CHRONOS: A Hardware-Assisted Phase-Decoupled Framework for Secure Federated Learning in IoT
Hung Dang

TL;DR
CHRONOS is a hardware-assisted framework that enhances secure federated learning in IoT by decoupling cryptographic setup from training, improving efficiency and security through ARM TrustZone enclave integration.
Contribution
It introduces a novel hardware-assisted approach that separates cryptographic setup from active training, reducing latency and enhancing security in federated learning for IoT devices.
Findings
Achieves up to 74% reduction in aggregation latency.
Provides OS-level compromise resistance and defends against gradient inversion attacks.
Maintains a small, scalable secure storage footprint per device.
Abstract
We propose CHRONOS, a hardware-assisted framework that decouples the cryptographic setup required for private gradient aggregation from the active training phase. CHRONOS executes a once-per-epoch server-relayed Diffie-Hellman key exchange during a device's idle window. It generates ephemeral keypairs and derives PRG keys entirely within an ARM TrustZone enclave, ensuring private keys never exist in Normal World memory. Pairwise secrets are sealed in the enclave, and Shamir secret shares of the ephemeral private key are distributed to peers. During training, clients mask gradients with a single stream-cipher evaluation and transmit them in one communication round. A hardware-backed round counter enforces single-use freshness. If clients drop out mid-round, the server reconstructs their masks from peer-held Shamir shares, preserving correct aggregation without repeating the round.…
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