# Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains

arXiv: https://arxiv.org/abs/1801.10228 · HTML: https://mlsanity.com/paper/1801.10228/

## Key facts

- Cited by 49 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2018.

## Built on by (most cited first, 30 of 49)

- [Decentralized Federated Learning: A Survey on Security and Privacy](https://mlsanity.com/paper/2401.17319/) (2024)
- [Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review](https://mlsanity.com/paper/2205.07855/) (2022)
- [Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning](https://mlsanity.com/paper/2403.19178/) (2024)
- [BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning](https://mlsanity.com/paper/2202.02817/) (2022)
- [Privacy-Preserving in Blockchain-based Federated Learning Systems](https://mlsanity.com/paper/2401.03552/) (2024)
- [Right to History: A Sovereignty Kernel for Verifiable AI Agent Execution](https://mlsanity.com/paper/2602.20214/) (2026)
- [Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based Analysis](https://mlsanity.com/paper/2309.05525/) (2023)
- [A review of Federated Learning in Intrusion Detection Systems for IoT](https://mlsanity.com/paper/2204.12443/) (2022)
- [FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks](https://mlsanity.com/paper/2310.02113/) (2023)
- [Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage](https://mlsanity.com/paper/2404.06077/) (2024)
- [Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles](https://mlsanity.com/paper/2103.01116/) (2021)
- [Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach](https://mlsanity.com/paper/2202.12443/) (2022)
- [Blockchain-Empowered Trustworthy Data Sharing: Fundamentals, Applications, and Challenges](https://mlsanity.com/paper/2303.06546/) (2023)
- [From Logic Monopoly to Social Contract: Separation of Power and the Institutional Foundations for Autonomous Agent Economies](https://mlsanity.com/paper/2603.25100/) (2026)
- [Reward-Based 1-bit Compressed Federated Distillation on Blockchain](https://mlsanity.com/paper/2106.14265/) (2021)
- [Digital Twins for Dynamic Management of Blockchain Systems](https://mlsanity.com/paper/2204.12477/) (2022)
- [An Efficient and Reliable Asynchronous Federated Learning Scheme for Smart Public Transportation](https://mlsanity.com/paper/2208.07194/) (2022)
- [Survey of Federated Learning Models for Spatial-Temporal Mobility Applications](https://mlsanity.com/paper/2305.05257/) (2023)
- [Proof-of-Collaborative-Learning: A Multi-winner Federated Learning Consensus Algorithm](https://mlsanity.com/paper/2407.13018/) (2024)
- [A Survey on AI for 6G: Challenges and Opportunities](https://mlsanity.com/paper/2604.02370/) (2026)
- [SourceP: Detecting Ponzi Schemes on Ethereum with Source Code](https://mlsanity.com/paper/2306.01665/) (2023)
- [Can Blockchains Reliably Train Machine Learning Models?](https://mlsanity.com/paper/2307.07066/) (2023)
- [FedBChain: A Blockchain-enabled Federated Learning Framework for Improving DeepConvLSTM with Comparative Strategy Insights](https://mlsanity.com/paper/2407.21282/) (2024)
- [MetaBGM: Dynamic Soundtrack Transformation For Continuous Multi-Scene Experiences With Ambient Awareness And Personalization](https://mlsanity.com/paper/2409.03844/) (2024)
- [Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving](https://mlsanity.com/paper/2603.02214/) (2026)
- [InfraBench: Evaluating Infrastructure Agents Across Layers, Lifecycle, and Risk](https://mlsanity.com/paper/2608.11234/) (2026)
- [Measuring the Impact of Blockchain and Smart Contract on Construction Supply Chain Visibility](https://mlsanity.com/paper/2104.07532/) (2021)
- [A Bytecode-based Approach for Smart Contract Classification](https://mlsanity.com/paper/2106.15497/) (2021)
- [How Computer Science Can Aid Forest Restoration](https://mlsanity.com/paper/2109.07898/) (2021)
- [Towards automated verification of multi-party consensus protocols](https://mlsanity.com/paper/2112.02397/) (2021)

## Abstract (arXiv)

Fabric is a modular and extensible open-source system for deploying and operating permissioned blockchains and one of the Hyperledger projects hosted by the Linux Foundation (www.hyperledger.org). Fabric is the first truly extensible blockchain system for running distributed applications. It supports modular consensus protocols, which allows the system to be tailored to particular use cases and trust models. Fabric is also the first blockchain system that runs distributed applications written in standard, general-purpose programming languages, without systemic dependency on a native cryptocurrency. This stands in sharp contrast to existing blockchain platforms that require "smart-contracts" to be written in domain-specific languages or rely on a cryptocurrency. Fabric realizes the permissioned model using a portable notion of membership, which may be integrated with industry-standard identity management. To support such flexibility, Fabric introduces an entirely novel blockchain design and revamps the way blockchains cope with non-determinism, resource exhaustion, and performance attacks. This paper describes Fabric, its architecture, the rationale behind various design decisions, its most prominent implementation aspects, as well as its distributed application programming model. We further evaluate Fabric by implementing and benchmarking a Bitcoin-inspired digital currency. We show that Fabric achieves end-to-end throughput of more than 3500 transactions per second in certain popular deployment configurations, with sub-second latency, scaling well to over 100 peers.