Safety

At Planck, security is paramount. We prioritize the protection of user data, ensuring a robust and secure environment for all participants in the Planck network. Here's how we maintain the safety and integrity of your information:

1. User Data Integrity:

• Planck's application operates independently of user data. It aggregates information from diverse sources on the internet, fellow users, developers, and enterprises leveraging the Planck network.

• The generated data is machine-generated and transmitted to peer nodes, maintaining a clear separation from user-specific information.

2. Identity Protection:

• The internal features of the Planck network utilize generated data exclusively for model training, with no connection to user identities. This ensures a privacy-focused approach to data handling.

3. End-to-End Encryption:

• Planck employs a robust tunneling system with end-to-end encryption. This cryptographic measure enhances security by preventing packet sniffing on the network, ensuring the confidentiality of communication between nodes.

4. Virtualization for Data Separation:

• The application utilizes virtualization techniques, effectively isolating the host machine from the application environment. This separation not only enhances security but also safeguards data from unauthorized alterations by users.

5. Data Generation and Transmission:

• To contribute to the network, users' machines (nodes) generate data. This approach ensures that the data shared on the network is securely generated from individual user machines, enhancing the overall integrity of the information.

At Planck, we are committed to providing a secure and trustworthy platform, assuring users that their data is handled with the utmost care and protected by cutting-edge security measures. Your privacy and security are central to our mission in building a decentralized and democratized AI ecosystem.