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Journal Article Improvement of the Efficiency of Neural Cryptography-Based Secret Key Exchange Algorithm
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Authors
Juyoung Kim, Sooyong Jeong, Dowon Hong, Nam-Su Jh
Issue Date
2023-05
Citation
IEEE Access, v.11, pp.45323-45333
ISSN
2169-3536
Publisher
Institute of Electrical and Electronics Engineers Inc.
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1109/ACCESS.2023.3273011
Abstract
Owing to new security threats and relevant changes in network computing environments, key exchange methods that replace conventional public key exchange algorithms are being researched. The neural cryptography-based key exchange algorithm proposed recently uses neural synchronization as an alternative to public-key methods. However, the learning-based synchronization method uses considerable communication resources to generate output values and share the results. The efficiency of this method depends on the type of algorithm and is affected by both the communication rounds for exchanging output values and the number of weight learning rounds. To improve its efficiency, this paper proposes 1-h random walk and batch scheme methods and verifies their efficiency and security.
KSP Keywords
Communication resources, Cryptography-based, Exchange algorithm, Its efficiency, Learning-based, Neural synchronization, Public Key, Random Walk, Security threats, Weight learning, neural cryptography
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC ND)
CC BY NC ND