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Implementation of RSA cryptographic algorithm using SN P systems based on HP/LP neurons

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Abstract

Asymmetric cryptographic systems are often more complex and require more computational power than symmetric systems. This is why they might be implemented using unconventional computing systems, such as P systems, spiking neural systems, and DNA computing. In this work, we design an implementation model for RSA encryption and decryption algorithms in the framework of Spiking neural P systems with HP/LP basic neurons.

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Acknowledgements

We would like to thank the financial support from the Mongolian Foundation for Science and Technology (Research Grants ShUSS- 2018/04). This work has been presented at the 21th International Conference on Membrane Computing (ICMC 2020) in Ulaanbaatar, Mongolia and Vienna, Austria, September 14–17, 2020.

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Authors and Affiliations

  1. School of Information and Communication Technology, Mongolian University of Science and Technology, Ulaanbaatar, Mongolia

    Ganbat Ganbaatar, Dugar Nyamdorj, Gordon Cichon & Tseren-Onolt Ishdorj

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  1. Ganbat Ganbaatar
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  2. Dugar Nyamdorj
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  3. Gordon Cichon
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  4. Tseren-Onolt Ishdorj
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Correspondence to Tseren-Onolt Ishdorj.

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Ganbaatar, G., Nyamdorj, D., Cichon, G. et al. Implementation of RSA cryptographic algorithm using SN P systems based on HP/LP neurons. J Membr Comput 3, 22–34 (2021). https://doi.org/10.1007/s41965-021-00073-3

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