@inproceedings{5a7ab38294c84514ae9309fe32638445,
title = "MDIot: IoT device identification method based on traffic characteristics",
abstract = "In recent years, the rapid growth of the Internet of Things (IoT) devices has brought with it security risks, highlighting the need for management for IoT devices. Identification and classification are key components of devices management. However, existing work on IoT device identification is based on prior knowledge to manually extract features, resulting in too many redundant features and reducing devices identification accuracy. In this paper, we propose amodel called MDIoT. Our model use the multi-votingmethod for feature selection, and is combined with Multiobjective Genetic Algorithm to reduce redundancy features and noise. Experimental results show that our feature selection method is more efficient in feature selection and the classification accuracy is over 95\%.",
keywords = "Device feature, Device identification, Internet of Things, MDIoT",
author = "Hanxi Zheng and Ruijun Liu and Huanpu Yin and Haisheng Li",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.; 19th Chinese Intelligent Systems Conference, CISC 2023 ; Conference date: 14-10-2023 Through 15-10-2023",
year = "2023",
doi = "10.1007/978-981-99-6882-4\_19",
language = "英语",
isbn = "9789819968817",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "231--239",
editor = "Yingmin Jia and Weicun Zhang and Yongling Fu and Jiqiang Wang",
booktitle = "Proceedings of 2023 Chinese Intelligent Systems Conference - Volume II",
address = "德国",
}