Cypher Technical Documentation
  • Introduction
    • Overview
    • Key Features and Technical Advantages
    • Developer Focused Development
  • Technical Innovation
    • Fully Homomorphic Encryption EVM (fhEVM)
    • Layer 3 Architecture
    • Privacy-Preserving Data Management
    • Seamless Integration
    • Optimized for Privacy-Critical Applications
  • Cypher’s fhEVM Technology
    • What is fhEVM?
    • Architecture of fhEVM
    • Detailed Supported Operations in fhEVM
  • Deploying Smart Contracts on Cypher Testnet
    • Configuration and Deployment
    • Obtaining Testnet Tokens
  • Operations in a fhEVM Framework
    • Concepts
    • Random
    • Secret Store and Access Control in Encrypted Smart Contracts
    • Using fhevmjs for Encrypted Smart Contract Development
  • Tokenomics V2
    • $DEAI Token
    • Token Utility
    • Token Distribution
  • Cypher Layer 3 Tech Integration
  • Glossary
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  • Practical Applications
  • Purpose
  1. Introduction

Developer Focused Development

Cypher’s platform equips developers with a comprehensive toolchain to implement encrypted workflows seamlessly:

  • SDK and APIs: Offers libraries for integrating FHE computations into smart contracts, with detailed support for Solidity and EVM-compatible chains.

  • Encryption-Oriented Oracles: Enables secure data feeds for AI models, allowing encrypted external data to be consumed on-chain.

  • Pre-Built FHE Templates: Includes ready-to-use templates for common AI use cases such as encrypted predictive analytics, federated learning, and private data marketplaces.

Practical Applications

Developers can leverage Cypher to create next-generation AI-powered dApps across diverse industries:

  • Healthcare: Encrypted medical data analysis and AI diagnostics on-chain.

  • Finance: Privacy-preserving fraud detection and risk assessment models.

  • Supply Chain: Secure multi-party computation for real-time optimization and analytics.

Cypher’s infrastructure redefines the boundaries of privacy and functionality in decentralized systems, providing the building blocks for scalable, efficient, and secure AI-focused applications.

Purpose

This technical documentation is tailored for individuals and teams operating at the intersection of blockchain, AI, and decentralized systems development. It aims to provide in-depth technical insights, and a comprehensive framework for leveraging Cypher’s advanced features.

Blockchain Developers:

Designed for engineers with a solid foundation in the Ethereum ecosystem, including proficiency in Solidity and the Ethereum Virtual Machine (EVM). Developers familiar with Layer 2 rollups or modular blockchain architectures will find Cypher’s Layer 3 architecture particularly compelling. It will cover the integration of FHE-based computation within smart contracts, interaction with Cypher’s decentralized nodes, and best practices for optimizing gas efficiency when incorporating encryption-heavy workflows.

Cryptographic Researchers:

For academics and practitioners focused on cutting-edge cryptographic protocols, Cypher offers a practical implementation of Fully Homomorphic Encryption (FHE) within a decentralized framework. This guide delves into the cryptographic primitives employed, key exchange mechanisms, and Cypher’s approach to maintaining performance while ensuring data confidentiality. Topics include FHE circuit design, compatibility with emerging encryption standards, and benchmarking secure computations against plaintext analogs.

Decentralized Systems Engineers:

Engineers specializing in building secure, high-performance, and scalable applications will benefit from Cypher’s emphasis on privacy-preserving computation. The guide explores architectural strategies for integrating Cypher into complex dApp ecosystems, including multi-chain interoperability, modular design for state management, and asynchronous task execution for encrypted workloads. Detailed case studies provide a blueprint for deploying scalable applications without compromising user data security.

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Last updated 5 months ago