Confidential Computing

Creates a cryptographically sealed Trusted Execution Environment (TEE) within the CPU that isolates code and data from the host operating system, hypervisor, and other tenants.

• Memory pages are encrypted at the hardware level
• Even a compromised OS cannot read TEE contents
• Implemented via technologies like Intel SGX, AMD SEV-SNP, and ARM CCA
• Protects against privileged insider threats and malicious cloud administrators

A cryptographic mechanism that verifies the identity and integrity of the TEE before any secrets are provisioned or data is processed.

• Generates a hardware-signed attestation report containing a hash of the TEE's initial state
• Allows a relying party to verify the exact code running inside the enclave
• Prevents man-in-the-middle attacks during secure channel establishment
• Essential for establishing trust between the data owner and the untrusted host

Extends encryption coverage to the final frontier of the data lifecycle: active computation in system memory.

• Complements data-at-rest encryption (disk/storage) and data-in-transit encryption (TLS)
• CPU decrypts data only within the TEE boundary
• Memory bus snooping and cold-boot attacks become ineffective
• Critical for workloads processing PII, financial transactions, or proprietary ML models

Enables a central aggregator to combine model updates from multiple factories without ever seeing individual contributions in plaintext.

• Aggregation logic runs inside a TEE, provably isolated from the cloud provider
• Clients encrypt updates to the TEE's public key, ensuring end-to-end confidentiality
• Attestation proves to each factory that only the intended aggregation code executes
• Eliminates the need to trust the aggregation server operator

Guarantees that the software running inside the TEE has not been tampered with, replaced, or backdoored.

• The hardware measures the entire trusted computing base (TCB) at launch
• Any modification to the enclave code produces a different cryptographic measurement
• Attestation fails if the measurement doesn't match the expected value
• Protects against supply chain attacks and runtime code injection

Modern TEE implementations incorporate defenses against microarchitectural side-channel attacks that attempt to infer enclave secrets through timing, cache, or power analysis.

• AMD SEV-SNP adds reverse-map table protection against page-table-based attacks
• Constant-time cryptographic libraries prevent timing leakage
• Hardware mitigations for speculative execution vulnerabilities like Spectre and Meltdown
• Ongoing research into formal verification of side-channel resistance

A hardware-enforced enclave within a processor that isolates code and data from the host operating system, hypervisor, and other applications. TEEs provide three core guarantees: data confidentiality (outsiders cannot read enclave contents), data integrity (outsiders cannot modify enclave contents), and code integrity (the enclave runs only authorized code).

• Intel SGX: Application-level enclaves with memory encryption engine
• AMD SEV-SNP: Full VM encryption with integrity protection
• ARM TrustZone: Divides processor into secure and non-secure worlds

TEEs are the fundamental building block that makes Confidential Computing possible, creating a hardware root of trust that even the cloud provider cannot breach.

A cryptographic verification protocol that allows a relying party to confirm that a specific workload is running unmodified inside a genuine TEE on a trusted platform. The process produces a signed attestation report containing a hash of the enclave's initial state and the platform's hardware identity.

• Local attestation: Two enclaves on the same platform verify each other
• Remote attestation: An external client verifies an enclave over the network
• Third-party attestation services like Intel IAS or AMD KDS act as trusted intermediaries

Without remote attestation, there is no way to distinguish a real TEE from a software emulation, making it essential for establishing trust in federated learning aggregation nodes.

A multi-party computation protocol that allows a central server to compute the sum of encrypted model updates from multiple clients without being able to inspect any individual contribution. When combined with Confidential Computing, the aggregation server runs inside a TEE, ensuring the plaintext intermediate values are never exposed to the cloud operator.

• Secret sharing: Updates are split into fragments that reveal nothing individually
• Masking vectors: Pairwise masks cancel out during summation
• Dropout robustness: Protocol tolerates clients going offline mid-round

This pairing of cryptographic secure aggregation with hardware TEEs provides defense-in-depth: even if the TEE is compromised, the individual updates remain masked.

A cryptographic scheme that enables computation directly on encrypted data, producing an encrypted result that, when decrypted, matches the output of operations performed on the plaintext. Unlike TEEs, homomorphic encryption provides mathematical guarantees rather than hardware-based trust.

• Partially Homomorphic Encryption (PHE): Supports only addition or multiplication
• Somewhat Homomorphic Encryption (SHE): Supports limited operations before noise overwhelms the ciphertext
• Fully Homomorphic Encryption (FHE): Supports arbitrary computation on encrypted data

In federated learning, homomorphic encryption can protect model updates in transit, while Confidential Computing protects them during aggregation. The two technologies are complementary, not competing.

A hardware component integrated into modern processors that transparently encrypts and decrypts data as it moves between the CPU and main memory. This prevents cold boot attacks, DMA attacks, and physical memory snooping by the host operating system or hypervisor.

• Total Memory Encryption (TME) on AMD: Encrypts all memory with a single key
• Multi-Key TME (MKTME) on Intel: Allows per-VM or per-enclave encryption keys
• Inline encryption: Encryption occurs at memory controller speed with negligible latency

The memory encryption engine is the hardware foundation that makes TEEs resistant to physical attacks, ensuring that even if an attacker probes the memory bus, they see only ciphertext.

The resilience property of a distributed system to continue operating correctly even when some constituent nodes exhibit arbitrary or malicious failures. In the context of Confidential Computing for federated learning, BFT ensures the aggregation protocol remains correct even if some TEEs are compromised or some clients submit poisoned updates.

• Practical BFT (PBFT): Tolerates up to one-third of nodes being faulty
• Federated BFT: Designed for open, permissionless participation
• TEE-backed BFT: Uses attestation to reduce the fault probability of each node

Combining BFT consensus with TEE-based aggregation creates a system where the global model remains trustworthy even under active attack, critical for cross-silo federated learning across competing manufacturers.