Privacy Scaling comes to Starknet! Port existing privacy scaling projects from Ethereum to Starkent for cost efficiency by verifying Groth16 proofs on Starknet
Project Overview: PrivacyScalingSN is an innovative initiative that brings advanced privacy scaling solutions to the Starknet ecosystem. By leveraging the power of Groth16 proofs, we aim to port existing privacy projects from Ethereum to Starknet, achieving greater cost efficiency and scalability.
Core Features:
Groth16 Proof Verification with Garaga: We utilize the Garaga project to seamlessly verify Groth16 proofs on Starknet. This integration ensures robust and efficient verification processes, laying the foundation for secure and private transactions on the network.
Porting Anon Aadhar to Starknet: PrivacyScalingSN is proud to port the PSE’s Anon Aadhar project to Starknet. This feature allows users, particularly from India, to prove their identity without revealing sensitive information from their Aadhar Card. By providing proof of identity in a privacy-preserving manner, we enhance user confidentiality and trust.
Benefits:
Cost Efficiency: Transitioning privacy scaling projects from Ethereum to Starknet significantly reduces costs, making advanced privacy solutions more accessible and affordable.
Enhanced Privacy: Users can leverage sophisticated cryptographic proofs to protect their personal information, ensuring privacy without compromising on security.
Scalability: Starknet’s high-performance environment allows for seamless scaling of privacy-centric applications, supporting a growing user base without degradation in performance.
PrivacyScalingSN is committed to pushing the boundaries of privacy and scalability on Starknet, providing users with cutting-edge tools to safeguard their digital identities and transactions.
Development Process:
Utilizing the Garaga Project:
Porting Anon Aadhar:
Optimization and Testing:
Deployment:
Presentation Preparation:
PrivacyScalingSN, created as a hackathon proof of concept, demonstrates the feasibility and potential of bringing advanced privacy scaling solutions to Starknet. The focus is on showcasing core functionalities and integrating key components to provide a glimpse of what full-scale implementation could achieve.