The Blockchain and AI Converging
Privacy solutions have not yet become widely adopted in blockchains and decentralized apps. One reason for this may be that they are seen as burdensome by developers and users. To overcome this, Fhenix CEO Guy Itzhaki suggests making privacy solutions compatible with the Ethereum Virtual Machine (EVM) and introducing Fully Homomorphic Encryption (FHE) capabilities to the Solidity programming language.
Protecting Privacy in the Converging World of Blockchain and AI
Itzhaki believes that raising awareness about emerging risks is crucial in protecting privacy when blockchain and AI converge. This will prompt developers to design applications that address these challenges. For users, educating themselves about safe usage and utilizing tools that support personal data protection is the key to safeguarding their privacy.
Main Obstacles to Web3 Mass Adoption
Itzhaki identifies the lack of a sense of security, poor user experience, and regulatory concerns as the main obstacles to Web3 mass adoption. To address these challenges, FHE technology can provide a better sense of security, simplify user interactions with the blockchain, and support decentralized identity management.
Coexistence of FHE and ZK Proofs
FHE and zero-knowledge proofs (ZK proofs) are different technologies that can coexist to create a robust encryption layer. Combining ZK proofs with FHE can achieve fully generalizable, confidential decentralized finance (defi). ZK proofs can ensure the integrity of user inputs and computation, FHE can process computation on encrypted data, and multiparty computation (MPC) can separate the keys used.
Fhenix and the FHE Rollup
Fhenix is an FHE-powered Layer 2 solution that brings computation over encrypted data to Ethereum. Through the FHE Rollup, users can conduct encrypted on-chain transactions and explore applications like confidential trustless gaming and private voting. Fhenix utilizes Zama’s fhEVM, which integrates FHE into the Ethereum Virtual Machine (EVM) and allows developers to create encrypted smart contracts using Solidity.
Integration of Privacy Solutions into Existing Chains and Platforms
FHE technology should be made as easy as possible for developers and users. Fhenix ensures EVM compatibility and brings FHE capabilities to Solidity, reducing the burden on developers. The focus is on creating a developer-friendly stack to simplify the development process.
Potential Use Cases of FHE
FHE can benefit applications that require data encryption, such as decentralized identity, confidential payments, trustless gaming, and confidential defi. For example, FHE can enable fully private on-chain encryption in casino gaming, ensuring data privacy and trust. Fhenix’s FHE Rollups empower developers to create custom app chains with FHE technology integrated, enabling various gaming ecosystems.
Safeguarding On-Chain Privacy in the Convergence of AI and Blockchain
Raising awareness of the challenges in Web3 and educating users about safe usage are important precautionary measures. Itzhaki highlights the need for tools that support personal data protection. He also envisions apps that can attest to the origin of AI-generative content, preserving data origin on blockchains. FHE can contribute to creating better AI modules by allowing users to share data for training while maintaining privacy.
Hot Take: The Convergence of Blockchain and AI Requires Privacy Solutions
While privacy solutions have yet to become widely adopted in the blockchain ecosystem, they play a crucial role in ensuring user privacy and safety. The convergence of blockchain and AI presents both opportunities and challenges. To achieve mass adoption of Web3 and unlock its full potential, developers and users need to address the obstacles of security, user experience, and regulations. Technologies like FHE and ZK proofs can coexist to create an efficient encryption layer. By integrating privacy solutions into existing chains and platforms, developers can simplify the development process and enhance user privacy. Raising awareness and utilizing tools for personal data protection are essential in safeguarding on-chain privacy in the era of blockchain and AI convergence.
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