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        <datestamp>2024-03-06T10:39:16Z</datestamp>
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          <dc:title>Towards Human Computable Passwords</dc:title>
          <dc:creator>Blocki, Jeremiah</dc:creator>
          <dc:creator>Blum, Manuel</dc:creator>
          <dc:creator>Datta, Anupam</dc:creator>
          <dc:creator>Vempala, Santosh</dc:creator>
          <dc:subject>Passwords</dc:subject>
          <dc:subject>Cognitive Authentication</dc:subject>
          <dc:subject>Human Computation</dc:subject>
          <dc:subject>Planted Constraint Satisfaction Problem</dc:subject>
          <dc:subject>Statistical Dimension</dc:subject>
          <dc:description>An interesting challenge for the cryptography community is to design authentication protocols that are so simple that a human can execute them &#13;
without relying on a fully trusted computer. We propose several candidate authentication protocols for a setting in which the human user can &#13;
only receive assistance from a semi-trusted computer - a computer that stores information and performs computations correctly &#13;
but does not provide confidentiality. Our schemes use a semi-trusted computer to store and display public challenges C_i\in[n]^k. &#13;
The human user memorizes a random secret mapping \sigma:[n]\rightarrow \mathbb{Z}_d and authenticates by computing responses f(\sigma(C_i)) to &#13;
a sequence of public challenges where f:\mathbb{Z}_d^k\rightarrow \mathbb{Z}_d is a function that is easy for the human to evaluate. We prove &#13;
that any statistical adversary needs to sample m=\tilde{\Omega}\paren{n^{s(f)}} challenge-response pairs to recover \sigma, for a security &#13;
parameter s(f) that depends on two key properties of f. Our lower bound generalizes recent results of Feldman et al. [Feldman'15]&#13;
who proved analogous results for the special case d=2. To obtain our results, we apply the general hypercontractivity theorem [O'Donnell'14]&#13;
to lower bound the statistical dimension of the distribution over challenge-response pairs induced by f and \sigma. &#13;
Our statistical dimension lower bounds apply to arbitrary functions f:\mathbb{Z}_d^k\rightarrow \mathbb{Z}_d (not just to functions that &#13;
are easy for a human to evaluate). As an application, we propose a family of human computable password &#13;
functions f_{k_1,k_2} in which the user needs to perform 2k_1+2k_2+1 primitive operations (e.g., adding two digits or remembering a &#13;
secret value \sigma(i)), and we show that s(f) = \min{k_1+1, (k_2+1)/2}. For these schemes, we prove that forging passwords is &#13;
equivalent to recovering the secret mapping. Thus, our human computable password schemes can maintain strong security guarantees even after &#13;
an adversary has observed the user login to many different accounts.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Jeremiah Blocki and Manuel Blum and Anupam Datta and Santosh Vempala</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 67, 8th Innovations in Theoretical Computer Science Conference (ITCS 2017)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.ITCS.2017.10</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-81847</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2017.10</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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