TY - GEN
T1 - Statistical Analysis to Optimize the Generation of Cryptographic Keys from Physical Unclonable Functions
AU - Cambou, Bertrand
AU - Mohammadi, Mohammad
AU - Philabaum, Christopher
AU - Booher, Duane
N1 - Funding Information:
The authors are thanking the Information Directorate of the US Air Force Research Laboratory (AFRL) for their support of this research work. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of AFRL. The authors are also thanking the contribution of several graduate students at Northern Arizona University, in particular Vince Rodriguez, and Ian Burke.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Physical unclonable functions are not easy to integrate into cryptographic systems because they age, and are sensitive to environmental interferences. Excellent error correcting schemes were developed to handle such drifts, however the computing power needed at the client level can leak information to opponents, and are difficult to deploy to networks of ultra-low power Internet of Things. Response-based cryptography methods, which are server based, use search engines to uncover the erratic keys generated by the physical unclonable functions, minimizing the consumption of electric power at the client level. However, when the defect densities are high, the latencies associated with search engines can be prohibitive. The statistical analysis presented in this paper shows how the fragmentation of the cryptographic keys can significantly reduce the latencies of the search engine, even when error rates are high. The statistical model developed, with Poisson distribution, shows that the level of fragmentation in sub-keys can handle up to 15% error rates. The methodology is generic, and can be applied to any type of physically unclonable functions with defects in the 15% range, or lower.
AB - Physical unclonable functions are not easy to integrate into cryptographic systems because they age, and are sensitive to environmental interferences. Excellent error correcting schemes were developed to handle such drifts, however the computing power needed at the client level can leak information to opponents, and are difficult to deploy to networks of ultra-low power Internet of Things. Response-based cryptography methods, which are server based, use search engines to uncover the erratic keys generated by the physical unclonable functions, minimizing the consumption of electric power at the client level. However, when the defect densities are high, the latencies associated with search engines can be prohibitive. The statistical analysis presented in this paper shows how the fragmentation of the cryptographic keys can significantly reduce the latencies of the search engine, even when error rates are high. The statistical model developed, with Poisson distribution, shows that the level of fragmentation in sub-keys can handle up to 15% error rates. The methodology is generic, and can be applied to any type of physically unclonable functions with defects in the 15% range, or lower.
KW - Error correction
KW - Internet of Things
KW - Physical unclonable functions
KW - Security primitives
UR - http://www.scopus.com/inward/record.url?scp=85088510481&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85088510481&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-52243-8_22
DO - 10.1007/978-3-030-52243-8_22
M3 - Conference contribution
AN - SCOPUS:85088510481
SN - 9783030522421
T3 - Advances in Intelligent Systems and Computing
SP - 302
EP - 321
BT - Intelligent Computing - Proceedings of the 2020 Computing Conference
A2 - Arai, Kohei
A2 - Kapoor, Supriya
A2 - Bhatia, Rahul
PB - Springer
T2 - Science and Information Conference, SAI 2020
Y2 - 16 July 2020 through 17 July 2020
ER -