the proper authority can use the blockchain system. Therefore, it is possible to further improve the security in the Android mobile app usage environment through the development of the machine learning-based Android malicious app identification block chain DApp system presented. In the future, it is expected to be able to develop enhanced security services that combine machine learning and blockchain for general-purpose data.
Keywords
Machine Learning; Blockchain; DApp System; Android System; Malicious App Detection; Mobile Security;
Citations & Related Records
Times Cited By KSCI : 10  (Citation Analysis)
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