Hey @Department of Government Efficiency , here's how I would create verifiable and secure onchain proof of government spending through a Zero Knowledge powered network. A thread

To start, the node operators for this chain would operate solely in Trusted Execution Environments (TEEs) to prevent data leakage or manipulation. This means all data processing by these nodes will be done on hardware that's completely separate from any outside influence.

Financial data collection is done entirely using Zero Knowledge Proofs (ZKPs) that can mathematically verify info to be accurate without revealing it. A proof will be generated for each uploaded statement that can guarantee its validity and be fully traced to its origin. This will ensure that every dollar spent will be backed by a ZKP that verifies exactly how, where, and who spent it.

Transmission of all data will be done entirely using Zero Knowledge Transport Layer Security (zkTLS) to preserve confidentiality. When a user requests information from a node, data will be sent in a way that does not reveal any sensitive information throughout its transmission.

The network's nodes can be operated by govt approved entities that constantly monitor one another to detect malicious intent. The more nodes that operate the network, the more decentralized and secure the network becomes, as a bad actor would have to take control over 50% of nodes to achieve control over the network.

The beauty of having an entirely ZK-powered network is that there is no point at which any sensitive info is revealed. All records are stored, processed, and transmitted as ZK proofs that only show the data to be accurate and not the data itself.

To summarize: - financial data is collected as ZK proofs - data is processed in nodes operating in secure TEEs - All data transmission is done through zkTLS This system will create a network that is entirely transparent so that all govt spending can be audited yet is secure enough to ensure no sensitive govt info is revealed throughout the process. Shoutout to @0xJeff who has a great article about privacy layers within AI that inspired this thread: https://x.com/Defi0xJeff/status/1887131310625521964…