arrow
Return

Multi-Party Cryptographic Key Distribution Protocol over a Public Network Based on a Quick-Response Code

delete2022-05-25
delete5
delete
OA
AI
W
Wen-Kai Yu *
Y
Ying Yang
Y
Yaxin Li
N
Ning Wei
S
Shuo-Fei Wang
DOI:10.3390/s22113994delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
In existing cryptographic key distribution (CKD) protocols based on computational ghost imaging (CGI), the interaction among multiple legitimate users is generally neglected, and the channel noise has a serious impact on the performance. To overcome these shortcomings, we propose a multi-party interactive CKD protocol over a public network, which takes advantage of the cascade ablation of fragment patterns (FPs). The server splits a quick-response (QR) code image into multiple FPs and embeds different watermark labels into these FPs. By using a CGI setup, the server will acquire a series of bucket value sequences with respect to different FPs and send them to multiple legitimate users through a public network. The users reconstruct the FPs and determine whether there is an attack in the public channel according to the content of the recovered watermark labels, so as to complete the self-authentication. Finally, these users can extract their cryptographic keys by scanning the QR code (the cascade ablation result of FPs) returned by an intermediary. Both simulation and experimental results have verified the feasibility of this protocol. The impacts of different attacks and the noise robustness have also been investigated.
Keywords:
cryptographic key distribution
multi-party communication
computational ghost imaging
quick-response code
watermark embedding and extraction
identity authentication
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Sensors cover
Sensors
IF:
3.5
Papers:
7.1W
Citations:
20.9W

Organization

B
beijing institute of technology
Scholars:
5.5W
Papers: 4.0W
Citations: 63