2PM.Network

#AI #Blockchain

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Related Resources

  1. Demo Video: Youtube
  2. 2PM Chain Connector (on Calimero Network) Repository: GitHub Link
  3. Other 2PM Repos: GitHub Link

Track

Chain agnostic track AND Calimero | Data Privacy Bounty - AI - Privacy-Preserving AI Training

Here's how 2PM.Network meets the sponsor (Calimero) requirements:

  1. Privacy-Preserving AI Training with Blockchain Integration: 2PM.Network enables decentralized, privacy-focused AI model training through blockchain integration. Using federated learning, it allows collaborative model training while ensuring data privacy. Each node's contributions are secured and transparently verifiable, using Calimero's Chain Connector for seamless communication with the blockchain.

  2. Data Privacy Through Federated Learning: The project creates a distributed AI training ecosystem where data remains on its source nodes, never leaving its original location. Model updates are securely encrypted and transmitted, enhancing AI capabilities without compromising individual data privacy. This approach aligns with Calimero's goal of privacy-preserving AI by maintaining the sovereignty of user data.

  3. Use of the Chain Connector for Federated Learning Verification: The Chain Connector, an abstract layer in the 2PM modular node framework, ensures secure blockchain transaction signing. Nodes execute federated learning tasks with cryptographic verification, allowing any off-chain verifier to validate model training tasks, enhancing trust and security in privacy-preserving AI models.

Project Overview

2PM.Network is a groundbreaking privacy-preserving network protocol designed to support decentralized, secure AI training on blockchain. Using a modular, federated node structure, 2PM.Network empowers users to participate in privacy-focused computations, contributing data and computational power to train AI models collaboratively. The protocol ensures data privacy, enables secure transaction verification, and offers incentives for data and model contributors through a blockchain-integrated ecosystem.

Features

Privacy-Focused Distributed AI Model Training

2PM.Network combines federated learning with fully homomorphic encryption, allowing nodes to train AI models collaboratively without sharing raw data. This decentralized approach ensures that the AI model benefits from diverse data sources, while the data remains securely at its origin, supporting enhanced data privacy and compliance with privacy regulations.

Modular Node Framework with Chain Connector

Each node in the 2PM Network is equipped with the Chain Connector, which abstracts blockchain interactions, facilitating secure federated learning tasks. The modular design allows seamless integration across blockchain systems and supports isolated key management, ensuring that sensitive signing processes are handled offline to maximize security.

Progress and Effort

Federated Learning Task Execution

2PM.Network has implemented federated learning tasks where nodes securely process local data and contribute model updates to the shared AI model. For example, a logistic regression model trained on student performance data demonstrates the network's ability to aggregate insights across nodes while keeping individual data private.

AI Model Verification and Accountability

2PM.Network nodes provide cryptographic proofs of their computations, making each federated learning task verifiable on-chain. This ensures transparency, allowing off-chain verifiers to check task accuracy and model integrity, crucial for building trust in privacy-preserving AI.

Real-Time Inference with Privacy Guarantees

The system enables real-time inferences where user data inputs remain private during processing. For instance, a student’s grade improvement prediction is securely processed on-chain, offering immediate results without exposing sensitive data.

Feasibility and Future Development

Future development directions include:

  1. Expanded Privacy Model Training Framework: Adding more types of AI models and data sets to broaden the federated learning applications, especially for privacy-sensitive domains.

  2. Enhanced Chain Connector Features: Future updates to the Chain Connector will further simplify blockchain interaction and support additional cryptographic mechanisms for increased transaction security.

Social Value

Privacy concerns around data use in AI have limited the utilization of private datasets. 2PM.Network addresses this gap, enabling privacy-focused AI model training with verifiable security and accuracy. By providing a decentralized solution for secure AI training, 2PM.Network empowers organizations and individuals to leverage private data responsibly, promoting secure data usage in AI development.

Through its transparent verification and incentivization mechanisms, 2PM.Network fosters a privacy-respecting environment for AI innovations. This contributes to reducing barriers in data-sharing collaborations, enabling broader societal access to the benefits of privacy-focused AI technology.

Code Modularity

2PM.Network's code architecture supports maintainability and scalability through a modular design:

  • Federated Learning Module: Manages collaborative AI model training, ensuring data remains private and securely integrated.
  • Chain Connector Module: Abstracts blockchain interactions, handles cryptographic signing, and provides proof mechanisms for AI training tasks.
  • Node Management Dashboard: Enables node operators to monitor and manage tasks, data interactions, and contributions to the shared AI model.
  • Data Privacy and Security Module: Implements homomorphic encryption, ensuring user data privacy during model training and inference.
  • Incentive and Reward Module: Distributes rewards to data and computation contributors, promoting sustained engagement and collaboration in the 2PM Network.

The modular structure of 2PM.Network ensures easy extension and adaptation to new privacy and AI developments.

Conclusion

Through robust privacy-preserving technology, innovative blockchain integration, and a scalable, modular code design, 2PM.Network is redefining secure, decentralized AI model training. Looking ahead, 2PM.Network will continue enhancing its privacy and verification features, delivering a trusted framework for private data utilization in AI.

2PM-chain-connector

Chain Connector is an abstract layer connecting 2PM Node and the Blockchain. Chain Connector provides a unique set of APIs to Delta Node regardless of the type of Blockchain system used. And Chain Connector handles the Blockchain transaction signing. In a strict security environment, Chain Connector supports using an isolated signer to keep the private key offline and submit the signature remotely, thus keeping the private key safe.

Deployment Details

License

This project is licensed under the MIT License. You are free to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of this software, provided that the following conditions are met:

Permission Notice

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the software.

Warranty Disclaimer

This software is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, and non-infringement. In no event shall the authors or copyright holders be liable for any claim, damages, or other liability, whether in an action of contract, tort, or otherwise, arising from, out of, or in connection with the software or the use or other dealings in the software.

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