Abstract
In this paper we analyse the security of a new key exchange protocol proposed in [3], which is based on mutually learning neural networks. This is a new potential source for public key cryptographic schemes which are not based on number theoretic functions, and have small time and memory complexities. In the first part of the paper we analyse the scheme, explain why the two parties converge to a common key, and why an attacker using a similar neural network is unlikely to converge to the same key. However, in the second part of the paper we show that this key exchange protocol can be broken in three different ways, and thus it is completely insecure.
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References
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Ido Kanter, Wolfgang Kinzel, Eran Kanter, “Secure exchange of information by synchronization of neural networks”, Europhys., Lett. 57, 141, 2002.
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© 2002 Springer-Verlag Berlin Heidelberg
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Klimov, A., Mityagin, A., Shamir, A. (2002). Analysis of Neural Cryptography. In: Zheng, Y. (eds) Advances in Cryptology — ASIACRYPT 2002. ASIACRYPT 2002. Lecture Notes in Computer Science, vol 2501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36178-2_18
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DOI: https://doi.org/10.1007/3-540-36178-2_18
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Online ISBN: 978-3-540-36178-7
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