docs/algorithms/secure_aggregation.md

# Secure Aggregation (Curve25519 SecAgg) Algorithm Specification

## 1. Problem Solved
Secure Aggregation (SecAgg; Bonawitz et al., 2017) resolves the fundamental privacy risk that a curious or compromised central coordinator could inspect unmasked client weight updates $\Delta w_k$.

SecAgg ensures that the central coordinator learns **only** the global sum:

$$S = \sum_{k=1}^K \Delta w_k$$

while remaining cryptographically blinded to any individual bank's contribution $\Delta w_k$.

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## 2. Implementation in CF-Intelligence
- **Location**: [`backend/app/infrastructure/security/p2p_secagg_driver.py`](../../backend/app/infrastructure/security/p2p_secagg_driver.py)
- **Key Exchange**: X25519 (Curve25519 Diffie-Hellman key agreement over $\mathbb{F}_{2^{255}-19}$).
- **Pairwise Zero-Sum Masking**:
  For every pair of active banks $(i, j)$ with $i < j$:
  1. Bank $i$ and Bank $j$ establish a shared secret via Diffie-Hellman: $k_{i,j} = \mathrm{X25519}(\mathrm{sk}_i, \mathrm{pk}_j) = \mathrm{X25519}(\mathrm{sk}_j, \mathrm{pk}_i)$.
  2. A pseudorandom mask vector $s_{i,j} \in \mathbb{R}^d$ is expanded using HMAC-SHA256 seeded with $k_{i,j}$.
  3. Bank $i$ adds $s_{i,j}$ to its update; Bank $j$ subtracts $s_{i,j}$:

$$\widetilde{\Delta w}_i = \Delta w_i + \sum_{j > i} s_{i,j} - \sum_{j < i} s_{j,i} + \mathbf{b}_i$$

  where $\mathbf{b}_i$ is Bank $i$'s local self-mask.
- **Sum Cancellation**:
  When all $K$ clients submit their masked updates to the coordinator:

$$\sum_{i=1}^K \widetilde{\Delta w}_i = \sum_{i=1}^K \Delta w_i + \underbrace{\sum_{i=1}^K \left( \sum_{j > i} s_{i,j} - \sum_{j < i} s_{j,i} \right)}_{= 0} + \sum_{i=1}^K \mathbf{b}_i$$

- **Dropout Resilience**:
  Self-masks $\mathbf{b}_i$ and pairwise seeds are split using $(t, n)$ Shamir's Secret Sharing. If a client drops out before round completion, remaining active peers reveal shares of the dropped client's pairwise keys, enabling the coordinator to subtract orphaned masks without unblinding honest clients.

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## 3. Threat Model & Security Assumptions
- **Adversary Limit**: Protects against an honest-but-curious coordinator colluding with up to $N - 2$ corrupted clients.
- **Collusion Bound**: Requires at least 2 honest clients $(u, v)$ to guarantee complete confidentiality of model updates; their mutual pairwise mask $s_{u,v}$ prevents the coordinator and all $N - 2$ colluding participants from unblinding individual updates.
- **Information-Theoretic Barrier**: In the event of $N - 1$ colluding participants, the remaining client's update is algebraically determined by subtracting known weights from the global sum $S - \sum_{i \neq u} w_i = w_u$, representing the fundamental information-theoretic limit of all additive aggregation protocols.
- **Replay & Tamper Resistance**: Ephemeral Curve25519 key agreements combined with round-salted HKDF-SHA256 derivation (`cfi:secagg:round:{round_id}`) prevent cross-round replay and mask injection attacks.

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## 4. Operational Limitations
- **Communication Rounds**: Requires 4 sequential network rounds:
  1. Advertise Keys (Round 0)
  2. Share Encrypted Seeds (Round 1)
  3. Masked Input Collection (Round 2)
  4. Unmasking Shares Verification (Round 3)
- **Computational Complexity**: Scale $O(K^2)$ in pairwise key negotiations, optimized for consortium sizes $K \le 50$.

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## 5. Test Suite Verification & Scientific Proofs
- **Scientific Verification Suite (53 Passing Tests)**:
  - [`verification/secure_aggregation/tests/test_secagg_correctness.py`](../../verification/secure_aggregation/tests/test_secagg_correctness.py): 27 mathematical tests proving exact pairwise mask cancellation $\sum_{u \in U} \mathbf{m}_u \equiv \mathbf{0} \pmod{2^{32}}$ for $N \in \{2, 3, 5, 8\}$ and dimensions $d \in \{1, 16, 256, 1024, 20000\}$, with floating-point tolerance $\le 10^{-6}$ against unblinded model updates.
  - [`verification/secure_aggregation/tests/test_zero_server_knowledge.py`](../../verification/secure_aggregation/tests/test_zero_server_knowledge.py): 7 statistical and cryptographic tests verifying Pearson correlation $|r(w, y)| < 0.05$ (zero correlation), Shannon entropy $H(y) \ge 31.95\text{ bits}$, $N-2$ non-collusion protection, Shamir $(t, n)$ dropout privacy, and round isolation.
  - [`verification/secure_aggregation/tests/test_secagg_hypothesis.py`](../../verification/secure_aggregation/tests/test_secagg_hypothesis.py): 6 Hypothesis property-based tests verifying unweighted and weighted zero-sum invariants.
  - [`verification/secure_aggregation/tests/test_secagg_robustness.py`](../../verification/secure_aggregation/tests/test_secagg_robustness.py): 12 failure injection and protocol stress scenarios.
  - [`verification/secure_aggregation/tests/test_fhe_homomorphic_sum.py`](../../verification/secure_aggregation/tests/test_fhe_homomorphic_sum.py): TenSEAL CKKS homomorphic linearity verification.
- **Unit & Integration Tests**:
  - [`backend/tests/unit/test_p2p_secagg_driver.py`](../../backend/tests/unit/test_p2p_secagg_driver.py): 16 unit tests covering Curve25519 ECDH key exchange, HMAC bundle signing, PRNG counter expansion, and modular arithmetic.
  - [`backend/tests/unit/test_p2p_secagg_dropout_recovery.py`](../../backend/tests/unit/test_p2p_secagg_dropout_recovery.py): Dropout reconstruction using Shamir $(t, n)$ shares.
  - [`backend/tests/unit/test_shamir_engine.py`](../../backend/tests/unit/test_shamir_engine.py): Polynomial secret sharing primitives over Galois fields.
  - [`backend/tests/unit/test_compression_engine.py`](../../backend/tests/unit/test_compression_engine.py): 22 unit tests verifying wire transfer measurements, Top-K gradient sparsification, FP16/INT8 quantization, and SecAgg protocol overhead bounds.

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## 6. Communication Cost, Bandwidth Overhead & Wire Size Profiling

### 6.1 Cryptographic Coordination Payload Breakdown

Across the 4-round Curve25519 SecAgg lifecycle, the wire payload exchanged between $K$ client banks and the central coordinator consists of:

1. **Round 0 (Advertise Keys)**:
   Each client broadcasts its ephemeral Curve25519 public key ($32\text{ bytes}$) signed with an Ed25519 identity signature ($64\text{ bytes}$):

$$\mathrm{Payload}_{\mathrm{R0}} = K \cdot 96 \quad (\text{bytes})$$

2. **Round 1 (Share Encrypted Seeds)**:
   Each client transmits $(K - 1)$ encrypted seed shares wrapped with recipient public keys ($\approx 48\text{ bytes}$ ciphertext per peer):

$$\mathrm{Payload}_{\mathrm{R1}} = K(K - 1) \cdot 48 \quad (\text{bytes})$$

3. **Round 2 (Masked Input Collection)**:
   Each client transmits its blinded parameter vector $\widetilde{\Delta w}_i \in \mathbb{R}^d$ along with an HMAC-SHA256 message authentication code ($32\text{ bytes}$):

$$\mathrm{Payload}_{\mathrm{R2}} = K \cdot (S_{\mathrm{model}} + 32) \quad (\text{bytes})$$

4. **Round 3 (Unmasking Shares)**:
   Clients reveal Shamir shares of the blinding seeds for dropped participants or self-masks ($\approx 32\text{ bytes}$ per peer):

$$\mathrm{Payload}_{\mathrm{R3}} = K(K - 1) \cdot 32 \quad (\text{bytes})$$

### 6.2 Total Wire Volume vs Baseline Protocols ($d = 1{,}969$ parameters, $K=3$ banks, $R=5$ rounds)

| Protocol | Payload per Round | 5-Round Total Volume | Relative Overhead vs FedAvg | Security & Privacy Guarantee |
| :--- | :---: | :---: | :---: | :--- |
| `FED_AVG` | 31,504 B | **0.1502 MB** | **1.00×** | No cryptographic blinding (plaintext parameters) |
| `FED_PROX` | 31,504 B | **0.1502 MB** | **1.00×** | Identical wire footprint; local proximal loss penalty |
| `CURVE25519_SECAGG` | 32,752 B | **0.1562 MB** | **1.04×** | Information-theoretic zero-knowledge server privacy ($+4.0\%$ overhead) |
| `SCAFFOLD` | 63,008 B | **0.3004 MB** | **2.00×** | Dual parameter + control variate exchange |
| `TENSEAL_CKKS` | 330,792 B | **1.5773 MB** | **10.50×** | Fully homomorphic ciphertext expansion ($10.5\times$ bandwidth) |

The complete empirical benchmark analysis and 4-panel bandwidth visualization figure are documented in [`docs/enterprise_benchmark_report.md#24-federated-communication-cost--bandwidth-profiling-benchmark`](../enterprise_benchmark_report.md) and [`docs/figures/benchmark_communication.png`](../figures/benchmark_communication.png).