17,283 research outputs found
Fair Computation with Rational Players
We consider the problem of fair multiparty computation, where fairness means (informally) that all parties should learn the correct output. A seminal result of Cleve (STOC 1986) shows that fairness is, in general, impossible to achieve if a majority of the parties is malicious. Here, we treat all parties as rational and seek to understand what can be done.
Asharov et al. (Eurocrypt 2011) showed impossibility of rational fair computation in the two-party setting, for a particular function and a particular choice of utilities. We observe, however, that in their setting the parties have no strict incentive to compute the function even in an ideal world where fairness is guaranteed. Revisiting the problem, we show that rational fair computation is possible, for arbitrary functions, as long as the parties have a strict incentive to compute the function in an ideal world where fairness is guaranteed. Our results extend to more general utility functions that do not directly correspond to fairness, as well as to the multi-party setting. Our work thus shows a new setting in which game-theoretic considerations can be used to circumvent a cryptographic impossibility result
Robust Coin Flipping
Alice seeks an information-theoretically secure source of private random
data. Unfortunately, she lacks a personal source and must use remote sources
controlled by other parties. Alice wants to simulate a coin flip of specified
bias , as a function of data she receives from sources; she seeks
privacy from any coalition of of them. We show: If , the
bias can be any rational number and nothing else; if , the bias
can be any algebraic number and nothing else. The proof uses projective
varieties, convex geometry, and the probabilistic method. Our results improve
on those laid out by Yao, who asserts one direction of the case in his
seminal paper [Yao82]. We also provide an application to secure multiparty
computation.Comment: 22 pages, 1 figur
A Rational Approach to Cryptographic Protocols
This work initiates an analysis of several cryptographic protocols from a
rational point of view using a game-theoretical approach, which allows us to
represent not only the protocols but also possible misbehaviours of parties.
Concretely, several concepts of two-person games and of two-party cryptographic
protocols are here combined in order to model the latters as the formers. One
of the main advantages of analysing a cryptographic protocol in the game-theory
setting is the possibility of describing improved and stronger cryptographic
solutions because possible adversarial behaviours may be taken into account
directly. With those tools, protocols can be studied in a malicious model in
order to find equilibrium conditions that make possible to protect honest
parties against all possible strategies of adversaries
FairLedger: A Fair Blockchain Protocol for Financial Institutions
Financial institutions are currently looking into technologies for
permissioned blockchains. A major effort in this direction is Hyperledger, an
open source project hosted by the Linux Foundation and backed by a consortium
of over a hundred companies. A key component in permissioned blockchain
protocols is a byzantine fault tolerant (BFT) consensus engine that orders
transactions. However, currently available BFT solutions in Hyperledger (as
well as in the literature at large) are inadequate for financial settings; they
are not designed to ensure fairness or to tolerate selfish behavior that arises
when financial institutions strive to maximize their own profit.
We present FairLedger, a permissioned blockchain BFT protocol, which is fair,
designed to deal with rational behavior, and, no less important, easy to
understand and implement. The secret sauce of our protocol is a new
communication abstraction, called detectable all-to-all (DA2A), which allows us
to detect participants (byzantine or rational) that deviate from the protocol,
and punish them. We implement FairLedger in the Hyperledger open source
project, using Iroha framework, one of the biggest projects therein. To
evaluate FairLegder's performance, we also implement it in the PBFT framework
and compare the two protocols. Our results show that in failure-free scenarios
FairLedger achieves better throughput than both Iroha's implementation and PBFT
in wide-area settings
Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems
Collaboration may be understood as the execution of coordinated tasks (in the
most general sense) by groups of users, who cooperate for achieving a common
goal. Collaboration is a fundamental assumption and requirement for the correct
operation of many communication systems. The main challenge when creating
collaborative systems in a decentralized manner is dealing with the fact that
users may behave in selfish ways, trying to obtain the benefits of the tasks
but without participating in their execution. In this context, Game Theory has
been instrumental to model collaborative systems and the task allocation
problem, and to design mechanisms for optimal allocation of tasks. In this
paper, we revise the classical assumptions and propose a new approach to this
problem. First, we establish a system model based on heterogenous nodes (users,
players), and propose a basic distributed mechanism so that, when a new task
appears, it is assigned to the most suitable node. The classical technique for
compensating a node that executes a task is the use of payments (which in most
networks are hard or impossible to implement). Instead, we propose a
distributed mechanism for the optimal allocation of tasks without payments. We
prove this mechanism to be robust event in the presence of independent selfish
or rationally limited players. Additionally, our model is based on very weak
assumptions, which makes the proposed mechanisms susceptible to be implemented
in networked systems (e.g., the Internet).Comment: 23 pages, 5 figures, 3 algorithm
Decision-Making: A Neuroeconomic Perspective
This article introduces and discusses from a philosophical point of view the nascent field of neuroeconomics, which is the study of neural mechanisms involved in decision-making and their economic significance. Following a survey of the ways in which decision-making is usually construed in philosophy, economics and psychology, I review many important findings in neuroeconomics to show that they suggest a revised picture of decision-making and ourselves as choosing agents. Finally, I outline a neuroeconomic account of irrationality
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