TY - GEN
T1 - A Secret Key Generation Scheme for Internet of Things using Ternary-States ReRAM-based Physical Unclonable Functions
AU - Korenda, Ashwija Reddy
AU - Afghah, Fatemeh
AU - Cambou, Bertrand
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/28
Y1 - 2018/8/28
N2 - 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 BCHPolar 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 10-8which was further increased to 10-10 when a complex iterative belief propagation decoder was used.1 1This project is partially supported by Arizona Board of Regents under Grant # 1003330.
AB - 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 BCHPolar 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 10-8which was further increased to 10-10 when a complex iterative belief propagation decoder was used.1 1This project is partially supported by Arizona Board of Regents under Grant # 1003330.
KW - Fuzzy Extractor
KW - PUFs
KW - Polar Codes
KW - ReRAM
KW - Strong cryptographic key
UR - http://www.scopus.com/inward/record.url?scp=85053900234&partnerID=8YFLogxK
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U2 - 10.1109/IWCMC.2018.8450341
DO - 10.1109/IWCMC.2018.8450341
M3 - Conference contribution
AN - SCOPUS:85053900234
SN - 9781538620700
T3 - 2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018
SP - 1261
EP - 1266
BT - 2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018
Y2 - 25 June 2018 through 29 June 2018
ER -