Genetic Algorithm to Study Practical Quantum Adversaries
Title | Genetic Algorithm to Study Practical Quantum Adversaries |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Krawec, Walter O., Markelon, Sam A. |
Conference Name | Proceedings of the Genetic and Evolutionary Computation Conference |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-5618-3 |
Keywords | composability, genetic algorithm, Metrics, pubcrawl, quantum computing, quantum computing security, quantum cryptography, resilience, Resiliency, Scalability |
Abstract | In this paper we show how genetic algorithms can be effectively applied to study the security of arbitrary quantum key distribution (QKD) protocols when faced with adversaries limited to current-day technology. We compare two approaches, both of which take into account practical limitations on the quantum power of an adversary (which can be specified by the user). Our system can be used to determine upper-bounds on noise tolerances of novel QKD protocols in this scenario, thus making it a useful tool for researchers. We compare our algorithm's results with current known numerical results, and also evaluate it on newer, more complex, protocols where no results are currently known. |
URL | https://dl.acm.org/citation.cfm?doid=3205455.3205478 |
DOI | 10.1145/3205455.3205478 |
Citation Key | krawec_genetic_2018 |