Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 1
70-74,89

Federated spectral clustering algorithm for ship AIS trajectory

Lyu Guohua
Hu Xuexian
Zhang Qihui
Wei Jianghong
PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China
DOI: 10.19734/j.issn.1001-3695.2021.06.0221

Abstract

How to realize safety data sharing and promote the integration of multi-source data is one of the important technical challenges faced by academic and industrial circles. In recent years, federated learning has received widespread attention, which is a new technology to deal with this challenge. Federated learning has been applied in fields such as smart healthcare and smart city construction, but there is little research in the field of potential trajectory data mining. To solve this problem, this paper proposed a distributed and secure framework named federated spectral clustering(FSC), and applied it to the spectral clustering of ship AIS trajectory data. In the FSC framework, it used the encrypted sample alignment technology and a homomorphic encryption scheme as building blocks for the clustering algorithm, guaranteeing the security of the data in the process of federal training executed by multi-participants. To illustrate the effect of this algorithm, this paper conducted the experiments on both synthetic datasets and ships AIS trajectory datasets. The comparisons of experiments results with other similar clustering algorithms demonstrate that, besides its security advantage, this algorithm performs well in terms of clustering effect. The results indicate that the FSC can obtain the main route in the marine navigation area, which can provide specialized support for the intelligence of maritime supervision systems.

Foundation Support

国家自然科学基金资助项目(61862011,61872449,61772548)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0221
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 1
Section: Algorithm Research & Explore
Pages: 70-74,89
Serial Number: 1001-3695(2022)01-012-0070-05

Publish History

[2021-10-08] Accepted Paper
[2022-01-05] Printed Article

Cite This Article

吕国华, 胡学先, 张启慧, 等. 基于联邦学习的船舶AIS轨迹谱聚类算法研究 [J]. 计算机应用研究, 2022, 39 (1): 70-74,89. (Lyu Guohua, Hu Xuexian, Zhang Qihui, et al. Federated spectral clustering algorithm for ship AIS trajectory [J]. Application Research of Computers, 2022, 39 (1): 70-74,89. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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