A novel computational model for SRAM PUF min-entropy estimation. (17th June 2019)

• Record Type: Journal Article
• Authors: Li, Dongfang; Zhu, Qiuyan; Wang, Hong; Liu, Wenchao; Feng, Zhihua; Zhang, Jianwei
• Is Part Of: International journal of computational science and engineering. Volume 19:Number 2(2019)
• Page Start: 215
• Page End: 222
• Publication Date: 2019-06-17
• Subjects: min-entropy -- SRAM -- PUF -- estimation model -- entropy-energy coupling; Computer science -- Mathematics -- Periodicals; Computer simulation -- Mathematical aspects -- Periodicals; Computational intelligence -- Periodicals; 004.015105
• Languages: English
• ISSNs: 1742-7185

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.