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Affine Determinant Programs: A Framework for Obfuscation and Witness Encryption

James Bartusek, Yuval Ishai, Aayush Jain, Fermi Ma, Amit Sahai, Mark Zhandry

2020DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)24 citationsDOIOpen Access PDF

Abstract

An affine determinant program ADP: {0,1}^n → {0,1} is specified by a tuple (A,B_1,…,B_n) of square matrices over ?_q and a function Eval: ?_q → {0,1}, and evaluated on x ∈ {0,1}^n by computing Eval(det(A + ∑_{i∈[n]} x_i B_i)). In this work, we suggest ADPs as a new framework for building general-purpose obfuscation and witness encryption. We provide evidence to suggest that constructions following our ADP-based framework may one day yield secure, practically feasible obfuscation. As a proof-of-concept, we give a candidate ADP-based construction of indistinguishability obfuscation (i?) for all circuits along with a simple witness encryption candidate. We provide cryptanalysis demonstrating that our schemes resist several potential attacks, and leave further cryptanalysis to future work. Lastly, we explore practically feasible applications of our witness encryption candidate, such as public-key encryption with near-optimal key generation.

Topics & Concepts

ObfuscationEncryptionComputer scienceWitnessAffine transformationTheoretical computer scienceCryptanalysisFunctional encryptionPublic-key cryptographyComputer securityMathematicsProgramming languageCiphertextPure mathematicsComplexity and Algorithms in GraphsQuantum Computing Algorithms and ArchitectureCryptographic Implementations and Security
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