@inproceedings{1c4fdabdd67d469f87db420ed4a86bda,
title = "Classification Method of Blockchain and IoT Devices Based on LSTM",
abstract = "With the development of the technology, more and more blockchain devices and Internet of Things devices are deployed around us. In order to manage these devices more conveniently, it is necessary to classify the devices according to the flow rate. The existing classification methods of devices are divided into active detection and passive detection. Active detection needs to send messages to them. Passive detection only needs to get the flow information of the devices, and existing passive detection needs to do so. The methods are all based on complete flow. We propose a method based on the previous part of the flow, using LSTM and random forest algorithm to classify. The f1-score of our method is 0.89. Compared with the existing methods, our method improves by 8%–30%, and our method can classify devices more effectively.",
keywords = "Blockchain, Internet of things, LSTM, Network traffic, Random forest",
author = "Pengyu Duan and Ruiguang Li and Liehuang Zhu and Hao Yu",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 3rd International Conference on Blockchain and Trustworthy Systems, Blocksys 2021 ; Conference date: 05-08-2021 Through 06-08-2021",
year = "2021",
doi = "10.1007/978-981-16-7993-3_27",
language = "English",
isbn = "9789811679926",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "355--367",
editor = "Hong-Ning Dai and Xuanzhe Liu and Luo, {Daniel Xiapu} and Jiang Xiao and Xiangping Chen",
booktitle = "Blockchain and Trustworthy Systems - 3rd International Conference, BlockSys 2021, Revised Selected Papers",
address = "Germany",
}