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On the Computational Complexity of Minimal Cumulative Cost Graph Pebbling

Published 14 Sep 2016 in cs.CR and cs.CC | (1609.04449v2)

Abstract: We consider the computational complexity of finding a legal black pebbling of a DAG G=(V,E)G=(V,E) with minimum cumulative cost. A black pebbling is a sequence P0,…,Pt⊆VP_0,\ldots, P_t \subseteq V of sets of nodes which must satisfy the following properties: P0=∅P_0 = \emptyset (we start off with no pebbles on GG), sinks(G)⊆⋃j≤tPj\mathsf{sinks}(G) \subseteq \bigcup_{j \leq t} P_j (every sink node was pebbled at some point) and parents(Pi+1\Pi)⊆Pi\mathsf{parents}\big(P_{i+1}\backslash P_i\big) \subseteq P_i (we can only place a new pebble on a node vv if all of vv's parents had a pebble during the last round). The cumulative cost of a pebbling P0,P1,…,Pt⊆VP_0,P_1,\ldots, P_t \subseteq V is cc(P)=∣P1∣+…+∣Pt∣\mathsf{cc}(P) = | P_1| + \ldots + | P_t|. The cumulative pebbling cost is an especially important security metric for data-independent memory hard functions, an important primitive for password hashing. Thus, an efficient (approximation) algorithm would be an invaluable tool for the cryptanalysis of password hash functions as it would provide an automated tool to establish tight bounds on the amortized space-time cost of computing the function. We show that such a tool is unlikely to exist. In particular, we prove the following results. (1) It is $\texttt{NP}\mbox{-}\texttt{Hard}$ to find a pebbling minimizing cumulative cost. (2) The natural linear program relaxation for the problem has integrality gap O~(n)\tilde{O}(n), where nn is the number of nodes in GG. We conjecture that the problem is hard to approximate. (3) We show that a related problem, find the minimum size subset S⊆VS\subseteq V such that depth(G−S)≤d\textsf{depth}(G-S) \leq d, is also $\texttt{NP}\mbox{-}\texttt{Hard}$. In fact, under the unique games conjecture there is no (2−ϵ)(2-\epsilon)-approximation algorithm.

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