ROYALE: A Framework for Universally Composable Card Games with Financial Rewards and Penalties Enforcement

While many tailor made card game protocols are known, the vast majority of those suffer from three main issues: lack of mechanisms for distributing financial rewards and punishing cheaters, lack of composability guarantees and little flexibility, focusing on the specific game of poker. Even though folklore holds that poker protocols can be used to play any card game, this conjecture remains unproven and, in fact, does not hold for a number of protocols (including recent results). We both tackle the problem of constructing protocols for general card games and initiate a treatment of such protocols in the Universal Composability (UC) framework, introducing an ideal functionality that captures general card games constructed from a set of core card operations. Based on this formalism, we introduce Royale, the first UC-secure general card games which supports financial rewards/penalties enforcement. We remark that Royale also yields the first UC-secure poker protocol. Interestingly, Royale performs better than most previous works (that do not have composability guarantees), which we highlight through a detailed concrete complexity analysis and benchmarks from a prototype implementation

A Fast Mental Poker Protocol

Abstract. We present a fast and secure mental poker protocol. It is twice as fast as Barnett-Smart\u27s and Castellà-Roca\u27s protocols. This protocol is provably secure under DDH assumption

Kaleidoscope: An Efficient Poker Protocol with Payment Distribution and Penalty Enforcement

The research on secure poker protocols without trusted intermediaries has a long history that dates back to modern cryptography\u27s infancy. Two main challenges towards bringing it into real-life are enforcing the distribution of the rewards, and penalizing misbehaving/aborting parties. Using recent advances on cryptocurrencies and blockchain technologies, Andrychowicz et al. (IEEE S\&P 2014 and FC 2014 BITCOIN Workshop) were able to address those problems. Improving on these results, Kumaresan et al. (CCS 2015) and Bentov et al. (ASIACRYPT 2017) proposed specific purpose poker protocols that made significant progress towards meeting the real-world deployment requirements. However, their protocols still lack either efficiency or a formal security proof in a strong model. Specifically, the work of Kumaresan et al. relies on Bitcoin and simple contracts, but is not very efficient as it needs numerous interactions with the cryptocurrency network as well as a lot of collateral. Bentov et al. achieve further improvements by using stateful contracts and off-chain execution: they show a solution based on general multiparty computation that has a security proof in a strong model, but is also not very efficient. Alternatively, it proposes to use tailor-made poker protocols as a building block to improve the efficiency. However, a security proof is unfortunately still missing for the latter case: the security properties the tailor-made protocol would need to meet were not even specified, let alone proven to be met by a given protocol. Our solution closes this undesirable gap as it concurrently: (1) enforces the rewards\u27 distribution; (2) enforces penalties on misbehaving parties; (3) has efficiency comparable to the tailor-made protocols; (4) has a security proof in a simulation-based model of security. Combining techniques from the above works, from tailor-made poker protocols and from efficient zero-knowledge proofs for shuffles, and performing optimizations, we obtain a solution that satisfies all four desired criteria and does not incur a big burden on the blockchain

Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contract Execution

Smart contracts are applications that execute on blockchains. Today they manage billions of dollars in value and motivate visionary plans for pervasive blockchain deployment. While smart contracts inherit the availability and other security assurances of blockchains, however, they are impeded by blockchains' lack of confidentiality and poor performance. We present Ekiden, a system that addresses these critical gaps by combining blockchains with Trusted Execution Environments (TEEs). Ekiden leverages a novel architecture that separates consensus from execution, enabling efficient TEE-backed confidentiality-preserving smart-contracts and high scalability. Our prototype (with Tendermint as the consensus layer) achieves example performance of 600x more throughput and 400x less latency at 1000x less cost than the Ethereum mainnet. Another contribution of this paper is that we systematically identify and treat the pitfalls arising from harmonizing TEEs and blockchains. Treated separately, both TEEs and blockchains provide powerful guarantees, but hybridized, though, they engender new attacks. For example, in naive designs, privacy in TEE-backed contracts can be jeopardized by forgery of blocks, a seemingly unrelated attack vector. We believe the insights learned from Ekiden will prove to be of broad importance in hybridized TEE-blockchain systems

Logical and deep learning methods for temporal reasoning

In this thesis, we study logical and deep learning methods for the temporal reasoning of reactive systems. In Part I, we determine decidability borders for the satisfiability and realizability problem of temporal hyperproperties. Temporal hyperproperties relate multiple computation traces to each other and are expressed in a temporal hyperlogic. In particular, we identify decidable fragments of the highly expressive hyperlogics HyperQPTL and HyperCTL*. As an application, we elaborate on an enforcement mechanism for temporal hyperproperties. We study explicit enforcement algorithms for specifications given as formulas in universally quantified HyperLTL. In Part II, we train a (deep) neural network on the trace generation and realizability problem of linear-time temporal logic (LTL). We consider a method to generate large amounts of additional training data from practical specification patterns. The training data is generated with classical solvers, which provide one of many possible solutions to each formula. We demonstrate that it is sufficient to train on those particular solutions such that the neural network generalizes to the semantics of the logic. The neural network can predict solutions even for formulas from benchmarks from the literature on which the classical solver timed out. Additionally, we show that it solves a significant portion of problems from the annual synthesis competition (SYNTCOMP) and even out-of-distribution examples from a recent case study.Diese Arbeit befasst sich mit logischen Methoden und mehrschichtigen Lernmethoden für das zeitabhängige Argumentieren über reaktive Systeme. In Teil I werden die Grenzen der Entscheidbarkeit des Erfüllbarkeits- und des Realisierbarkeitsproblem von temporalen Hypereigenschaften bestimmt. Temporale Hypereigenschaften setzen mehrere Berechnungsspuren zueinander in Beziehung und werden in einer temporalen Hyperlogik ausgedrückt. Insbesondere werden entscheidbare Fragmente der hochexpressiven Hyperlogiken HyperQPTL und HyperCTL* identifiziert. Als Anwendung wird ein Enforcement-Mechanismus für temporale Hypereigenschaften erarbeitet. Explizite Enforcement-Algorithmen für Spezifikationen, die als Formeln in universell quantifiziertem HyperLTL angegeben werden, werden untersucht. In Teil II wird ein (mehrschichtiges) neuronales Netz auf den Problemen der Spurgenerierung und Realisierbarkeit von Linear-zeit Temporallogik (LTL) trainiert. Es wird eine Methode betrachtet, um aus praktischen Spezifikationsmustern große Mengen zusätzlicher Trainingsdaten zu generieren. Die Trainingsdaten werden mit klassischen Solvern generiert, die zu jeder Formel nur eine von vielen möglichen Lösungen liefern. Es wird gezeigt, dass es ausreichend ist, an diesen speziellen Lösungen zu trainieren, sodass das neuronale Netz zur Semantik der Logik generalisiert. Das neuronale Netz kann Lösungen sogar für Formeln aus Benchmarks aus der Literatur vorhersagen, bei denen der klassische Solver eine Zeitüberschreitung hatte. Zusätzlich wird gezeigt, dass das neuronale Netz einen erheblichen Teil der Probleme aus dem jährlichen Synthesewettbewerb (SYNTCOMP) und sogar Beispiele außerhalb der Distribution aus einer aktuellen Fallstudie lösen kann

Dropout-Tolerant TTP-Free Mental Poker

Abstract. There is a broad literature on distributed card games over communications networks, collectively known as mental poker. Likein any distributed protocol, avoiding the need for a Trusted Third Party (TTP) in mental poker is highly desirable, because really trusted TTPs are not always available and seldom free. This paper deals with the player dropout problem in mental poker without a TTP. A solution based on zero-knowledge proofs is proposed. While staying TTP-free, our proposal allows the game to continue after player dropout

A COMPARISON BETWEEN MOTIVATIONS AND PERSONALITY TRAITS IN RELIGIOUS TOURISTS AND CRUISE SHIP TOURISTS

The purpose of this paper is to analyze the motivations and the personality traits that characterize tourists who choose religious travels versus cruises. Participating in the research were 683 Italian tourists (345 males and 338 females, age range 18–63 years); 483 who went to a pilgrimage travel and 200 who chose a cruise ship in the Mediterranean Sea. Both groups of tourists completed the Travel Motivation Scale and the Big Five Questionnaire. Results show that different motivations and personality traits characterize the different types of tourists and, further, that motivations for traveling are predicted by specific —some similar, other divergent— personality trait