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        <identifier>oai:drops-oai.dagstuhl.de:7093</identifier>
        <datestamp>2024-03-06T10:39:31Z</datestamp>
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          <dc:title>Non-Determinism in Byzantine Fault-Tolerant Replication</dc:title>
          <dc:creator>Cachin, Christian</dc:creator>
          <dc:creator>Schubert, Simon</dc:creator>
          <dc:creator>Vukolic, Marko</dc:creator>
          <dc:subject>Blockchain</dc:subject>
          <dc:subject>atomic broadcast</dc:subject>
          <dc:subject>consensus</dc:subject>
          <dc:subject>distributed cryptography</dc:subject>
          <dc:subject>verifiable random functions</dc:subject>
          <dc:description>Service replication distributes an application over many processes for tolerating faults, attacks, and misbehavior among a subset of the processes. With the recent interest in blockchain technologies, distributed execution of one logical application has become a prominent topic. The established state-machine replication paradigm inherently requires the application to be deterministic. This paper distinguishes three models for dealing with non-determinism in replicated services, where some processes are subject to faults and arbitrary behavior (so-called Byzantine faults): first, the modular case that does not require any changes to the potentially non-deterministic application (and neither access to its internal data); second, master-slave solutions, where ties are broken by a leader and the other processes validate the choices of the leader; and finally, applications that use cryptography and secret keys. Cryptographic operations and secrets must be treated specially because they require strong randomness to satisfy their goals.&#13;
&#13;
The paper also introduces two new protocols. First, Protocol Sieve uses the modular approach and filters out non-deterministic operations in an application. It ensures that all correct processes produce the same outputs and that their internal states do not diverge. A second protocol, called Mastercrypt, implements cryptographically secure randomness generation with a verifiable random function and is appropriate for most situations in which cryptographic secrets are involved. All protocols are described in a generic way and do not assume a particular implementation of the underlying consensus primitive.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Christian Cachin and Simon Schubert and Marko Vukolic</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 70, 20th International Conference on Principles of Distributed Systems (OPODIS 2016)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.OPODIS.2016.24</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-70935</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2016.24</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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