Symmetric encryption with key distribution based on neural networks
| Autor: | Alisa Makhmutova, O. E. Gadelshin, Igor V. Anikin |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Theoretical computer science
Artificial neural network business.industry Computer science Key distribution 020206 networking & telecommunications 02 engineering and technology Encryption Tree (data structure) Symmetric-key algorithm Synchronization (computer science) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business Secure channel Key exchange |
| Zdroj: | 2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). |
| DOI: | 10.1109/icieam.2016.7911640 |
| Popis: | In this paper, a symmetric encryption approach with key distribution based on artifitial neural networks (ANN) has been investigated and implemented. We have used the ANN synchronization scheme with the tree parity machine for secret key exchange through a public channel. We developed the software for training the TPM and establishing the secure channel between two parties. We also made some experiments and got some conclusions about applying different TPM learning rules. We compare the number of tries and errors during TPM training. We found that using the classic Hebbian rule for TPM's training provides the best training results. We also found that more than 60% of TPM runs was learned from the weight changing. The developed software is suitable for application area which require reinforced protection of sending messages. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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