Name
Abstract | ||
|---|---|---|
Security of edge computing devices has become the most important issue in IoT era. Regarding the security, physical unclonable function (PUF) as forgery prevention technology has attracted attention. PUF utilizes the random physical feature of semiconductor as unique ID. From a viewpoint of feasibility of PUF, evaluation of tamper resistance is important. The evaluation accuracy depends on modeling accuracy of PUF. The modeling requires information of the detailed architecture of PUF. On the other hand, genetic programming (GP) based analysis which can analysis without PUF models has been proposed recently. However, the GP based analysis generates many lethal genes, which reduce evaluation accuracy, during analysis. This study proposes a new GP based analysis, which not only generates no lethal gene, but also requires no PUF models. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/GCCE.2018.8574699 | IEEE Global Conference on Consumer Electronics |
Keywords | Field | DocType |
security of IoT device,physical unclonable function,genetic programming,hardware security | Edge computing,Hardware security module,Computer science,Lethal allele,Internet of Things,Genetic programming,Physical unclonable function,Tamper resistance,Embedded system | Conference |
ISSN | Citations | PageRank |
2378-8143 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taichi Umeda | 1 | 0 | 0.68 |
| Kazuya Shibagaki | 2 | 0 | 0.68 |
| Nozaki, Y. | 3 | 5 | 11.62 |
| Masaya Yoshikawa | 4 | 25 | 23.93 |