? Announcement: Exploring the Benefits of FHE in Cypher

Last week, we unveiled the exciting details of Cypher’s FHE-EVM capabilities. This week, we're diving deeper into the benefits of Fully Homomorphic Encryption (FHE) for data processing and why it's a game-changer for privacy.

What is FHE?
At its core, FHE is an encryption scheme that allows computations to be performed directly on encrypted data, producing encrypted results. These results are identical to those obtained if the computations were run on plaintext, but with a crucial difference: data privacy is never compromised.

Real-World Impact:
Imagine a medical researcher needing to analyze sensitive patient data, such as lung cancer records, but privacy regulations prevent direct access to this information. With FHE, the hospital can encrypt its data and share it securely with the researcher. The researcher can then run necessary computations on this encrypted data without ever seeing the actual patient records. The final results are decrypted only after the entire process is complete, ensuring that the data remains secure and private throughout.

Key Benefits of FHE:

No Need for Trusted Third Parties: Data remains secure and private, even in untrusted environments like public clouds.
Privacy Without Sacrificing Usability: All data features can be used in analysis without compromising sensitive information.
Quantum-Safe Security: FHE schemes are resilient against potential future quantum attacks.

As FHE continues to evolve, it promises new use cases in machine learning, cloud computing, and data analytics, all while keeping sensitive information secure. The ability to compute on encrypted data without exposing it is truly revolutionary.

Stay tuned as we continue to explore and share more about the technology behind Cypher! ?

https://x.com/zero1_labs/status/1825856237873017053

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As it's refined and optimized, we can expect new use cases in machine learning, cloud computing, and data analytics. The ability to compute on encrypted data without exposure is a game-changer. Stay tuned for more updates as we continue to share the tech…

Diving Deeper into Cypher's Technical Capabilities

In our latest announcement, we gave you a brief overview of Cypher, our revolutionary blockchain layer that integrates Fully Homomorphic Encryption (FHE) with Ethereum Virtual Machine (EVM) compatibility. Now, we're excited to dive deeper into the technical aspects that make Cypher a game-changer for confidential computing in AI-driven decentralized applications (dApps).

Key Features:

Secure AI Computation: Cypher allows secure computation on encrypted data, ensuring data privacy throughout the entire process.
EVM Compatibility: Easily migrate existing AI projects to Cypher's platform.
Global Decentralized Computing: Features a global node network and advanced cryptographic tools like Multi-Party Computation (MPC) and Zero-Knowledge Proofs (ZKPs).

How Cypher Handles Data:

Data Encryption: Users encrypt their data using Cypher’s FHE protocols before transmission.
Computation on Encrypted Data: Cypher’s nodes process this encrypted data without ever needing to decrypt it.
Encrypted Output: The computation results are returned to the user in an encrypted form.
Decryption: Users then decrypt the results using their private key, ensuring that only they can access the final output.

Real-World Use Cases:

AI and collaborative model training
Securing Decentralized Physical Infrastructure Networks (DePIN)
Privacy-preserving scientific collaboration (DeSci)
Confidential machine learning

With Cypher, we're setting a new standard for privacy-preserving computation, paving the way for secure, data-driven technologies across AI, decentralized infrastructure, and scientific research.

Stay tuned for more updates as we continue to explore the potential of confidential computing with Cypher! ?
https://x.com/zero1_labs/status/1824017442219458881?t=joJ2cglC1OUBQT4_karMzA&s=19

Blog post: https://z1labs.ai/blog/cypher-unlocking-confidential-computing-for-ai-with-the-first-fully-homomorphic-encryption-fhe-and-evm-integration/

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Road to Mainnet #1: Confidential Computing for AI with FHE-EVM Integration Cypher, a blockchain that merges Fully Homomorphic Encryption (FHE) with Ethereum Virtual Machine (EVM) compatibility, unlocks confidential compute for AI-powered dApps. A technical…

Introducing Cypher?

Cypher is a new technology that aims to bring confidential computing to decentralized AI. It integrates native Fully Homomorphic Encryption (FHE) and Ethereum Virtual Machine (EVM) capabilities to secure and privatize AI models and applications.

Key Features:

- Native FHE Integration: Cypher incorporates FHE into AI models and dApps, allowing computations on encrypted data without decrypting it, ensuring data privacy.
- Confidential Computing Network: Cypher leverages a robust network designed for confidential computing, creating a private environment for AI operations and safeguarding algorithms from external threats.
- Native Encryption for AI Applications: Cypher’s encryption capabilities are tailored for AI applications, enabling developers to build and deploy AI models with built-in privacy features.

Benefits for Builders on Cypher:

- Enhanced data privacy in AI-driven industries like healthcare and finance.
- Improved compliance with data protection regulations.
- Potential for more collaborative AI projects without compromising sensitive data.

Cypher represents a significant step forward in addressing data security concerns in an increasingly AI-driven world.
The testnet is expected to launch in Q4.

https://x.com/zero1_labs/status/1821551802388725941

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https://x.com/Zero1_Community/status/1819373180756041766

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Dino | Zero1 Labs

DINO – The first Blockchain-based game that integrates ERC-404 technology, supported by the ...

? Announcement! ?

We’re thrilled to share that Cypher's FHE is the first for a privacy-first AI compute network, solving the dilemma between privacy and utility

What’s the big deal? ?

- FHE allows computations on encrypted data without decrypting it, ensuring top-notch data privacy and security.
- It’s a major leap for AI in crypto as it enables secure data pooling from multiple sources and simplifies federated learning.
- Plus, it ticks off GDPR requirements by keeping personal data confidential during AI computations.

Why Cypher’s FHE?

- Our FHE implementation enhances security by encrypting both input data and the AI model, making it resistant to model inversion attacks.
- It’s like a silent guardian encrypting all data used for AI modelling across all nodes, making unauthorized access nearly impossible.

Stay tuned for more updates on our upcoming testnet!

For more details, check out our latest tweet!

https://x.com/zero1_labs/status/1819358557068054853

Hey Anon,

We are working tirelessly behind the scenes and will provide you with important updates in the upcoming weeks. To keep our main account focused on the most important news, we have created two subchannels:

https://x.com/Zero1_Ecosystem
https://x.com/Zero1_Community

✨ Give us a follow and stay updated! ✨

Cypher FHE-EVM Coming in 2025!

Testnet access in Q4 2024.

https://x.com/zero1_labs/status/1817904511756931336

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Pirate Nation | Zero1 Labs

Pirate Nation is a new type of game, filled with high seas adventure, treasure, fun, and unexpected ...

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Zero1 | Zero1 Labs

Zero1 Labs stands as the pioneering Proof-of-Stake-powered Decentralized Artificial Intelligence ...

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Welcome @zero1\_labs , our awesome supporter lite sponsor for #EDCON2024! ***💫*** Zero1 is leading & redefining the DEAI ecosystem. Ready to explore? Take the Red Pill & hop into their Discord: https://t.co/50q9yDLytn Claim free tickets & join us in Tokyo: ht…