Zero-Knowledge Proofs (ZK) in FLOPS

FLOPS is committed to building a secure, efficient, and trustworthy decentralized AI computing platform. To achieve this goal, FLOPS incorporates zero-knowledge proofs (ZK) technology into its architecture to enhance data privacy protection and computational trustworthiness.

Zero-knowledge proofs (ZK) are a cryptographic technique that allows one party (the prover) to convince another party (the verifier) of the truth of a statement without revealing any information about the statement itself. In FLOPS, ZK technology is primarily applied in the following scenarios:

1. Private AI Model Training:

• On the FLOPS platform, users can leverage ZK technology for private AI model training. This means users can demonstrate the effectiveness of their models to other users without disclosing the training data.

• For example, a healthcare institution can use ZK technology to train a disease diagnosis model and prove its accuracy to other healthcare institutions without sharing sensitive patient medical data.

2. Secure Data Sharing:

• ZK technology can be used to securely share data. For instance, during federated learning, multiple institutions can utilize ZK technology to share data without exposing it to other institutions.

• This approach effectively protects data privacy while allowing institutions to collaborate and jointly train more powerful AI models.

3. Trusted Computing:

• ZK technology can be used to verify the correctness of computational results without revealing any information about the computational process.

• For example, users can employ ZK technology to verify the prediction results of AI models, ensuring that the model's output is trustworthy.

ZK Technology Implementation in FLOPS:

FLOPS is currently exploring and researching different ZK technology implementation solutions, including:

• zk-SNARKs: zk-SNARKs are an efficient ZK technology that can generate very concise proofs but require a complex setup process.

• zk-STARKs: zk-STARKs are a setup-free ZK technology, but the proofs are relatively larger in size.

• Other ZK Technologies: FLOPS will continue to monitor and research other ZK technologies, such as Bulletproofs and PLONK, to find the most suitable solution for its application scenarios.

Advantages of ZK Technology:

• Data Privacy Protection: ZK technology effectively protects data privacy, preventing sensitive data leaks.

• Computational Trustworthiness: ZK technology ensures the correctness of computational results, enhancing computational trustworthiness.

• Scalability: ZK technology can be scaled to large datasets and complex computational tasks.

ZK technology is an essential component of the FLOPS platform's security and privacy protection. By leveraging ZK technology, FLOPS can achieve private AI model training, secure data sharing, and trusted computing, providing users with a secure, efficient, and trustworthy decentralized AI computing platform.

FLOPS will continue to research and develop ZK technology to further enhance the platform's security and privacy protection capabilities and explore the application of ZK technology in more AI application scenarios.