惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Hugging Face - Blog
Hugging Face - Blog
Vercel News
Vercel News
C
Check Point Blog
G
Google Developers Blog
博客园 - 司徒正美
量子位
Engineering at Meta
Engineering at Meta
S
SegmentFault 最新的问题
Google DeepMind News
Google DeepMind News
F
Fortinet All Blogs
A
About on SuperTechFans
美团技术团队
D
DataBreaches.Net
Stack Overflow Blog
Stack Overflow Blog
Jina AI
Jina AI
Y
Y Combinator Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Apple Machine Learning Research
Apple Machine Learning Research
J
Java Code Geeks
MongoDB | Blog
MongoDB | Blog
人人都是产品经理
人人都是产品经理
H
Hackread – Cybersecurity News, Data Breaches, AI and More
The Cloudflare Blog
U
Unit 42

Cryptology ePrint Archive

Formalizing and Strengthening the Security Proof of NTOR Verifiable Anomaly and Similarity Detection Using Matrix Profile in Private Time-series Adaptor Signature Schemes with Deniable Presignatures Privacy Coins Under Viewing Key Compromise Adaptively-Secure Flexible and Identity-Based Broadcast Encryption from Decomposed LWE MERIDIAN: A Toroid-Inspired Permutation Block Cipher for Constrained Environments PPML Is More Vulnerable to Cryptanalytic Extraction Attacks Toward Practical Fair Data Exchange: Eliminating In-Circuit Public-Key Operations Fault Injection Attacks Against zkSTARKs Scale, Round, Break: Simple Leakage Attacks on Secret Sharing Schemes Private Delegation of (Non-)Membership Proof Updates in Cryptographic Accumulators Beyond Binary: crosscorrelation of Cubic, Quartic and Quintic Character Sequences ZEE200: Zero Knowledge for Everything and Everyone @ 200 KHz A Post-Quantum Accountable Sanitizable Signature Scheme Based on Unbalanced Oil and Vinegar Better Usability: Leakage-Resistant AEADs from Single-length Blockciphers TieredOMap: Skewness-Aware Oblivious Map From Rerandtopia to Interceptopia, the Anamorphic Encryption Saga Rises Non-Adaptive Programmable PRFs and Applications to Stacked Garbling Practical Post-Quantum Secure Publicly Verifiable Secret Sharing and Applications Mosaic: Practical Malicious Security for Garbled Circuits on Bitcoin Efficient Bootstrapping of Matrices in FHE Decomposing Multiplication: A Vertical Packing Approach for Faster TFHE Formal Verification, Integration and Physical Evaluation of Prime-Field Masking on Silicon New Techniques for Communication-Efficient Secure Comparison Protocols Pairing-Based Verifiable Shuffles with Logarithmic-Size Proofs Verifying Provenance of Digital Media: Security Analysis of C2PA and its Implementation EQuADiSE: Efficient Quantum-safe Adaptive Distributed Symmetric-key Encryption Secure and Updatable Single Password Authentication Batch-Puncturing Circuit CP-ABE (and More) from Lattices Panther: Robust Hybrid KEM Combiners via Structural Splicing
Tail-Hammer: Optimized Statistics for Anonymous Committee...
Bernardo David, IT University of Copenhagen · 2026-05-29 · via Cryptology ePrint Archive

Paper 2026/1101

Tail-Hammer: Optimized Statistics for Anonymous Committees and Applications

Lucia Lavagnino, Chalmers University of Technology

Elena Pagnin, Chalmers University of Technology

Paul Stankovski Wagner, Lund University

Abstract

Techniques to randomly select sets of anonymous parties are ubiquitous in efficient and adaptively secure consensus protocols, as well as in Multi-Party Computation in the YOSO model, where each round is executed by a different random anonymous committee. Anonymous committee selection aims at randomly selecting a set of $n$ parties (the committee), where at most $t$ parties are corrupted (except with negligible probability), drawing from a population of $N \gg n$ parties with at most $T$ corrupted parties. Additionally, each party knows (and can prove) if they belong to the committee, but ignores other members' identities. A very common and efficient instantiation of anonymous committee selection is to select parties according to a VRF output, this however, leads to committees of probabilistic size ($n$ behaves as a Binomial random variable). Despite wide adoption, only Blum et al. (CCS23) provides an analysis of VRF-based probabilistic anonymous committee selection that estimates the size of committees. This analysis relies on lose bounds (Chernoff) and approximations (Poisson). In this work, we revisit Blum et al.'s estimates and derive accurate closed-form formulas (based on a tight Binomial approximation), as well as an efficient high-precision library called Tail-Hammer for computing exact parameters. Notably, Tail-Hammer identifies smaller committee sizes (approximately -25% on average) than Blum et al. (CCS23) for the same security level, leading to improved efficiency in protocols relying on random committee selection, also when anonymity is not needed. Our analysis applies to committee selection techniques that employ unbiased (uniformly random), or bounded-bias randomness, to both synchronous and asynchronous communication settings, and it can account for inactive parties. As a new application, we present a verifiable consistent broadcast protocol that leverages quorums in anonymous committees to achieve efficiency without requiring threshold signatures.

Note: This is the full version of a paper accepted at SCN 2026.

BibTeX

@misc{cryptoeprint:2026/1101,
      author = {Bernardo David and Lucia Lavagnino and Elena Pagnin and Paul Stankovski Wagner},
      title = {Tail-Hammer: Optimized Statistics for Anonymous Committees and Applications},
      howpublished = {Cryptology {ePrint} Archive, Paper 2026/1101},
      year = {2026},
      url = {https://eprint.iacr.org/2026/1101}
}