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| ファイル | 記述 | サイズ | フォーマット | |
|---|---|---|---|---|
| TCSII.2018.2821267.pdf | 671.45 kB | Adobe PDF | 見る/開く |
| タイトル: | Coin Flipping PUF: A Novel PUF with Improved Resistance against Machine Learning Attacks |
| 著者: | Tanaka, Yuki Bian, Song  Hiromoto, Masayuki Sato, Takashi   https://orcid.org/0000-0002-1577-8259 (unconfirmed) |
| 著者名の別形: | 田中, 悠貴 辺, 松 廣本, 正之 佐藤, 高史 |
| キーワード: | PUF Hardware Security Machine Learning Ring Oscillator Bistable Ring |
| 発行日: | May-2018 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | IEEE Transactions on Circuits and Systems II: Express Briefs |
| 巻: | 65 |
| 号: | 5 |
| 開始ページ: | 602 |
| 終了ページ: | 606 |
| 抄録: | We propose a novel coin-flipping physically unclonable function (CF-PUF) that significantly improves the resistance against machine-learning attacks. The proposed PUF utilizes the strong nonlinearity of the convergence time of bistable rings (BRs) with respect to variations in the threshold voltage. The response is generated based on the instantaneous value of a ring oscillator at the convergence time of the corresponding BR, which is running in parallel. SPICE simulations show that the prediction accuracy of support-vector machine (SVM) on the responses of CF-PUF is around 50 percent, which means that SVM cannot predict better than random guesses. |
| 著作権等: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。 This is not the published version. Please cite only the published version. |
| URI: | http://hdl.handle.net/2433/230968 |
| DOI(出版社版): | 10.1109/TCSII.2018.2821267 |
| 出現コレクション: | 学術雑誌掲載論文等 |
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