A novel computational model for SRAM PUF min-entropy estimation
by Dongfang Li; Qiuyan Zhu; Hong Wang; Wenchao Liu; Zhihua Feng; Jianwei Zhang
International Journal of Computational Science and Engineering (IJCSE), Vol. 19, No. 2, 2019

Abstract: Min-entropy is the standard for quantisation of uncertainty of security key source under the worst case. It indicates the upper bound of length of security key that is able to be extracted from its source. The openly published min-entropy estimation methods are all based on experimental data or statistical tests to obtain the underlying probability distribution of the security key source, where huge number of samples are required and therefore are not feasible from engineering perspective. Aimed at computational complexity optimisation, this paper proposes a novel model for SRAM PUF min-entropy estimation based on the generic coupling relationship between entropy and average energy consumption of the SRAM cell. The model mainly investigates the way of min-entropy evaluation derived from the average energy consumption of memory cell during power-up stage via simulation. We apply the model to estimate the min-entropy of IS62WV51216BLL SRAM chip. The experimental results demonstrated that the accuracy of the proposed min-entropy estimation model is in parallel with that of conventional methods while its computational efficiency surpasses them to a large extent.

Online publication date: Thu, 20-Jun-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com