Lethal Genes Aware Genetic Programming Analysis for RO PUF

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@InProceedings{Umeda:2018:GCCE,

• author = "Taichi Umeda and Kazuya Shibagaki and Yusuke Nozaki and Masaya Yoshikawa",
• booktitle = "2018 IEEE 7th Global Conference on Consumer Electronics (GCCE)",
• title = "Lethal Genes Aware Genetic Programming Analysis for RO PUF",
• year = "2018",
• pages = "758--759",
• abstract = "Security of edge computing devices has become the most important issue in internet of things IoT era. Regarding the security, physical unclonable function (PUF) as forgery prevention technology has attracted attention. PUF uses 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 modelling 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.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/GCCE.2018.8574699",
• ISSN = "2378-8143",
• month = oct,
• notes = "Also known as \cite{8574699}",

}

Genetic Programming entries for Taichi Umeda Kazuya Shibagaki Yusuke Nozaki Masaya Yoshikawa

Citations