A Secret Key Generation Scheme for Internet of Things using Ternary-States ReRAM-based Physical Unclonable Functions

Abstract

Some of the main challenges towards utilizing conventional cryptographic techniques in Internet of Things (IoT) include the need for generating secret keys for such a large-scale network, distributing the generated keys to all the devices, key storage as well as the vulnerability to security attacks when an adversary gets physical access to the devices. In this paper, a novel secret key generation method is proposed for IoTs that utilize the intrinsic randomness embedded in the devices' memories introduced in the manufacturing process. A fuzzy extractor structure using serially concatenated BCH-Polar codes is proposed to generate reproducible keys from a ReRAM-based ternary-state Physical Unclonable Functions (PUFs) for device authentication and secret key generation. The main concern in deploying PUF-based key generation methods is the leakage of information about the secret keys from the publicly available helper data. The fuzzy extractor proposed in this paper ensures much less mutual information between the generated keys and the helper data. The experimental results show that our proposed scheme is capable of generating notably stronger keys compared to existing techniques, while utilizing a significantly lower number of helper data bits. The failure probability when a low complex Successive Cancellation decoder is implemented in the proposed fuzzy extractor structure is 10 −8 which was further increased to 10 −10 when a complex iterative belief propagation decoder was used. 1

Analysis of Key Generation Methods for Enable Secured Communication in the IoTs System

“…Korenda, Ashwija Reddy Et al. [20] The fuzzy extractor discussed in this paper ensures much less mutual information between the generated keys and the helper data. The experimental results show that their discussed scheme is capable of generating notably stronger keys compared to existing techniques, while utilizing a significantly lower number of helper data bits.…”

A Proof of Concept SRAM-based Physically Unclonable Function (PUF) Key Generation Mechanism for IoT Devices

“…This work utilized polar codes for extraction of key and helper data, thus utilizing the property of zero mutual information between the helper and key. In our previous work, we utilized serially concatenated polar and BCH codes to generate 250 bit keys with 262 helper data bits using SC decoder and Belief propagation decoders, while maintaining a comparable failure probability of 10 −8 and 10 −10 , respectively [36].…”

“…Key Length Helper Data bits Failure Probability Flipping probability Reed Muller Generalized Multiple Concatenated coding [32] 128 13952 10 −6 15% BCH Repetition Code [33] 128 2052 10 −9 13% Generalized Concatenated (GC) Reed Muller [34] 2048 2048 5.37.10 −10 14% GC Reed Solomon [34] 1024 1024 3.47.10 −10 14% Polar Codes SC [35] 128 896 10 −6 15% HA SCL Polar Codes [35] 128 896 10 −9 15% Serially Concatenated BCH and Polar codes using SC decoder [36] 250 262 10 −8 15% Serially Concatenated BCH and Polar codes using Belief Propagation decoder [36] 250 262 10 −10 15% Fig. 7.…”

“…We use real-time SRAM responses of the device along with the helper data produced in the key generation phase to regenerate the key. The average error when an SRAM PUF is used to generate keys using the fuzzy extractors described in [4], [35], [36], [38] is reported in the Table IV. The FAR when a different user imposters as an authenticated user is also [4], [38] were utilized, but the FRR was high as they were not strong enough to correct the errors in the Noisy PUF.…”

“…The FAR when a different user imposters as an authenticated user is also [4], [38] were utilized, but the FRR was high as they were not strong enough to correct the errors in the Noisy PUF. When stronger methods like [35], [36] were utilized, the FAR was higher compared to the weaker methods, as they were capable enough to correct more errors in the PUF, thereby reducing their FRR.…”