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Article

Aggregatable Subvector Commitment with Efficient Updates

School of Cyperspace Security, Xi’an University of Posts & Telecommunications, Xi’an 710121, China
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Appl. Sci. 2025, 15(2), 554; https://doi.org/10.3390/app15020554
Submission received: 27 November 2024 / Revised: 28 December 2024 / Accepted: 6 January 2025 / Published: 8 January 2025

Abstract

An aggregatable subvector commitment scheme extends a vector commitment scheme by enabling the aggregation of multiple proofs into a single compact subvector proof. However, the existing schemes have to recompute proofs for each position when inserting an element into the vector, incurring significant computational overhead. In this paper, we propose a novel aggregatable subvector commitment scheme based on Newton interpolation, which efficiently supports the addition of new elements. Specifically, the proposed scheme allows incremental updates to the commitment and proofs for each position, avoiding the requirement for full recomputation and thereby significantly reducing computational overhead. Additionally, we employ the Karatsuba algorithm to efficiently perform large-integer multiplication, which improves the aggregation and verification of proofs. Finally, we implement the proposed scheme and conduct a detailed comparison with aSVC. Experimental results demonstrate that the proposed scheme achieves a 48× speedup when adding an element to a 16-length vector, as well as 2.13× and 1.73× speedups for aggregating eight proofs and performing verification, respectively.
Keywords: vector commitment; Newton interpolation; aggregatable vector commitment; Newton interpolation; aggregatable

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MDPI and ACS Style

Xu, Q.; Gao, C.; Wang, Y. Aggregatable Subvector Commitment with Efficient Updates. Appl. Sci. 2025, 15, 554. https://doi.org/10.3390/app15020554

AMA Style

Xu Q, Gao C, Wang Y. Aggregatable Subvector Commitment with Efficient Updates. Applied Sciences. 2025; 15(2):554. https://doi.org/10.3390/app15020554

Chicago/Turabian Style

Xu, Qing, Chenyang Gao, and Yunling Wang. 2025. "Aggregatable Subvector Commitment with Efficient Updates" Applied Sciences 15, no. 2: 554. https://doi.org/10.3390/app15020554

APA Style

Xu, Q., Gao, C., & Wang, Y. (2025). Aggregatable Subvector Commitment with Efficient Updates. Applied Sciences, 15(2), 554. https://doi.org/10.3390/app15020554

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