Cryptographic Provenance in ETDI

• Cryptographic Provenance in ETDI is a framework ensuring end-to-end integrity, authenticity, and auditability of digital artifacts using verifiable cryptographic techniques.
• It employs collision-resistant hash functions, digital signatures, and remote attestation from TEEs to secure multi-step transformations in complex supply chains.
• The approach enables efficient policy enforcement and compliance checks in CI/CD pipelines while maintaining decentralized trust among mutually distrustful participants.

Cryptographic provenance in ETDI (Evaluate–Transform–Deliver–Ingest) frameworks encompasses a set of mechanisms and protocols that establish end-to-end integrity, authenticity, and auditability of digital artifacts across complex, multi-actor supply chains, distributed code deployments, and collaborative environments. These mechanisms provide formal, cryptographically verifiable assurances about the origin, transformation, and compliance of artifacts—enabling mutually distrustful principals (e.g., software developers, cloud providers, data owners) to enforce security policies through hardware roots of trust, signed and hash-linked provenance records, and decentralized endorsement infrastructures (Melara et al., 2021).

1. Formal Definition, Goals, and System Model

CDI (Code Deployment Integrity) is a cryptographically anchored framework tailored for ETDI scenarios, aimed at securing distributed code and artifact deployments by maintaining an immutable, verifiable history of each processing or transformation step (Melara et al., 2021). The principal goals are:

• Confidentiality of artifacts: Only secure hashes (e.g., SHA-256) of inputs and outputs are exchanged, preventing exposure of proprietary code.
• Decentralized trust: Each participant specifies their own trusted Vetting Authorities (VAs), with possible requirements for m-of-n VA endorsement thresholds.
• On-demand, tool-agnostic verification: Deployers can verify compliance a posteriori using only the published provenance records and VA signatures, without hard-coding expectations about exact build tools.

The ETDI cryptographic provenance model presupposes a threat landscape where attackers fully control the operating system, build pipeline configuration, and network—but cannot breach the guarantees of the underlying Trusted Execution Environments (TEEs, e.g., SGX, SEV), hash functions, signature schemes, or the manufacturer-provided attestation and endorsement logic (Melara et al., 2021).

2. Cryptographic Primitives and Foundational Protocols

The CDI provenance pipeline relies on core primitives:

• Collision-resistant hash functions ($H$, e.g., SHA-256): Used both for per-step record chaining and Merkle tree aggregation across multiple artifacts.
• Digital signatures (e.g., ECDSA, Ed25519): Each provenance step is signed beneath a key generated or provisioned inside the TEE, and sealed to that TEE's measured state.
• Merkle trees: When multiple inputs are present or for checkpointing, hashes are aggregated, enabling compact proofs of inclusion or checkpointing for long provenance chains.
• Remote attestation: Each tool's execution inside a TEE is attested to a VA, whose manifest for the tool binary lists required properties. The TEE produces a quote $$Q = \mathit{Sign}_{EK}(\mathrm{PCRs} \| \mathrm{nonce})$$ which is verified against the manifest.

The provenance record for each step $i$ includes metadata $m_i$ (tool hash, VA manifest sigs, build flags, input/output hashes) and is linked in a hash chain:

$$H_0 = \text{genesis} \qquad H_i = H(H_{i-1} \| m_i)$$

After execution, the enclave signs $H_i$: $\sigma_i = \text{Sign}_{SK_{\text{tool}}}(H_i)$.

The final bundle, after $N$ steps, is:

$$(H_N,\, \{\sigma_1, \ldots, \sigma_N\},\, \text{VA\_sigs})$$

where $\text{VA\_sigs}$ are the signatures from trusted authorities on the tool manifests (Melara et al., 2021).

3. Metadata Capture, Chaining, and Policy Enforcement

Each supply chain tool or transformation stage is instrumented (directly or via wrappers) to:

• Measure and attest its own binary before execution.
• Request VA-signed manifests upon startup and seal SK to the measured identity.
• For each artifact consumed, read prior provenance state $\{H_{i-1}, \sigma_{i-1}\}$, verify integrity, compute new metadata $m_i$, extend $H_{i-1}$ to $H_i$, sign $H_i$ beneath $SK_{\text{tool}}$, and append $(m_i, H_i, \sigma_i)$ to the record chain.

Provenance collection is thus lockstep, with no tool aware of more than the state hash and signature it inherits. Forgery or splicing is infeasible short of a TEE, hash, or signature scheme compromise (Melara et al., 2021).

A policy language allows expressing application-specific requirements:

• Trusted tool versions and required VA signers.
• Required or forbidden build flags.
• Static/dynamic analysis requirements.
• Threshold VA endorsement (e.g., “at least two out of three VAs must endorse this compiler”).

Verification at deployment checks:

1. Chain integrity via replay of $H_0 \rightarrow H_N$ extensions and signature checks.
2. Policy compliance via VA signature thresholds and parameter parsing.

4. Security Properties and Guarantees

The security analysis of CDI demonstrates:

• Integrity: $H_i$ binds all prior steps in a hash chain; any alteration, omission, or reordering is detected.
• Authenticity: Only the attested TEE holding $SK_{\text{tool}}$ can create valid $\sigma_i$; no OS-level compromise suffices.
• Non-repudiation: Sealing $SK_{\text{tool}}$ to unique hardware measurements and VA manifests disables denial of record origin.
• Policy enforcement: Deployment only proceeds if the provenance satisfies all chain, signature, and policy checks.

These properties hold under the standard cryptographic assumptions for hash functions (collision resistance), signature unforgeability, and TEE hardware isolation, along with the trustworthiness of manufacturer-supplied attestation and endorsement systems (Melara et al., 2021).

5. Performance Analysis and Deployment Considerations

Prototype deployments on Intel SGX demonstrate that:

• Remote attestation per tool incurs an initial ≈150 ms cost, typically amortized.
• Per-step hash extension and signing (for a ~1 KB record) takes ≈400 μs.
• Overall CI/CD pipeline latency increases by 5–12% over unsigned Docker builds, dominated by enclave and signature costs.
• Provenance bundle size scales linearly ($\approx 2$ KB per step), but can be compressed/aggregated via Merkle trees.

The overhead profile is deemed well within acceptable bounds for modern DevSecOps pipelines, where verifiable end-to-end security and deployment trustworthiness take precedence over minimal latency (Melara et al., 2021).

6. Significance and Future Research

CDI demonstrates that ETDI cryptographic provenance is practically achievable using a composition of TEEs, hash chains, digital signatures, and a pluggable, signed policy layer. This architecture enables deployment platforms, CI/CD systems, and enforcement engines to:

• Automatically ensure that the delivered microservice or artifact is the output of a policy-compliant, fully auditable build process.
• Attest provenance to arbitrary third parties, without exposing source artifacts or build internals.
• Accommodate decentralized, multi-tenant environments with flexible trust boundaries and endorsement topologies.

Consequently, CDI’s approach forms a technical foundation for secure supply-chain verification, regulatory compliance, and cross-principal accountability in cloud-native, federated, and collaborative computing contexts, representing a major advance in scalable, hardware-anchored provenance (Melara et al., 2021).