Abstract
Spiking neural P systems, SN P systems for short, have found various applications over time. Perhaps the most important application to date is in the area of artificial intelligence where SN P systems are significant models of the third generation of neural networks. Another application of SN P systems that has not been researched much is cryptography. SN P systems can be used as computational devices on which various cryptographic algorithms can be implemented. Many of the machine learning algorithms that are applied in cryptography are based on neural networks which can be implemented using SN P systems. In this paper, we propose a new type of SN P system called Anti-Spiking Neural Tree Parity Machine. The system is inspired by how a Tree Parity Machine works and is constructed using SN P systems with anti-spikes. Based on the new system, we propose a novel key agreement protocol that allows two parties to communicate over a public channel and obtain a secret shared key. We perform multiple experiments in which we show the efficiency of our protocol and its security.
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Acknowledgements
This research was supported by the European Regional Development Fund, Competitiveness Operational Program 2014–2020 through project IDBC (code SMIS 2014+: 121512).
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Plesa, MI., Gheoghe, M., Ipate, F. et al. A key agreement protocol based on spiking neural P systems with anti-spikes. J Membr Comput 4, 341–351 (2022). https://doi.org/10.1007/s41965-022-00110-9
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DOI: https://doi.org/10.1007/s41965-022-00110-9