https://pubchem.ncbi.nlm.nih.gov/patent/AU-2024203136-B2

The integration of identity into consensus—often discussed in the context of "Proof of Humanity"—attempts to solve fundamental bottlenecks in decentralized networks. Below is an analysis of the proposed use cases, the security architecture, and an assessment of the project's execution feasibility.

Proposed Use Cases and Technical Feasibility

Decentralized Physical Services (The Liability Problem)

The primary barrier to deploying decentralized physical services (such as a blockchain-based Uber or Airbnb) is not network throughput, but legal liability and physical safety. Smart contracts currently cannot enforce real-world accountability because interacting parties are pseudonymous.

Protocol-Level Multi-Factor Authentication (MFA)

The reliance on private keys remains a critical vulnerability in digital asset custody. If a seed phrase is compromised, the assets are irreversibly lost.

Direct Fiat Integration

Currently, transitioning between fiat currencies and digital assets requires centralized exchanges (CEXs) to comply with KYC/AML regulations. Anonymous validator nodes cannot legally process fiat transactions.

Security and Privacy Architecture

Storing Personally Identifiable Information (PII) on a decentralized network presents severe privacy risks. The patent outlines a specific security model combining three mechanisms to mitigate this:

• Trusted Execution Environments (TEEs): PII (such as passports and biometric scans) is not stored on a public ledger. It is processed exclusively inside hardware TEEs (such as Intel SGX or AMD SEV). These secure enclaves ensure that even the physical owner of the node server cannot access or alter the data being processed. (Note: Claims by the inventor that this data remains "private for eternity" should be viewed critically. While TEEs are the current enterprise standard for confidential computing, hardware vulnerabilities and future quantum computing advancements present long-term risks. The data does get flushed out of TEE's once the processing is complete, so no long-term storage of high-risk PII data)
• Cryptoeconomic Staking (Slashing): Identity nodes are required to stake significant capital to participate in consensus. If the network detects malicious behavior—such as attempting to run verification software outside of the TEE to extract data—the node's staked tokens are immediately slashed (burned). This establishes a severe financial disincentive for bad actors.
• Decentralized Machine Learning Consensus: This is the core structural novelty. Instead of relying on a single centralized algorithm for verification, encrypted biometric data is processed simultaneously by multiple independent Identity Nodes inside their respective TEEs. These nodes run ML algorithms and must achieve mathematical consensus on the output (e.g., confirming a biometric match). To successfully fake an identity or compromise data, an attacker would need to simultaneously breach the hardware enclaves of multiple globally distributed validators, which is practically infeasible.