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Datta, Pratish; Komargodski, Ilan; Waters, Brent (, Eurocrypt 2023)
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Ephraim, Naomi; Freitag, Cody; Komargodski, Ilan; Pass, Rafael (, Journal of the ACM)We introduce the notion of a Succinct Parallelizable Argument of Knowledge (SPARK). This is an argument of knowledge with the following three efficiency properties for computing and proving a (non-deterministic, polynomial time) parallel RAM computation that can be computed in parallel time T with at most p processors: — The prover’s (parallel) running time is \( T + \mathrm{poly}\hspace{-2.0pt}\log (T \cdot p) \) . (In other words, the prover’s running time is essentially T for large computation times!) — The prover uses at most \( p \cdot \mathrm{poly}\hspace{-2.0pt}\log (T \cdot p) \) processors. — The communication and verifier complexity are both \( \mathrm{poly}\hspace{-2.0pt}\log (T \cdot p) \) . The combination of all three is desirable, as it gives a way to leverage a moderate increase in parallelism in favor of near-optimal running time. We emphasize that even a factor two overhead in the prover’s parallel running time is not allowed. Our main contribution is a generic construction of SPARKs from any succinct argument of knowledge where the prover’s parallel running time is \( T \cdot \mathrm{poly}\hspace{-2.0pt}\log (T \cdot p) \) when using p processors, assuming collision-resistant hash functions. When suitably instantiating our construction, we achieve a four-round SPARK for any parallel RAM computation assuming only collision resistance. Additionally assuming the existence of a succinct non-interactive argument of knowledge (SNARK), we construct a non-interactive SPARK that also preserves the space complexity of the underlying computation up to \( \mathrm{poly}\hspace{-2.0pt}\log (T\cdot p) \) factors. We also show the following applications of non-interactive SPARKs. First, they immediately imply delegation protocols with near optimal prover (parallel) running time. This, in turn, gives a way to construct verifiable delay functions (VDFs) from any sequential function. When the sequential function is also memory-hard, this yields the first construction of a memory-hard VDF.more » « less
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Ghazi, Badih; Komargodski, Ilan; Kothari, Pravesh K.; Sudan, Madhu (, computational complexity)
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