2018/05/17 by Ashwija Reddy Korenda, Korenda, Ashwija Reddy, Fatemeh Afghah +3
Computer Science · Engineering · #Advanced Memory and Neural Computing #Cryptography and Security (cs.CR) #Digital Media Forensic Detection #FOS: Computer and information sciences #Physical Unclonable Functions (PUFs) and Hardware Security
paper · pdf · doi:10.48550/arxiv.1805.06980
openalex publication_date 2018/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Some of the main challenges towards utilizing conventional cryptographic\ntechniques in Internet of Things (IoT) include the need for generating secret\nkeys for such a large-scale network, distributing the generated keys to all the\ndevices, key storage as well as the vulnerability to security attacks when an\nadversary gets physical access to the devices. In this paper, a novel secret\nkey generation method is proposed for IoTs that utilize the intrinsic\nrandomness embedded in the devices' memories introduced in the manufacturing\nprocess. A fuzzy extractor structure using serially concatenated BCH-Polar\ncodes is proposed to generate reproducible keys from a ReRAM-based\n\ternary-state Physical Unclonable Functions (PUFs) for device\nauthentication and secret key generation. The ReRAM based PUFs are the most\npractical choice for authentication and key generation in IoT, as they operate\nat or below the systems' noise level and therefore are less vulnerable to side\nchannel attacks compared to the alternative memory technologies. However, the\ncurrent ReRAM-based PUFs present a high false negative authentication rate\nsince the behavior of these devices can vary in different physical conditions\nthat results in a low probability of regenerating the same response in\ndifferent attempts. In this paper, we propose a secret key generation scheme\nfor ternary state PUFs that enables reliable reconstruction of the desired\nsecret keys utilizing a serially concatenated BCH-Polar fuzzy extractor. The\nexperimental results show that the proposed model can offer a significantly\nlower probability of mismatch between the original key and the regenerated\nones, while a less number of \Helper data bits were used to extract the\n\Key when compared to previously proposed fuzzy extractor techniques.\n