Name
Abstract | ||
|---|---|---|
For cryptographic applications based on physical unclonable functions (PUFs), it is very important to estimate the entropy of PUF responses accurately. The upper bound of the entropy estimated by compression algorithms, such as context-tree weighting, is too loose, while the lower bound estimated by the min-entropy calculation is too conservative, especially when the sample size is small. The actu... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCSI.2017.2733582 | IEEE Transactions on Circuits and Systems I: Regular Papers |
Keywords | Field | DocType |
Entropy,Random access memory,Estimation,Convergence,Cryptography,Error correction,Data mining | Convergence (routing),Weighting,Control theory,Upper and lower bounds,Algorithm,Error detection and correction,Static random-access memory,Data compression,Min entropy,Sample size determination,Mathematics | Journal |
Volume | Issue | ISSN |
65 | 2 | 1549-8328 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hailong Liu | 1 | 39 | 7.57 |
| Wenchao Liu | 2 | 23 | 2.55 |
| Zhaojun Lu | 3 | 60 | 5.58 |
| Qiaoling Tong | 4 | 21 | 4.54 |
| Zhenglin Liu | 5 | 53 | 3.97 |