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Genetic and Evolutionary Computation Conference (GECCO)

Genetic algorithm to study practical quantum adversaries

Walter O. Krawec, Sam A. Markelon

Published Jul 2, 2018• 1 citation
Publisher

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.

DOI
10.1145/3205455.3205478

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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.
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Genetic Algorithm (GA) may be used to analyses the security of Quantum Key Distribution (QKD) protocols. It evaluates on multiple QKD protocol such as, comparing it to known bounds and also discovering new results. It also shows how it can be used to analyze the security of complicated QKD protocols requiring the adversary to interact with the users. It may also be used to detect security flaws in protocols. This algorithm can be a useful tool in QKD research and design. The genetic algorithm can be used to analyses the security of the quantum cryptographic protocols. This paper handles the different types of attacks like photon loss and multi-photon attacks. Analysis can be done on these protocols namely BB84, B92, SARGO4, Semi-Quantum protocol, Mediated Semi-Quantum protocols. The attacks can be handled by using genetic algorithm is the main intention of this work.
Quantum Key Distribution (QKD) allows two parties to establish a shared secret key secure against an all-powerful adversary. Typically, one designs new QKD protocols and then analyzes their maximal tolerated noise mathematically. If the noise in the quantum channel connecting the two parties is higher than this threshold value, they must abort. In this paper we design and evaluate a new real-coded Genetic Algorithm which takes as input statistics on a particular quantum channel (found using standard channel estimation procedures) and outputs a QKD protocol optimized for the specific given channel. We show how this method can be used to find QKD protocols for channels where standard protocols would fail.
In this paper, we describe a new real coded GA which may be used to analyze the security of quantum key distribution (QKD) protocols by estimating the maximally tolerated error rate - an important statistic and, for many newer more complicated protocols, still unknown. Our algorithm takes advantage of several nice features of QKD protocols to simplify the search process and was evaluated on several protocols and can even detect security flaws in a protocol thus showing our algorithm's usefulness in protocol design.
Quantum key distribution (QKD) enables two remote users to share a string of key bits with information-theoretical security. Parameter optimization is a crucial step in achieving optimal performance in practical QKD systems. In general, such optimization is implemented using a local search algorithm (LSA). However, LSAs inevitably fail to find out the optimal values when the searched key rate function is nonconvex or has a discontinuity of first-order derivatives and a narrow parameter search space. This paper proposes a genetic algorithm-based method to overcome the limitations of LSAs for QKD parameter optimization. We tested the proposed method with various types of common QKD protocols and found that it has very high parameter optimization performance for QKD with a time consumption comparable to that using a standard LSA. We expect our method to be a valuable optimization tool for quantum information processing tasks.
Quantum key distribution (QKD) enables secure information exchange with untrusted quantum links between remote communication parties. A central task in the studies of QKD protocols is security analysis, which aims at deriving the length of the final key such that it is secure regardless of the eavesdropper's computational power. In literature, the security analysis has been done both analytically and numerically. Compared to analytical methods which tend to require techniques specific to each QKD protocol, numerical ones are more general since they can be directly applied to many QKD protocols with little adaptation. However, current numerical methods are carried out based on some assumptions such as working in the asymptotic limit and collective attacks from eavesdroppers. In this work, we remove these assumptions and develop a numerical finite-size security analysis against general attacks for a large class of QKD protocols. We also give an example of applying the method to the recent phase-matching QKD protocol with a simplified protocol design. Our result shows that the finite-size key rate can surpass the linear key-rate bound with a practical QKD system operated for only several hours.