Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research 2011
DOI: 10.1145/2179298.2179363
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An empirical analysis of the cascade error reconciliation protocol for quantum key distribution

Abstract: Modern cryptography provides the means to securely communicate data between authorized entities by using mathematical transformations which require pre-shared cryptographic keys. The need to share key material with authorized entities in a secure, cost efficient and timely manner has driven efforts to develop new key distribution methods. A promising method is Quantum Key Distribution (QKD) which is considered to be "unconditionally secure" because it relies upon the immutable laws of quantum physics rather th… Show more

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Cited by 12 publications
(8 citation statements)
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“…As a proof of concept to illustrate the versatility of the modular approach, a simulation experiment using different ER techniques was created. Previous work 12,26 implemented and examined performance issues associated with the Cascade, LDPC, and Winnow algorithms 13 as standalone applications. Given our new design, these algorithms were implemented as modules within the framework.…”
Section: Resultsmentioning
confidence: 99%
“…As a proof of concept to illustrate the versatility of the modular approach, a simulation experiment using different ER techniques was created. Previous work 12,26 implemented and examined performance issues associated with the Cascade, LDPC, and Winnow algorithms 13 as standalone applications. Given our new design, these algorithms were implemented as modules within the framework.…”
Section: Resultsmentioning
confidence: 99%
“…Cascade [17] is a reconciliation method that has become the de-facto standard for all QKD practical implementations. After a number of passes, permutations and cascades, the protocol finishes with low probability that errors still remain [21]. However, large communication overhead have raised methods based on error correcting codes which are more practical.…”
Section: Related Workmentioning
confidence: 99%
“…Preporučen broj rundi je 4. Nakon izvršenja sve četiri runde velika je verovatnoća da su nizovi usaglašeni, što je objašnjeno u radu [7].…”
Section: Simulatorunclassified