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Design and Implementation of Machine Learning-based Blockchain DApp System

머신러닝 기반 블록체인 DApp 시스템 설계 및 구현

  • Lee, Hyung-Woo (Div. of Computer Engineering, Hanshin University) ;
  • Lee, HanSeong (Dept. of Computer Engineering, Hanshin University)
  • 이형우 (한신대학교 컴퓨터공학부) ;
  • 이한성 (한신대학교 대학원 컴퓨터공학과)
  • Received : 2020.10.14
  • Accepted : 2020.11.30
  • Published : 2020.12.31

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.

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