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Discovery of robust protocols for secure quantum cryptography

Published: 13 July 2019 Publication History

Abstract

Quantum Key Distribution (QKD) allows for two parties to establish a shared secret key which is secure against an all-powerful adversary (a task impossible to achieve using only classical communication). Furthermore, any attack against these systems creates an observable "noise signature." This work develops a new solution representation for QKD protocols allowing a GA to evolve optimal protocols to counter observed attacks against the communication.

References

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Igor Devetak and Andreas Winter. 2005. Distillation of secret key and entanglement from quantum states. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science 461, 2053 (2005), 207--235.
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Alex Satoru Fukunaga and Andrew B Kahng. 1995. Improving the performance of evolutionary optimization by dynamically scaling the evaluation function. UCLA Computer Science Department.
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Walter O Krawec. 2016. A genetic algorithm to analyze the security of quantum cryptographic protocols. In Evolutionary Computation (CEC), 2016 IEEE Congress on. IEEE, 2098--2105.
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Walter O Krawec, Michael G Nelson, and Eric P Geiss. 2017. Automatic generation of optimal quantum key distribution protocols. In Proceedings of the Genetic and Evolutionary Computation Conference. ACM, 1153--1160.
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Walter O Krawec, Stjepan Picek, and Domagoj Jakobovic. 2019. Evolutionary Algorithms for the Design of Quantum Protocols. In To appear, EvoApplications 2019.
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M.A. Nielsen and I.L. Chuang. 2000. Quantum Computation and Quantum Information. Cambridge University Press, Cambridge, MA.
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Stjepan Picek and Marin Golub. 2011. On evolutionary computation methods in cryptography. In MIPRO, 2011 Proc. 34th International Convention. IEEE, 1496--1501.
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Stjepan Picek, Luca Mariot, Alberto Leporati, and Domagoj Jakobovic. 2017. Evolving S-boxes based on cellular automata with genetic programming. In Proc. GECCO 2017 Companion. ACM, 251--252.
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L. Spector. 2004. Automatic Quantum Computer Programming: A Genetic Programming Approach. Kluwer Academic Publishers, Boston, MA.

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    cover image ACM Conferences
    GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
    July 2019
    2161 pages
    ISBN:9781450367486
    DOI:10.1145/3319619
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 13 July 2019

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    Author Tags

    1. genetic algorithm
    2. quantum computing
    3. quantum cryptography

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    GECCO '19
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    GECCO '19: Genetic and Evolutionary Computation Conference
    July 13 - 17, 2019
    Prague, Czech Republic

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