> For the complete documentation index, see [llms.txt](https://novaq-docs.gitbook.io/novaq/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://novaq-docs.gitbook.io/novaq/novaq-protocol/protocol-architecture.md).

# Protocol Architecture

### **Protocol Architecture**

NovaQ Protocol is structured into **three primary functional layers**:

#### 1. **Verification Layer**

Ensures **AI model authenticity** and deployment integrity using simulated enclave attestation and checkpoint validation. Key features:

* **Hash-bound model identifiers** (e.g., SHA3, BLAKE3)
* **Simulated Trusted Execution Environments (TEEs)** for model loading
* **Merkle Trees** to timestamp and anchor logs of deployments
* **Multi-Checkpoint Proofs (MCP)**: Verifies model hashes across virtual nodes

#### 2. **Optimization Layer**

Enhances **prompt and query inputs** to ensure clarity, compliance, and safety — aligned with LLM response mechanics. This includes:

* **Lattice-inspired phrasing filters** for post-quantum grammar sanitization
* **Redundancy minimization** via NLP compression
* **Bias/injection mitigation** via adversarial prompt stripping
* **Compliance-aware tagging** (flags risky/ambiguous prompts)

#### 3. **Stress Testing Layer**

Simulates **runtime stress and adversarial conditions** against APIs or LLM endpoints using WebAssembly-like logic and quantum-adversarial patterns:

* Fuzz-style injection of malformed and hostile prompts
* Delay & timeout simulations under load
* NLP-based fault detection across model outputs
* Logging of error boundaries and API behavior profiles


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