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Hiding Cliques for Cryptographic Security
Authors:Ari Juels  Marcus Peinado
Affiliation:(1) RSA Laboratories, 20 Crosby Dr., Bedford, MA 01730, USA;(2) Microsoft, One Microsoft Way, Redmond, WA 98052, USA
Abstract:We demonstrate how a well studied combinatorial optimizationproblem may be used as a new cryptographic primitive. The problemin question is that of finding a "large" clique in a randomgraph. While the largest clique in a random graph with nvertices and edge probability p is very likely tobe of size about 
$$2log _{{raise0.7exhbox{$1$} !mathord{left/ {vphantom {1 p}}right.kern-nulldelimiterspace}!lower0.7exhbox{$p$}}} n$$
, it is widely conjecturedthat no polynomial-time algorithm exists which finds a cliqueof size 
$$ geqslant (1 + varepsilon )log _{{raise0.7exhbox{$1$} !mathord{left/ {vphantom {1 p}}right.kern-nulldelimiterspace}!lower0.7exhbox{$p$}}} n$$
with significantprobability for any constant isin > 0. We presenta very simple method of exploiting this conjecture by ldquohidingrdquolarge cliques in random graphs. In particular, we show that ifthe conjecture is true, then when a large clique—of size,say, 
$$(1 + 2varepsilon )log _{{raise0.7exhbox{$1$} !mathord{left/ {vphantom {1 p}}right.kern-nulldelimiterspace}!lower0.7exhbox{$p$}}} n{mathbf{---}}$$
is randomlyinserted (ldquohiddenrdquo) in a random graph, finding a clique ofsize 
$$ geqslant (1 + varepsilon )log _{{raise0.7exhbox{$1$} !mathord{left/ {vphantom {1 p}}right.kern-nulldelimiterspace}!lower0.7exhbox{$p$}}} n$$
remains hard.Our analysis also covers the case of high edge probabilitieswhich allows us to insert cliques of size up to 
$$n^{{raise0.7exhbox{$1$} !mathord{left/ {vphantom {1 {4 - varepsilon }}}right.kern-nulldelimiterspace}!lower0.7exhbox{${4 - varepsilon }$}}} (varepsilon >0)$$
. Our result suggests several cryptographicapplications, such as a simple one-way function.
Keywords:Graph-based crypto systems  random graphs  cliques
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