Information entropy based leakage profiling

An accurate leakage model is critical to side-channel attacks and evaluations. Leakage certification plays an important role to address the following question: “how good is my leakage model?” Moreover, most of the current leakage model profiling only exploits the information from lower orders of mom...

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Main Authors: Ou, Changhai, Zhou, Xinping, Lam, Siew-Kei, Zhou, Chengju, Ning, Fangxing
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/151858
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1518582021-07-05T08:28:32Z Information entropy based leakage profiling Ou, Changhai Zhou, Xinping Lam, Siew-Kei Zhou, Chengju Ning, Fangxing School of Computer Science and Engineering Engineering::Computer science and engineering Security Entropy An accurate leakage model is critical to side-channel attacks and evaluations. Leakage certification plays an important role to address the following question: “how good is my leakage model?” Moreover, most of the current leakage model profiling only exploits the information from lower orders of moments. They still need to tolerate assumption error and estimation error from unknown leakage models. There are many Probability Density Functions (PDFs) satisfying given moment constraints. As such, finding an unbiased, objective and reasonable model still remains an unresolved problem. In this paper, we address a more fundamental question: “which model can approach the leakage infinitely and is the optimal in theory?” In particular, we extract information from higher-order moments and propose Maximum Entropy Distribution (MED) to estimate the leakage model as MED is an unbiased, objective and theoretically the most reasonable PDF conditioned upon the available information. MED is a moment-based statistical PDF model in side-channel attacks. It can theoretically use information on arbitrary higher-order moments to infinitely approximate the leakage distribution, and well compensates the theory vacancy of model profiling and evaluation. Experimental results demonstrate the superiority of our proposed method for approximating the leakage model using MED estimation. National Research Foundation (NRF) 2021-07-05T08:28:32Z 2021-07-05T08:28:32Z 2021 Journal Article Ou, C., Zhou, X., Lam, S., Zhou, C. & Ning, F. (2021). Information entropy based leakage profiling. IEEE Transactions On Computer-Aided Design of Integrated Circuits and Systems, 40(6), 1052-1062. https://dx.doi.org/10.1109/TCAD.2020.3036810 1937-4151 https://hdl.handle.net/10356/151858 10.1109/TCAD.2020.3036810 2-s2.0-85096405280 6 40 1052 1062 en IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems © 2021 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Security
Entropy
spellingShingle Engineering::Computer science and engineering
Security
Entropy
Ou, Changhai
Zhou, Xinping
Lam, Siew-Kei
Zhou, Chengju
Ning, Fangxing
Information entropy based leakage profiling
description An accurate leakage model is critical to side-channel attacks and evaluations. Leakage certification plays an important role to address the following question: “how good is my leakage model?” Moreover, most of the current leakage model profiling only exploits the information from lower orders of moments. They still need to tolerate assumption error and estimation error from unknown leakage models. There are many Probability Density Functions (PDFs) satisfying given moment constraints. As such, finding an unbiased, objective and reasonable model still remains an unresolved problem. In this paper, we address a more fundamental question: “which model can approach the leakage infinitely and is the optimal in theory?” In particular, we extract information from higher-order moments and propose Maximum Entropy Distribution (MED) to estimate the leakage model as MED is an unbiased, objective and theoretically the most reasonable PDF conditioned upon the available information. MED is a moment-based statistical PDF model in side-channel attacks. It can theoretically use information on arbitrary higher-order moments to infinitely approximate the leakage distribution, and well compensates the theory vacancy of model profiling and evaluation. Experimental results demonstrate the superiority of our proposed method for approximating the leakage model using MED estimation.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Ou, Changhai
Zhou, Xinping
Lam, Siew-Kei
Zhou, Chengju
Ning, Fangxing
format Article
author Ou, Changhai
Zhou, Xinping
Lam, Siew-Kei
Zhou, Chengju
Ning, Fangxing
author_sort Ou, Changhai
title Information entropy based leakage profiling
title_short Information entropy based leakage profiling
title_full Information entropy based leakage profiling
title_fullStr Information entropy based leakage profiling
title_full_unstemmed Information entropy based leakage profiling
title_sort information entropy based leakage profiling
publishDate 2021
url https://hdl.handle.net/10356/151858
_version_ 1705151345460248576