Copertina

How to Beat Nakamoto in the Race

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cao, Shu-Jie, Guo, Dongning
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Security, Latency, and Throughput of Proof-of-Work Nakamoto Consensus
di: Cao, Shu-Jie, et al.
Pubblicazione: (2023)

Larger Scale Offers Better Security in the Nakamoto-style Blockchain
di: Hu, Junjie
Pubblicazione: (2025)

Larger-scale Nakamoto-style Blockchains Don't Necessarily Offer Better Security
di: Albrecht, Jannik, et al.
Pubblicazione: (2024)

Selfish Mining in Multi-Attacker Scenarios: An Empirical Evaluation of Nakamoto, Fruitchain, and Strongchain
di: Perešíni, Martin, et al.
Pubblicazione: (2026)

Nakamoto Consensus from Multiple Resources
di: Baig, Mirza Ahad, et al.
Pubblicazione: (2025)

Nakamoto Consensus under Bounded Processing Capacity
di: Kiffer, Lucianna, et al.
Pubblicazione: (2023)

Fault-Tolerant Spectrum Usage Consensus for Low-Earth-Orbit Satellite Constellations
di: Mollakhani, Arman, et al.
Pubblicazione: (2023)

Timestamp Manipulation: Timestamp-based Nakamoto-style Blockchains are Vulnerable
di: Hu, Junjie, et al.
Pubblicazione: (2025)

From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists
di: Cecconello, Stefano, et al.
Pubblicazione: (2026)

Blind Baselines Beat Membership Inference Attacks for Foundation Models
di: Das, Debeshee, et al.
Pubblicazione: (2024)

Work-in-Progress: Crash Course: Can (Under Attack) Autonomous Driving Beat Human Drivers?
di: Marchiori, Francesco, et al.
Pubblicazione: (2024)

RaceTEE: Enabling Interoperability of Confidential Smart Contracts
di: Zhang, Keyu, et al.
Pubblicazione: (2025)

Payout Races and Congested Channels: A Formal Analysis of Security in the Lightning Network
di: Weintraub, Ben, et al.
Pubblicazione: (2024)

FibRace: a large-scale benchmark of client-side proving on mobile devices
di: Malatrait, Simon, et al.
Pubblicazione: (2025)

Double Spending Analysis of Nakamoto Consensus for Time-Varying Mining Rates with Ruin Theory
di: Doger, Mustafa, et al.
Pubblicazione: (2024)

PreCurious: How Innocent Pre-Trained Language Models Turn into Privacy Traps
di: Liu, Ruixuan, et al.
Pubblicazione: (2024)

Proof-of-Useful-Work Blockchain for Trustworthy Biomedical Hyperdimensional Computing
di: Wen, Jinghao, et al.
Pubblicazione: (2022)

MarkSweep: A No-box Removal Attack on AI-Generated Image Watermarking via Noise Intensification and Frequency-aware Denoising
di: Cao, Jie, et al.
Pubblicazione: (2026)

Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend
di: Liu, Yige, et al.
Pubblicazione: (2026)

The Adaptive Arms Race: Redefining Robustness in AI Security
di: Tsingenopoulos, Ilias, et al.
Pubblicazione: (2023)

DUAP: Dual-task Universal Adversarial Perturbations Against Voice Control Systems
di: Sun, Suyang, et al.
Pubblicazione: (2026)

From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AI
di: Zhang, Zelin, et al.
Pubblicazione: (2026)

SRAM-based Physically Unclonable Function using Lightweight Hamming-Code Fuzzy Extractor for Energy Harvesting Beat Sensors
di: Pham, Hoang-Long, et al.
Pubblicazione: (2025)

Differential Privacy with Higher Utility by Exploiting Coordinate-wise Disparity: Laplace Mechanism Can Beat Gaussian in High Dimensions
di: Muthukrishnan, Gokularam, et al.
Pubblicazione: (2023)

Privacy-Preserving Race/Ethnicity Estimation for Algorithmic Bias Measurement in the U.S
di: Badrinarayanan, Saikrishna, et al.
Pubblicazione: (2024)

Targeted Nakamoto: A Bitcoin Protocol to Balance Network Security and Carbon Emissions
di: Aronoff, Daniel
Pubblicazione: (2024)

When Graph Convolution Meets Double Attention: Online Privacy Disclosure Detection with Multi-Label Text Classification
di: Liang, Zhanbo, et al.
Pubblicazione: (2023)

Do Modern Post-Hoc Watermarking Methods Beat Broken-Arrows?
di: Gesny, Enoal, et al.
Pubblicazione: (2026)

A Context-Sensitive, Outlier-Based Static Analysis to Find Kernel Race Conditions
di: Dossche, Niels, et al.
Pubblicazione: (2024)

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
di: Zhang, Jianqing, et al.
Pubblicazione: (2025)

A Robust Certified Machine Unlearning Method Under Distribution Shift
di: Guo, Jinduo, et al.
Pubblicazione: (2026)

Kite: How to Delegate Voting Power Privately
di: Nazirkhanova, Kamilla, et al.
Pubblicazione: (2025)

How to Steal Reasoning Without Reasoning Traces
di: Zhang, Tingwei, et al.
Pubblicazione: (2026)

How Secure is Code Generated by ChatGPT?
di: Khoury, Raphaël, et al.
Pubblicazione: (2023)

Algorithms for Sparse LPN and LSPN Against Low-noise
di: Chen, Xue, et al.
Pubblicazione: (2024)

Dye4AI: Assuring Data Boundary on Generative AI Services
di: Wang, Shu, et al.
Pubblicazione: (2024)

You Still See Me: How Data Protection Supports the Architecture of AI Surveillance
di: Yew, Rui-Jie, et al.
Pubblicazione: (2024)

Takedown: How It's Done in Modern Coding Agent Exploits
di: Lee, Eunkyu, et al.
Pubblicazione: (2025)

How Blind and Low-Vision Users Manage Their Passwords
di: Ponticello, Alexander, et al.
Pubblicazione: (2025)

Beating Backdoor Attack at Its Own Game
di: Liu, Min, et al.
Pubblicazione: (2023)