Abstract
We introduce reductions of knowledge, a generalization of arguments of knowledge, which reduce checking knowledge of a witness in one relation to checking knowledge of a witness in another (simpler) relation. Reductions of knowledge unify a growing class of modern techniques as well as provide a compositional framework to modularly reason about individual steps in complex arguments of knowledge. As a demonstration, we simplify and unify recursive arguments over linear algebraic statements by decomposing them as a sequence of reductions of knowledge. To do so, we develop the tensor reduction of knowledge, which generalizes the central reductive step common to many recursive arguments. Underlying the tensor reduction of knowledge is a new information-theoretic reduction, which, for any modules U, \(U_1\), and \(U_2\) such that \(U \cong U_1 \otimes U_2\), reduces the task of evaluating a homomorphism in U to evaluating a homomorphism in \(U_1\) and evaluating a homomorphism in \(U_2\).
Abhiram Kothapalli was supported by a fellowship from Protocol Labs, a gift from Bosch, NSF Grant No. 1801369, and the CONIX Research Center, one of six centers in JUMP, a Semiconductor Research Corporation program sponsored by DARPA. An extended version of this work is available on the Cryptology ePrint Archive [30].
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Notes
- 1.
We recommend Bitansky et al. [8, Remark 6.3] for details on such assumptions.
- 2.
The tensor relation can be formally understood as a ternary relation where any public parameters are ignored. This makes it compatible with the reductions of knowledge framework which works over ternary relations defined over public parameter, statement, and witness tuples.
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Acknowledgments
We thank Jonathan Bootle, Quang Dao, Vipul Goyal, Yael Tauman Kalai, Jonathan Lee, Srinath Setty, Elaine Shi, and Zoe Wellner for comments on earlier versions of this work.
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Kothapalli, A., Parno, B. (2023). Algebraic Reductions of Knowledge. In: Handschuh, H., Lysyanskaya, A. (eds) Advances in Cryptology – CRYPTO 2023. CRYPTO 2023. Lecture Notes in Computer Science, vol 14084. Springer, Cham. https://doi.org/10.1007/978-3-031-38551-3_21
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