Using Convolutional Codes for Key Extraction in SRAM Physical Unclonable Functions
This work addresses the need for more reliable and compact cryptographic key generation in hardware security, but it is incremental as it builds on existing methods for error correction in PUFs.
The paper tackled the problem of unstable key reproduction in SRAM Physical Unclonable Functions (PUFs) by applying convolutional codes with larger memory length and advanced decoding techniques, resulting in decreased reconstruction failure probability and reduced PUF implementation size.
Physical Unclonable Functions (PUFs) exploit variations in the manufacturing process to derive bit sequences from integrated circuits, which can be used as secure cryptographic keys. Instead of storing the keys in an insecure, non-volatile memory, they can be reproduced when needed. Since the reproduced sequences are not stable due to physical reasons, error correction must be applied. Recently, convolutional codes were shown to be suitable for key reproduction in PUFs based on SRAM. This work shows how to further decrease the reconstruction failure probability and PUF implementation size using codes with larger memory length and decoding concepts such as soft-information and list decoding.