Statistical Fault Analysis for PRINCE and its Evaluation
-
- Nozaki Yusuke
- Dept. of Information Engineering, Graduate School of Meijo University
-
- Nohara Kohei
- Dept. of Information Engineering, Graduate School of Meijo University
-
- Matsuhisa Ryoma
- Dept. of Information Engineering, Graduate School of Meijo University
-
- Asahi Kensaku
- Dept. of Information Engineering, Meijo University
-
- Yoshikawa Masaya
- Dept. of Information Engineering, Meijo University
Bibliographic Information
- Other Title
-
- PRINCEに対する統計的フォールト解析とその評価
- PRINCE ニ タイスル トウケイテキ フォールト カイセキ ト ソノ ヒョウカ
Search this article
Description
In devices that are used for RFID tags and sensor networks, the number of available hardware resources is extremely small. Since there is a risk of information leakage from these devices, the data they handle must be enciphered. A lightweight block cipher must be used in these devices, due to their resource constraints. Although the encryption algorithms are theoretically safe, it has been recently reported that confidential information could be illegally revealed when the encryption algorithms are used in electronic circuits. In particular, fault analysis attacks have become extremely serious problems. Fault analysis attacks intentionally generate operation errors during the encryption processing and illegally obtain confidential information by pairing an incorrect cipher text and a correct cipher text. To secure the safety of lightweight block ciphers in the future, the tamper resistance against fault analysis attacks must be verified. The present study proposes a new fault analysis method for PRINCE. The proposed method introduces hierarchical attack model using statistical processing to reveal secret keys. Simulation results prove the validity of the proposed method.
Journal
-
- IEEJ Transactions on Electronics, Information and Systems
-
IEEJ Transactions on Electronics, Information and Systems 135 (12), 1442-1452, 2015
The Institute of Electrical Engineers of Japan
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1390282679585924736
-
- NII Article ID
- 130005112623
-
- NII Book ID
- AN10065950
-
- ISSN
- 13488155
- 03854221
-
- NDL BIB ID
- 026984689
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- NDL Search
- Crossref
- CiNii Articles
- OpenAIRE
-
- Abstract License Flag
- Disallowed