Calvin Lab Room 116
Average-Case Fine-Grained Hardness
"We present functions that are hard to compute on average for algorithms running in some fixed polynomial time, assuming widely-conjectured worst-case hardness for Orthogonal Vectors (OV),
3SU, and All-Pairs Shortest Paths (APSP). Using the same techniques we also obtain a conditional average-case time hierarchy of functions. Based on the average-case hardness and the algebraic structure we achieve for our functions, we outline the construction of a Proof of Work scheme and discuss possible approaches to constructing fine-grained One-Way Functions. We also show how our reductions make conjectures regarding the worst-case hardness of the problems we reduce from (and consequently the Strong Exponential Time Hypothesis) heuristically falsifiable in a sense similar to that of (Naor, CRYPTO 2003). We will discuss many open problems that these results reveal, including pseudorandomness and derandomization in the fine-grained world." We will discuss many open problems that these results reveal, including pseudorandomness and derandomization in the fine-grained world."
Joint with Marshall Ball, Alon Rosen, and Prashant Nalini Vasudevan.