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2022-09-20
Korenda, Ashwija Reddy, Afghah, Fatemeh, Razi, Abolfazl, Cambou, Bertrand, Begay, Taylor.  2021.  Fuzzy Key Generator Design using ReRAM-Based Physically Unclonable Functions. 2021 IEEE Physical Assurance and Inspection of Electronics (PAINE). :1—7.
Physical unclonable functions (PUFs) are used to create unique device identifiers from their inherent fabrication variability. Unstable readings and variation of the PUF response over time are key issues that limit the applicability of PUFs in real-world systems. In this project, we developed a fuzzy extractor (FE) to generate robust cryptographic keys from ReRAM-based PUFs. We tested the efficiency of the proposed FE using BCH and Polar error correction codes. We use ReRAM-based PUFs operating in pre-forming range to generate binary cryptographic keys at ultra-low power with an objective of tamper sensitivity. We investigate the performance of the proposed FE with real data using the reading of the resistance of pre-formed ReRAM cells under various noise conditions. The results show a bit error rate (BER) in the range of 10−5 for the Polar-codes based method when 10% of the ReRAM cell array is erroneous at Signal to Noise Ratio (SNR) of 20dB.This error rate is achieved by using helper data length of 512 bits for a 256 bit cryptographic key. Our method uses a 2:1 ratio for helper data and key, much lower than the majority of previously reported methods. This property makes our method more robust against helper data attacks.
2020-03-23
Korenda, Ashwija Reddy, Afghah, Fatemeh, Cambou, Bertrand, Philabaum, Christopher.  2019.  A Proof of Concept SRAM-based Physically Unclonable Function (PUF) Key Generation Mechanism for IoT Devices. 2019 16th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). :1–8.
This paper provides a proof of concept for using SRAM based Physically Unclonable Functions (PUFs) to generate private keys for IoT devices. PUFs are utilized, as there is inadequate protection for secret keys stored in the memory of the IoT devices. We utilize a custom-made Arduino mega shield to extract the fingerprint from SRAM chip on demand. We utilize the concepts of ternary states to exclude the cells which are easily prone to flip, allowing us to extract stable bits from the fingerprint of the SRAM. Using the custom-made software for our SRAM device, we can control the error rate of the PUF to achieve an adjustable memory-based PUF for key generation. We utilize several fuzzy extractor techniques based on using different error correction coding methods to generate secret keys from the SRAM PUF, and study the trade-off between the false authentication rate and false rejection rate of the PUF.