A Key Exchange Optimization Scheme Based on Tree Parity Machine

Yiliang HAN; Yu LI; Zhe LI

doi:10.11999/JEIT200633

Volume 43 Issue 8

Aug. 2021

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Yiliang HAN, Yu LI, Zhe LI. A Key Exchange Optimization Scheme Based on Tree Parity Machine[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2140-2148. doi: 10.11999/JEIT200633

Citation:

Yiliang HAN, Yu LI, Zhe LI. A Key Exchange Optimization Scheme Based on Tree Parity Machine[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2140-2148. doi: 10.11999/JEIT200633

Yiliang HAN, Yu LI, Zhe LI. A Key Exchange Optimization Scheme Based on Tree Parity Machine[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2140-2148. doi: 10.11999/JEIT200633

Citation:

Yiliang HAN, Yu LI, Zhe LI. A Key Exchange Optimization Scheme Based on Tree Parity Machine[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2140-2148. doi: 10.11999/JEIT200633

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A Key Exchange Optimization Scheme Based on Tree Parity Machine

doi: 10.11999/JEIT200633

Department of Cryptographic Engineering, Engineering University of PAP, Xi’an 710086, China

Funds: The National Natural Science Foundation of China (61572521), The Scientific Foundation of the Scientific Research and Innovation Team of Engineering University of PAP (KYTD201805), The Natural Science Basic Research Plan in Shaanxi Province (2021JM252)

Received Date: 2020-07-29
Rev Recd Date: 2020-12-25

Available Online: 2020-12-31

Publish Date: 2021-08-10

Abstract

Abstract

Synchronization of Tree Parity Machines (TPM) by mutual learning can be used to achieve key exchange schemes. The security of the scheme depends on the structure parameters of TPM. In order to obtain the parameters that make the key exchange scheme more secure and less computation, a key exchange optimization scheme based on TPM is proposed. Firstly, the learning rules of vectorization are defined to improve the efficiency of synchronization of TPM. Secondly, the cooperating attack algorithm for synchronization of TPM is improved to make it adaptive to the change of parameters. Finally, the efficiency and security of the scheme are tested by simulation experiment. The simulation results show that the vectorization of TPM can reduce the synchronization time by about 90%, which does not reduce the number of steps required for synchronization and affect the security. Among the parameters that can be used to generate 512 bit fixed length key, the probability of (14, 14, 2) being attacked by cooperating attack is 0%, and the synchronization time is less. Therefore, the proposed key exchange optimization scheme is secure and efficient.
- Cryptography,
- Key exchange,
- Artificial neural network,
- Tree Parity Machine(TPM),
- Mutual learning

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References(22)

References

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