FairSwap

Dziembowski, Stefan; Eckey, Lisa; Faust, Sebastian

doi:10.1145/3243734.3243857

Cited by 156 publications

(53 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ϕ : σ → {0, 1}. For example, the FairSwap protocol implements such a mechanism by arithmetic circuits [12]. p are the payments made from a receiving agent B to a performing agent A as stated in the agreement.…”

Section: Contracts and Agreementsmentioning

confidence: 99%

“…For instance, the first iteration of this strategy is denoted by γ = 0; the next iteration by γ = 1. If we consider a one-shot game, whether the agent optimally commits a desired or undesired action is determined by (12). However, this does not consider the fact that once the agent performs an undesired action they need to work back up through the layers, with greater opportunity costs for their lockedup deposit, by performing ω − 1 desired actions to reach the highest layer again.…”

Section: Decision Boundary For Type T Rmentioning

confidence: 99%

“…If requesting is free in a protocol, boosting would be rational. Thus, to prevent griefing by B, cryptoeconomic protocols typically require a small amount of deposit [12] as friction. Since B also has an expected loss of interest on this deposit, this incurs a cost expressed by E[rD B ].…”

Section: Reputation Boostingmentioning

confidence: 99%

“…Further, a deposit can be used as insurance for tasks performed outside the underlying ledger, e.g. performing verifiable computations [20,30,48], cross-chain assets exchanges [53], or exchanging digital goods [12]. For such usage, the protocol is event-dependent, e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Balance is applicable to protocols that (i) are implemented on a decentralised ledger, (ii) use a deposit to prevent economically rational agents from performing undesired actions, (iii) require agents to over-collateralize due to at least one of the two identified sources of uncertainty, and (iv) verify interactions with agents through objective specifications ϕ. Suitable examples for integrating Balance are FairSwap [12], TrueBit [48], NOCUST [27], and XCLAIM [53].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Balance

Harz

Gudgeon

Gervais

et al. 2019

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security

View full text Add to dashboard Cite

Financial deposits are fundamental to the security of cryptoeconomic protocols as they serve as insurance against potential misbehaviour of agents. However, protocol designers and their agents face a trade-off when choosing the deposit size. While substantial deposits might increase the protocol security, for example by minimising the impact of adversarial behaviour or risks of currency fluctuations, locked-up capital incurs opportunity costs. Moreover, some protocols require over-collateralization in anticipation of future events and malicious intentions of agents. We present Balance, an application-agnostic system that reduces over-collateralization without compromising protocol security. In Balance, malicious agents receive no additional utility for cheating once their deposits are reduced. At the same time, honest and rational agents increase their utilities for behaving honestly as their opportunity costs for the locked-up deposits are reduced. Balance is a round-based mechanism in which agents need to continuously perform desired actions. Rather than treating agents' incentives and behaviour as ancillary, we explicitly model agents' utility, proving the conditions for incentive compatibility. Balance improves social welfare given a distribution of honest, rational, and malicious agents. Further, we integrate Balance with a cross-chain interoperability protocol, XCLAIM, reducing deposits by 10% while maintaining the same utility for behaving honestly. Our implementation allows any number of agents to be maintained for at most 55,287 gas (≈ USD 0.07) to update all agents' scores, and at a cost of 54,948 gas (≈ USD 0.07) to update the assignment of all agents to layers.

show abstract

Section: Contracts and Agreementsmentioning

confidence: 99%

Section: Decision Boundary For Type T Rmentioning

confidence: 99%

Section: Reputation Boostingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Balance

Harz

Gudgeon

Gervais

et al. 2019

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security

View full text Add to dashboard Cite

show abstract

Staged data delivery protocol: A blockchain‐based two‐stage protocol for non‐repudiation data delivery

Wang

Liu

2021

Concurrency and Computation

View full text Add to dashboard Cite

For many years, non‐repudiation in data delivery has not been satisfactorily achieved due to the difficulty of supervising delivery behavior. Existing fair protocols are still not entirely free of third parties who are usually not as trustworthy as expected. Moreover, most of them are built on complex encryption schemes, resulting in inefficiencies when handling large chunks of data and non‐exchanged data sharing. To be able to deliver data without third parties and repudiation, we propose the staged data delivery protocol (SDDP) that integrates fair data delivery into Blockchain consensus processes. SDDP confirms transactions of data delivery in a cascading manner where nodes sign on each transaction one after another. It consists of two stages, in which neither party will have a considerable advantage over the other. In this way, SDDP enables non‐repudiation of directly delivering large chunks of data through an understandable communication strategy; and the Blockchain network replaces third parties to preserve an immutable history of data delivery activities. The results of extensive evaluations show that SDDP is admissible for dealing with fair data delivery on the basis of its good qualities and performance.

show abstract

Blockchain‐based privacy‐preserving valet parking for self‐driving vehicles

Fang

Zhao

Zhu

et al. 2021

Trans Emerging Tel Tech

View full text Add to dashboard Cite

The valet parking provides convenience for users and thus is becoming increasingly popular nowadays. However, this valet parking service incurs the risks of location information leakage and vehicle theft. To address these issues, in this paper, we propose a blockchain‐based privacy‐preserving valet parking protocol (B‐park) for self‐driving vehicles. The protocol guarantees the privacy of users while providing transparency and auditability of the valet parking service. We define the system model of privacy‐preserving valet parking for self‐driving vehicles in blockchain setting and formalize its security properties including anonymity, conversion blindness, nonframeability, and traceability. We provide a concrete construction of B‐park as well based on a new variant of Pointcheval‐Sanders group signature. Then, we demonstrate that our protocol is secure in the random oracle model. Finally, we evaluate the performance of B‐park to demonstrate its effectiveness and practicability.

show abstract

FairSwap

Cited by 156 publications

References 18 publications

Balance

Balance

Staged data delivery protocol: A blockchain‐based two‐stage protocol for non‐repudiation data delivery

Blockchain‐based privacy‐preserving valet parking for self‐driving vehicles

Contact Info

Product

Resources

About