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QCCC commitment from quantum inaccessible entropy generator

delete2026-03-17
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OA
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K
K. L. Gao *
S
Shujiao Cao *
T
Tianshu Shan
R
Rui Xue
DOI:10.1186/s42400-025-00451-9delete
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Abstract

Abstract

En 中文
Quantum commitment schemes remain challenging to deploy in practice due to the high cost and fragility of quantum communication. Although recent advances have leveraged quantum channels to improve security and efficiency, these schemes often require substantial quantum interaction, limiting their practicality. To address these challenges, we follow the emerging paradigm of quantum-computation classical-communication (QCCC) protocols, which minimize quantum communication while preserving robust security guarantees. In this work, we construct a QCCC commitment scheme that achieves statistically hiding and computationally collapse-binding-a strong binding notion previously attainable only via collapsing hash functions, which are believed to be stronger than quantum collision-resistant hash functions. In order to circumvent the obstacle of quantum rewinding for an entirely quantum adversary, our construction introduces a novel cryptographic primitive, the quantum inaccessible entropy generator (qIEG), as a quantum analogue of the classical IEG framework developed by Haitner et al. [STOC ’09]. Notably, our approach relies on potentially weaker assumptions, marking a significant step toward practically deployable and theoretically robust quantum commitments in communication-constrained quantum settings.
Keywords:
Quantum inaccessible entropy generator
QCCC commitment
Quantum computationally binding property
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

C
Cybersecurity
IF:
3.7
Papers:
609
Citations:
1.0K

Organization

K
Key Laboratory of Cyberspace Security Defense
Scholars:
51
Papers: 22
Citations: 0
Cited Papers

Cited Papers

Constant-Round Oblivious Transfer in the Bounded Storage Model
err2004-01-01
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PREAI
errDing,Yan Zong; Harnik,Danny; Rosen,Alon; Shaltiel,Ronen
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Reducing Complexity Assumptions for Statistically-Hiding Commitment
err2005-01-01
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errOAAI
errIftach Haitner; Omer Horvitz; Jonathan Katz; Chiu-Yuen Koo; Ruggero Morselli; Ronen Shaltiel
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