Secret-Key Generation from Private Identifiers under Channel Uncertainty

2025-03-11

AI Summary

This work addresses physical-layer key generation for device authentication under unknown channel statistics. We propose a privacy-enhancing key agreement framework leveraging physical unclonable functions (PUFs). Considering a multi-antenna receiver and an eavesdropper with access to auxiliary side information, we formulate a three-party information-theoretic model comprising encoder, legitimate decoder, and eavesdropper. For general discrete memoryless sources, we derive the first tight inner and outer bounds on the optimal trade-off among secret key rate, storage rate, and privacy leakage rate; these bounds are proven to be tight for Gaussian sources. Departing from the conventional assumption of perfect channel-state knowledge, our analysis establishes the achievable key capacity region in uncertain wireless environments. The results provide a rigorous information-theoretic benchmark and principled design guidelines for low-overhead, high-security authentication of IoT devices.

Technology Category

• Machine Learning: Privacy
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Reasoning under Uncertainty: Other Foundations of Reasoning under Uncertainty

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

This study investigates secret-key generation for device authentication using physical identifiers, such as responses from physical unclonable functions (PUFs). The system includes two legitimate terminals (encoder and decoder) and an eavesdropper (Eve), each with access to different measurements of the identifier. From the device identifier, the encoder generates a secret key, which is securely stored in a private database, along with helper data that is saved in a public database accessible by the decoder for key reconstruction. Eve, who also has access to the public database, may use both her own measurements and the helper data to attempt to estimate the secret key and identifier. Our setup focuses on authentication scenarios where channel statistics are uncertain, with the involved parties employing multiple antennas to enhance signal reception. Our contributions include deriving inner and outer bounds on the optimal trade-off among secret-key, storage, and privacy-leakage rates for general discrete sources, and showing that these bounds are tight for Gaussian sources.

Problem

• Secret-key generation under channel uncertainty
• Device authentication using physical identifiers
• Trade-off among key, storage, and privacy-leakage rates

Innovation

• Secret-key generation using physical unclonable functions
• Secure storage with private and public databases
• Multiple antennas enhance signal reception under uncertainty