谛听Diting Lab

Crypto & Blockchain · Mon, Oct 26, 2026

Bitcoin, Ethereum, stablecoins, DeFi, smart contracts, scaling and consensus.

arXiv cs.CR · cs.DC

Merkle-Tree-Based Verifiable Public Data Auditing for Cloud Object Storage Using Smart Contracts

In briefMerkle-tree-based public auditing of cloud object storage using Ethereum smart contracts

SummaryThe paper proposes a public auditing system for cloud object storage in which the hash and name of each object form leaves of a Merkle tree. Only the tree's root is stored in an Ethereum smart contract, while the objects remain with the provider. An auditor downloads an object and checks it against the stored root using a short Merkle proof to mark it as intact, modified or missing. In experiments, the system detected all single and multiple modifications and deletions with no false alarms, and checking one object took about 10 ms regardless of dataset size.

Siri Reddy Tadi, K. Gangadhara Rao, M. Venu Gopalachari et al.

★★★★☆ Notable
IACR ePrint Cryptographic protocols

Isotaxis: Optimal Asynchronous Byzantine Consensus with Ordering Linearizability

In briefIsotaxis: Optimal Asynchronous Byzantine Consensus with Ordering Linearizability

SummaryThis paper presents Isotaxis, a state machine replication protocol with ordering linearizability, designed to resist adversaries who manipulate transaction order, such as in MEV attacks. Its communication complexity is O(nℓ+λn²), which is optimal when ℓ≥λn, and it is described as the first asynchronous protocol to achieve ordering linearizability. Experiments on up to 100 EC2 instances show it outperforms Pompē at all tested scales from 4 to 100 nodes.

WhyFirst asynchronous SMR achieving ordering linearizability with optimal communication and Byzantine resilience, validated by experiments on 4 to 100 nodes.

Vincent Gramoli, Zhenliang Lu, Qiang Tang et al.

arXiv stat.ML · cs.LG

Beyond Wasserstein Proximity: Finding Better Transfer Sources

In briefBeyond Wasserstein Proximity: Finding Better Transfer Sources

SummaryThis paper examines how to choose pretraining data sources for transfer, arguing that the most similar data is not always the most useful. The authors test five-day volatility forecasting for ten Binance spot cryptocurrencies across six model families. Selecting farther Gaussian-Wasserstein sources improved persistence-relative skill for several models. The findings are presented as exploratory results on a fixed historical dataset.

Gordei Verbii, Georgii Killinkarov, Vladimir Yafarov

arXiv stat.AP · cs.CR · stat.ME

Performance Guarantees for Permissionless Lending

In briefPerformance guarantees for a permissionless lending protocol

SummaryThis paper proposes a lending protocol that the authors say carries far fewer risks than pool-based protocols such as Aave and Compound. Lenders and borrowers make competing interest-rate offers, and loans carry a fixed rate for their full term. The authors model collateral value as a random walk and use characteristic functions and Fourier inversion to derive exact expressions for liquidation and repayment-shortfall probabilities, illustrated with Bitcoin collateral.

Nanqiao Wang, Jia Yuan Yu