Larger-scale Nakamoto-style Blockchains Offer Better Security

• URL: http://arxiv.org/abs/2509.05708v2
• Date: Thu, 18 Sep 2025 14:52:34 GMT
• Title: Larger-scale Nakamoto-style Blockchains Offer Better Security
• Authors: Junjie Hu,
• Abstract summary: Traditional security models for Nakamoto-style blockchains overestimate adversarial coordination by assuming instantaneous synchronization among malicious nodes.<n>This paper introduces a dual-delay framework to revisit security analysis, addressing this oversight through two key innovations.
• Score: 6.951606473725132
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Traditional security models for Nakamoto-style blockchains overestimate adversarial coordination by assuming instantaneous synchronization among malicious nodes, neglecting the critical impact of internal communication delays on security. This paper introduces a dual-delay framework to revisit security analysis, addressing this oversight through two key innovations. First, the static delay model quantifies how adversarial communication delays (\(\Delta_a\)) constrain the effective growth rate of private chains, derived via an M/D/1 queuing model as \(\lambda_{eff} = \lambda_a / (1 + \lambda_a \Delta_a)\). This model reveals that the security threshold (\(\beta^*\)), the maximum adversarial power the system tolerates, increases with \(\Delta_a\), even exceeding the classic 51\% boundary when \(\Delta_a \textgreater \Delta\) (honest nodes' delay), breaking the long-standing 50\% assumption. Second, the dynamic delay model integrates probabilistic corruption and scale-dependent delays to characterize the total adversarial delay window (\(\Delta_{total} = \Delta(n) e^{-k\beta} + c \log(1 + \beta n)\)), where \(\Delta(n) \in \Theta(\log n)\) captures honest nodes' logarithmic delay growth. Asymptotic analysis shows adversarial power decays linearly with network scale, ensuring the probability of \(\beta \leq \beta^*\) approaches 1 as \(n \to \infty\). By exposing the interplay between network scale, communication delays, and power dilution, we provide a theoretical foundation for optimizing consensus protocols and assessing robustness in large-scale Nakamoto-style blockchains.

Related papers

• Time Is All It Takes: Spike-Retiming Attacks on Event-Driven Spiking Neural Networks [87.16809558673403]
  Spiking neural networks (SNNs) compute with discrete spikes and exploit temporal structure.<n>We study a timing-only adversary that retimes existing spikes while preserving spike counts and amplitudes in event-driven SNNs.
  arXiv  Detail & Related papers  (2026-02-03T09:06:53Z)
• Speculative Decoding in Decentralized LLM Inference: Turning Communication Latency into Computation Throughput [8.480238305117298]
  We present Decentralized Speculative Decoding (DSD), a plug-and-play framework for decentralized inference.<n>We introduce an adaptive speculative verification strategy that adjusts acceptance thresholds by token-level semantic importance, delivering an additional 15% to 20% end-to-end speedup without retraining.<n>DSD achieves up to 2.56x speedup on HumanEval and 2.59x on GSM8K, surpassing the Eagle3 baseline while preserving accuracy.
  arXiv  Detail & Related papers  (2025-11-13T06:36:33Z)
• Logit-Entropy Adaptive Stopping Heuristic for Efficient Chain-of-Thought Reasoning [0.0]
  Chain-of-Thought (CoT) prompting is a key technique for enabling complex reasoning in large language models.<n>We introduce LEASH: Logit-Entropy Adaptive Stopping Heuristic, a training-free decoding algorithm that adaptively halts rationale generation.
  arXiv  Detail & Related papers  (2025-11-06T18:43:16Z)
• FRAIN to Train: A Fast-and-Reliable Solution for Decentralized Federated Learning [1.1510009152620668]
  asynchronous learning (FL) enables collaborative model training across distributed clients while preserving data locality.<n>We introduce Fast-and-Reliable AI Network, FRAIN, a new FL method that mitigates these limitations by incorporating two key ideas.<n>Experiments with a CNN image-classification model and a Transformer-based language model demonstrate that FRAIN achieves more stable and robust convergence than FedAvg, FedAsync, and BRAIN.
  arXiv  Detail & Related papers  (2025-05-07T08:20:23Z)
• Zaptos: Towards Optimal Blockchain Latency [52.30047458198369]
  We introduce Zaptos, a parallel pipelined architecture designed to minimize end-to-end latency.<n>Zaptos achieves a throughput of 20,000 transactions per second with sub-second latency.
  arXiv  Detail & Related papers  (2025-01-18T00:22:22Z)
• The Latency Price of Threshold Cryptosystem in Blockchains [52.359230560289745]
  We study the interplay between threshold cryptography and a class of blockchains that use Byzantine-fault tolerant (BFT) consensus protocols.<n>Our measurements from the Aptos mainnet show that the optimistic approach reduces latency overhead by 71%.
  arXiv  Detail & Related papers  (2024-07-16T20:53:04Z)
• Larger-scale Nakamoto-style Blockchains Don't Necessarily Offer Better Security [1.2644625435032817]
  Research on Nakamoto-style consensus protocols has shown that network delays degrade the security of these protocols. This contradicts the very foundation of blockchains, namely that decentralization improves security. We take a closer look at how the network scale affects security of Nakamoto-style blockchains.
  arXiv  Detail & Related papers  (2024-04-15T16:09:41Z)
• Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling [73.5602474095954]
  We study the non-asymptotic performance of approximation schemes with delayed updates under Markovian sampling. Our theoretical findings shed light on the finite-time effects of delays for a broad class of algorithms.
  arXiv  Detail & Related papers  (2024-02-19T03:08:02Z)
• Transaction Capacity, Security and Latency in Blockchains [35.16231062731263]
  We analyze how secure a block is after the block becomes k-deep, i.e., security-latency, for Nakamoto consensus. We compare our results for Nakamoto consensus under bounded network delay models and obtain analogous bounds for safety violation threshold.
  arXiv  Detail & Related papers  (2024-02-15T17:43:13Z)
• Security, Latency, and Throughput of Proof-of-Work Nakamoto Consensus [4.738177482027387]
  This paper investigates the fundamental trade-offs between block safety, confirmation latency, and transaction throughput of proof-of-work protocols.<n>New upper and lower bounds are derived for the probability of block safety violations as a function of honest and adversarial mining rates.<n>The study uncovers a fundamental trade-off between transaction throughput and confirmation latency, ultimately determined by the desired fault tolerance and the rate at which block propagation delay increases with block size.
  arXiv  Detail & Related papers  (2023-12-09T09:03:14Z)
• Acceleration in Distributed Optimization Under Similarity [72.54787082152278]
  We study distributed (strongly convex) optimization problems over a network of agents, with no centralized nodes. An $varepsilon$-solution is achieved in $tildemathcalrhoObig(sqrtfracbeta/mu (1-)log1/varepsilonbig)$ number of communications steps. This rate matches (up to poly-log factors) for the first time lower complexity communication bounds of distributed gossip-algorithms applied to the class of problems of interest.
  arXiv  Detail & Related papers  (2021-10-24T04:03:00Z)
• Distributed stochastic optimization with large delays [59.95552973784946]
  One of the most widely used methods for solving large-scale optimization problems is distributed asynchronous gradient descent (DASGD) We show that DASGD converges to a global optimal implementation model under same delay assumptions.
  arXiv  Detail & Related papers  (2021-07-06T21:59:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.