MDASCA: An Enhanced Algebraic Side-Channel Attack for Error Tolerance and New Leakage Model Exploitation

Algebraic side-channel attack (ASCA) is a powerful cryptanalysis technique different from conventional side-channel attacks. This paper studies ASCA from three aspects: enhancement, analysis and application. To enhance ASCA, we propose a generic method, called Multiple Deductions-based ASCA (MDASCA)...

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Bibliographic Details
Published inConstructive Side-Channel Analysis and Secure Design pp. 231 - 248
Main Authors Zhao, Xinjie, Zhang, Fan, Guo, Shize, Wang, Tao, Shi, Zhijie, Liu, Huiying, Ji, Keke
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2012
SeriesLecture Notes in Computer Science
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Summary:Algebraic side-channel attack (ASCA) is a powerful cryptanalysis technique different from conventional side-channel attacks. This paper studies ASCA from three aspects: enhancement, analysis and application. To enhance ASCA, we propose a generic method, called Multiple Deductions-based ASCA (MDASCA), to cope the multiple deductions caused by inaccurate measurements or interferences. For the first time, we show that ASCA can exploit cache leakage models. We analyze the attacks and estimate the minimal amount of leakages required for a successful ASCA on AES under different leakage models. In addition, we apply MDASCA to attack AES on an 8-bit microcontroller under Hamming weight leakage model, on two typical microprocessors under access driven cache leakage model, and on a 32-bit ARM microprocessor under trace driven cache leakage model. Many better results are achieved compared to the previous work. The results are also consistent with the theoretical analysis. Our work shows that MDASCA poses great threats with its excellence in error tolerance and new leakage model exploitation.
Bibliography:This work was supported in part by the National Natural Science Foundation of China under the grants 60772082 and 61173191, and US National Science Foundation under the grant CNS-0644188.
ISBN:9783642299117
3642299113
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-642-29912-4_17