Research on predicting trusted business relationships in autonomous  system based on neural networks

Xuesong Guo; Dabei Chen; Jun Chen; Zihan Xiong

doi:10.1117/12.3010226

20 October 2023 Research on predicting trusted business relationships in autonomous system based on neural networks

Xuesong Guo, Dabei Chen, Jun Chen, Zihan Xiong

Proceedings Volume 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023); 1281427 (2023) https://doi.org/10.1117/12.3010226
Event: Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 2023, Chongqing, China

Abstract

Autonomous System (AS) business relationship data serves as an important trust foundation for detecting route leaks. Some AS's reluctant to disclose all of their business relationship data for various reasons has led to a decrease in routing detection accuracy, requiring AS business relationship prediction. The existing AS business relationship prediction schemes have problems with data tampering and the accuracy needs to be improved. This article proposes a trusted AS business relationship prediction method based on neural networks. By collecting and storing AS business relationship data on the blockchain, a feature library of AS business relationship data is constructed. Finally, a deep neural network is used for AS business relationship prediction to achieve reliable and accurate AS business relationship prediction.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xuesong Guo, Dabei Chen, Jun Chen, and Zihan Xiong "Research on predicting trusted business relationships in autonomous system based on neural networks", Proc. SPIE 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 1281427 (20 October 2023); https://doi.org/10.1117/12.3010226

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available