Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Practical Secret Key Generation Under Correlated Eavesdropping: Conditional Min-Entropy Analysis and Real-Time Privacy Amplification

Amitha Mayya, Linda Senigagliesi, Arsenia Chorti

Published Sep 15, 2026• 0 citations
Publisher
DOI
10.5281/zenodo.22765355

Related papers

Secret Key Generation From Correlated Sources

Amin Gohari, Onur Günlü, Gerhard G. Kramer

•Jan 1, 2017•0 citations

Amplifying Privacy in Privacy Amplification.

Divesh Aggarwal, Yevgeniy Dodis, Zahra Jafargholi +2 more

We study the classical problem of privacy amplification, where two parties Alice and Bob share a weak secret X of min-entropy k, and wish to agree on secret key R of length m over a public communication channel completely controlled by a computationally unbounded attacker Eve. Despite being extensively studied in the literature, the problem of designing “optimal ” efficient privacy amplification protocols is still open, because there are several optimization goals. The first of them is (1) minimizing the entropy loss L = k−m (it is known that the optimal value for L = O(λ), where ε = 2−λ is the desired security of the protocol). Other important considerations include (2) minimizing the number of communication rounds, (3) maintaining security even after the secret key is used (this is called post-application robustness), and (4) ensuring that the protocol P does not leak some “useful information ” about the source X (this is called source privacy). Additionally, when dealing with a very long source X, as happens in the so-called Bounded Retrieval Model (BRM), extracting as long a key as possible is no longer the goal. Instead, the goals are (5) to touch as little of X as possible (for efficiency), and (6) to be able to run the protocol many times on the same X, extracting multiple secure keys.

•Jan 1, 2013•0 citations

Entropy-Driven Privacy Amplification with Adaptive Chaotic Statistical Conditioning for Quantum Key Distribution

R. K. Mugelan, N. G. Swetha

Abstract Privacy amplification is the final and most critical stage of quantum key distribution (QKD), where any residual correlation between the reconciled key and an eavesdropper must be eliminated. In practical systems, however, the corrected key may deviate from ideal uniformity due to channel asymmetries and finite-size effects, limiting the effectiveness of conventional hash-based methods. This work presents an entropy-driven privacy amplification framework that combines deterministic matrix-based entropy equalization with adaptive chaotic statistical conditioning. The reconciled key is first transformed into a structured decimal matrix, where controlled numerical diversification enables entropy evaluation across row- and column-wise representations. The entropy-dominant component is then mapped to an intermediate binary key. A subsequent stage applies coupled Logistic and Chebyshev maps whose parameters are adaptively tuned by the measured entropy of the intermediate sequence, allowing residual statistical imbalance to be suppressed without fixed parameter selection. The chaotic stage acts as a statistical conditioner and does not replace formal randomness extractors. The simulation results for key lengths ranging from 128 to 1024 bits show that Shannon entropy is greater than 0.999, min-entropy is greater than 0.97, with bit uniformity approaching 0.5. All of the sequences pass standard NIST randomness tests. In comparison with commonly used privacy amplification techniques, the proposed approach exhibits improved entropy stability under biased input conditions while maintaining linear computational complexity, making it suitable for practical QKD post-processing.

•Feb 2, 2026•0 citations

Distributed Privacy Amplification of Encrypted Multiple Sources with Correlated Keys

Yasutada Oohama, S Rahmat Bagus

•Jan 1, 2016•0 citations

Efficient Privacy Amplification Algorithms for Quantum Key Distribution

Takeshi Asai, Toyohiro Tsurumaru

IEICE Technical Report; IEICE Tech. Rep.•Feb 24, 2011•5 citations

Secure bound analysis of quantum key distribution with non-uniform random seed of privacy amplification

Bingze Yan, Yucheng Qiao, Qiong Li +1 more

Precise quantum key distribution (QKD) secure bound analysis is essential for practical QKD systems. The effect of uniformity of random number seed for privacy amplification is not considered in existing secure bound analysis. In this paper, we propose and prove the quantum leftover hash lemma with non-uniform random number seeds based on the min-entropy, and we give a precise QKD secure bound analysis with non-uniform random number seeds on this basis. We take the two-decoy BB84 protocol as an example to simulate the effect of random number seed uniformity on the secure bound of a QKD system. The experimental results indicate that when the average min-entropy of the random number generator is below 0.95, the secure bound of a QKD system will be seriously affected.

arXiv:2207.08345•Jul 18, 2022•0 citations
We study the classical problem of privacy amplification, where two parties Alice and Bob share a weak secret X of min-entropy k, and wish to agree on secret key R of length m over a public communication channel completely controlled by a computationally unbounded attacker Eve. Despite being extensively studied in the literature, the problem of designing “optimal ” efficient privacy amplification protocols is still open, because there are several optimization goals. The first of them is (1) minimizing the entropy loss L = k−m (it is known that the optimal value for L = O(λ), where ε = 2−λ is the desired security of the protocol). Other important considerations include (2) minimizing the number of communication rounds, (3) maintaining security even after the secret key is used (this is called post-application robustness), and (4) ensuring that the protocol P does not leak some “useful information ” about the source X (this is called source privacy). Additionally, when dealing with a very long source X, as happens in the so-called Bounded Retrieval Model (BRM), extracting as long a key as possible is no longer the goal. Instead, the goals are (5) to touch as little of X as possible (for efficiency), and (6) to be able to run the protocol many times on the same X, extracting multiple secure keys.
Abstract Privacy amplification is the final and most critical stage of quantum key distribution (QKD), where any residual correlation between the reconciled key and an eavesdropper must be eliminated. In practical systems, however, the corrected key may deviate from ideal uniformity due to channel asymmetries and finite-size effects, limiting the effectiveness of conventional hash-based methods. This work presents an entropy-driven privacy amplification framework that combines deterministic matrix-based entropy equalization with adaptive chaotic statistical conditioning. The reconciled key is first transformed into a structured decimal matrix, where controlled numerical diversification enables entropy evaluation across row- and column-wise representations. The entropy-dominant component is then mapped to an intermediate binary key. A subsequent stage applies coupled Logistic and Chebyshev maps whose parameters are adaptively tuned by the measured entropy of the intermediate sequence, allowing residual statistical imbalance to be suppressed without fixed parameter selection. The chaotic stage acts as a statistical conditioner and does not replace formal randomness extractors. The simulation results for key lengths ranging from 128 to 1024 bits show that Shannon entropy is greater than 0.999, min-entropy is greater than 0.97, with bit uniformity approaching 0.5. All of the sequences pass standard NIST randomness tests. In comparison with commonly used privacy amplification techniques, the proposed approach exhibits improved entropy stability under biased input conditions while maintaining linear computational complexity, making it suitable for practical QKD post-processing.
Precise quantum key distribution (QKD) secure bound analysis is essential for practical QKD systems. The effect of uniformity of random number seed for privacy amplification is not considered in existing secure bound analysis. In this paper, we propose and prove the quantum leftover hash lemma with non-uniform random number seeds based on the min-entropy, and we give a precise QKD secure bound analysis with non-uniform random number seeds on this basis. We take the two-decoy BB84 protocol as an example to simulate the effect of random number seed uniformity on the secure bound of a QKD system. The experimental results indicate that when the average min-entropy of the random number generator is below 0.95, the secure bound of a QKD system will be seriously affected.