DocumentCode :
2796870
Title :
Improvement of power analysis attacks using Kalman filter
Author :
Souissi, Youssef ; Guilley, Sylvain ; Danger, Jean-Luc ; Mekki, Sami ; Duc, Guillaume
Author_Institution :
Dept. ComElec, Inst. Telecom/Telecom-ParisTech, Paris, France
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
1778
Lastpage :
1781
Abstract :
Power analysis attacks are non intrusive and easily mounted. As a consequence, there is a growing interest in efficient implementation of these attacks against block cipher algorithms such as Data Encryption Standard (DES) and Advanced Encryption Standard (AES). In our paper we propose a new technique based on the Kalman theory. We show how this technique could be useful for the cryptographic domain by making power analysis attacks faster. Moreover we prove that the Kalman filter is more powerful than the High Order Statistics technique.
Keywords :
Kalman filters; cryptography; telecommunication security; Kalman filter; advanced encryption standard; block cipher algorithms; data encryption standard; power analysis attacks; Algorithm design and analysis; Biomedical measurements; Cryptography; Energy consumption; Kalman filters; Signal analysis; Signal processing algorithms; State-space methods; Statistics; Telecommunications; High Order Statistics; Kalman filtering; power analysis attacks (SPA, DPA, CPA); symmetrical encryption (AES, DES);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5495428
Filename :
5495428
Link To Document :
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