본문 바로가기
  • Home

Design and Implementation of Machine Learning-based Blockchain DApp System

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2020, 6(4), pp.65-72
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : October 14, 2020
  • Accepted : November 30, 2020
  • Published : December 31, 2020

Lee, Hyung Woo 1 HanSeong Lee 1

1한신대학교

Candidate

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.

Citation status

* References for papers published after 2022 are currently being built.