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Documents authored by Velner, Yaron

Document
DOI: 10.4230/LIPIcs.CONCUR.2018.11
Ergodic Mean-Payoff Games for the Analysis of Attacks in Crypto-Currencies

Authors: Krishnendu Chatterjee, Amir Kafshdar Goharshady, Rasmus Ibsen-Jensen, and Yaron Velner

Published in: LIPIcs, Volume 118, 29th International Conference on Concurrency Theory (CONCUR 2018)

Abstract
Crypto-currencies are digital assets designed to work as a medium of exchange, e.g., Bitcoin, but they are susceptible to attacks (dishonest behavior of participants). A framework for the analysis of attacks in crypto-currencies requires (a) modeling of game-theoretic aspects to analyze incentives for deviation from honest behavior; (b) concurrent interactions between participants; and (c) analysis of long-term monetary gains. Traditional game-theoretic approaches for the analysis of security protocols consider either qualitative temporal properties such as safety and termination, or the very special class of one-shot (stateless) games. However, to analyze general attacks on protocols for crypto-currencies, both stateful analysis and quantitative objectives are necessary. In this work our main contributions are as follows: (a) we show how a class of concurrent mean-payoff games, namely ergodic games, can model various attacks that arise naturally in crypto-currencies; (b) we present the first practical implementation of algorithms for ergodic games that scales to model realistic problems for crypto-currencies; and (c) we present experimental results showing that our framework can handle games with thousands of states and millions of transitions.
Cite as

Krishnendu Chatterjee, Amir Kafshdar Goharshady, Rasmus Ibsen-Jensen, and Yaron Velner. Ergodic Mean-Payoff Games for the Analysis of Attacks in Crypto-Currencies. In 29th International Conference on Concurrency Theory (CONCUR 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 118, pp. 11:1-11:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{chatterjee_et_al:LIPIcs.CONCUR.2018.11,
  author =	{Chatterjee, Krishnendu and Kafshdar Goharshady, Amir and Ibsen-Jensen, Rasmus and Velner, Yaron},
  title =	{{Ergodic Mean-Payoff Games for the Analysis of Attacks in Crypto-Currencies}},
  booktitle =	{29th International Conference on Concurrency Theory (CONCUR 2018)},
  pages =	{11:1--11:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-087-3},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{118},
  editor =	{Schewe, Sven and Zhang, Lijun},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2018.11},
  URN =		{urn:nbn:de:0030-drops-95497},
  doi =		{10.4230/LIPIcs.CONCUR.2018.11},
  annote =	{Keywords: Crypto-currency, Quantitative Verification, Mean-payoff Games}
}
Document
DOI: 10.4230/LIPIcs.CONCUR.2016.9
Minimizing Expected Cost Under Hard Boolean Constraints, with Applications to Quantitative Synthesis

Authors: Shaull Almagor, Orna Kupferman, and Yaron Velner

Published in: LIPIcs, Volume 59, 27th International Conference on Concurrency Theory (CONCUR 2016)

Abstract
In Boolean synthesis, we are given an LTL specification, and the goal is to construct a transducer that realizes it against an adversarial environment. Often, a specification contains both Boolean requirements that should be satisfied against an adversarial environment, and multi-valued components that refer to the quality of the satisfaction and whose expected cost we would like to minimize with respect to a probabilistic environment. In this work we study, for the first time, mean-payoff games in which the system aims at minimizing the expected cost against a probabilistic environment, while surely satisfying an omega-regular condition against an adversarial environment. We consider the case the omega-regular condition is given as a parity objective or by an LTL formula. We show that in general, optimal strategies need not exist, and moreover, the limit value cannot be approximated by finite-memory strategies. We thus focus on computing the limit-value, and give tight complexity bounds for synthesizing epsilon-optimal strategies for both finite-memory and infinite-memory strategies. We show that our game naturally arises in various contexts of synthesis with Boolean and multi-valued objectives. Beyond direct applications, in synthesis with costs and rewards to certain behaviors, it allows us to compute the minimal sensing cost of omega-regular specifications -- a measure of quality in which we look for a transducer that minimizes the expected number of signals that are read from the input.
Cite as

Shaull Almagor, Orna Kupferman, and Yaron Velner. Minimizing Expected Cost Under Hard Boolean Constraints, with Applications to Quantitative Synthesis. In 27th International Conference on Concurrency Theory (CONCUR 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 59, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{almagor_et_al:LIPIcs.CONCUR.2016.9,
  author =	{Almagor, Shaull and Kupferman, Orna and Velner, Yaron},
  title =	{{Minimizing Expected Cost Under Hard Boolean Constraints, with Applications to Quantitative Synthesis}},
  booktitle =	{27th International Conference on Concurrency Theory (CONCUR 2016)},
  pages =	{9:1--9:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-017-0},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{59},
  editor =	{Desharnais, Jos\'{e}e and Jagadeesan, Radha},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2016.9},
  URN =		{urn:nbn:de:0030-drops-61689},
  doi =		{10.4230/LIPIcs.CONCUR.2016.9},
  annote =	{Keywords: Stochastic and Quantitative Synthesis, Mean Payoff Games, Sensing.}
}
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