0G and American Fortress launch AI trading solution, completely hiding sender and receiver identities

In the field of blockchain transaction security, protecting the privacy of transaction participants’ identities has become an urgent challenge. According to Foresight News, 0G and AmericanFortress recently jointly released a native AI, privacy-first transaction stack solution aimed at providing comprehensive transaction protection for on-chain AI agents.

Multi-Dimensional Threats to Transaction Privacy

Currently, on-chain smart agents face multiple security risks when executing transactions. Threats such as phishing attacks, address correlation tracking, and transaction context detection continue to trouble users and developers. These attack methods can not only expose the relationships between transaction parties but also potentially undermine the privacy foundation of the entire transaction ecosystem. Therefore, targeted privacy protection technologies are imperative.

Multi-Layer Encryption Protection: Hiding and @E5@

The core of this new solution lies in its innovative privacy architecture design. It combines 0G’s computational layer with AmericanFortress’s dynamic stealth address technology, achieving deep protection of transaction participants’ identities.

First, this technology supports generating encrypted one-time addresses, effectively preventing third parties from correlating sender (absender) and receiver (empfänger) transaction behaviors. This mechanism ensures end-to-end privacy for on-chain transactions.

Second, the system employs zero-knowledge proof mechanisms to conceal account balances. Even while balances are hidden, the verifiability of transactions is maintained, allowing users to selectively disclose information when needed to meet compliance review requirements. This design cleverly balances the tension between privacy protection and regulatory demands.

Zero-Knowledge Proofs and Selective Compliance

The application of zero-knowledge proof technology is a highlight of this solution. It enables users to prove the legality of transactions to auditors without revealing specific transaction details. Through selective proof disclosure mechanisms, users can flexibly find a balance between privacy and compliance, keeping absender and empfänger confidential while satisfying necessary regulatory requirements.

Mainnet Launch and Ecosystem Expansion

Currently, this transaction stack has been officially launched on the 0G mainnet. Multiple institutions, wallet service providers, and Layer 2 ecosystem projects are actively integrating this solution by providing SDK toolkits for AI agent frameworks, embedding privacy protection capabilities into the transaction process.

The introduction of this technology signals a new direction in on-chain privacy protection. As more ecosystem participants adopt this solution, AI-driven transaction activities will be able to ensure the confidentiality of absender and empfänger identities while meeting increasingly strict compliance standards, setting a new industry benchmark for privacy transactions.