SNR-centric power trace extractors for side-channel attacks
Existing power trace extractors consider the case where the number of power traces available to the attacker is sufficient to guarantee successful attacks, and the goal of power trace extraction is to extract a small part of traces with high Signal-to-Noise Ratio (SNR) to reduce the complexity of at...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/147252 |
| _version_ | 1811695020097404928 |
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| author | Ou, Changhai Lam, Siew-Kei Sun, Degang Zhou, Xinping Qiao, Kevin Wang, Qu |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Ou, Changhai Lam, Siew-Kei Sun, Degang Zhou, Xinping Qiao, Kevin Wang, Qu |
| author_sort | Ou, Changhai |
| collection | NTU |
| description | Existing power trace extractors consider the case where the number of power traces available to the attacker is sufficient to guarantee successful attacks, and the goal of power trace extraction is to extract a small part of traces with high Signal-to-Noise Ratio (SNR) to reduce the complexity of attacks rather than to increase the success rates. Although strict theoretical proofs are given, the existing power trace extractors are too simple and leakage characteristics of Points-Of-Interest (POIs) have not been thoroughly analyzed. They only maximize the variance of data-dependent power consumption component and ignore the noise component, which results in very limited SNR that hampers the performance of extractors. In this paper, we provide a rigorous theoretical analysis of SNR of power traces, and propose a simple yet efficient SNR-centric extractor, named Shortest Distance First (SDF), to extract power traces with the smallest estimated noise by taking advantage of known plaintexts. In addition, to maximize the variance of the exploitable component while minimizing the noise, we refer to the SNR estimation model and propose another novel extractor named Maximizing Estimated SNR First (MESF). Finally, we further propose an advanced extractor called Mean-optimized MESF (MMESF) that exploits the mean power consumption of each plaintext byte value to more accurately and reasonably estimate the data-dependent power consumption of the corresponding samples. Experiments on both simulated power traces and measurements from an ATmega328p micro-controller demonstrate the superiority of our new extractors. |
| first_indexed | 2024-10-01T07:16:49Z |
| format | Journal Article |
| id | ntu-10356/147252 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:16:49Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1472522021-03-31T07:04:01Z SNR-centric power trace extractors for side-channel attacks Ou, Changhai Lam, Siew-Kei Sun, Degang Zhou, Xinping Qiao, Kevin Wang, Qu School of Computer Science and Engineering Hardware & Embedded Systems Lab (HESL) Engineering::Computer science and engineering Security Power Demand Existing power trace extractors consider the case where the number of power traces available to the attacker is sufficient to guarantee successful attacks, and the goal of power trace extraction is to extract a small part of traces with high Signal-to-Noise Ratio (SNR) to reduce the complexity of attacks rather than to increase the success rates. Although strict theoretical proofs are given, the existing power trace extractors are too simple and leakage characteristics of Points-Of-Interest (POIs) have not been thoroughly analyzed. They only maximize the variance of data-dependent power consumption component and ignore the noise component, which results in very limited SNR that hampers the performance of extractors. In this paper, we provide a rigorous theoretical analysis of SNR of power traces, and propose a simple yet efficient SNR-centric extractor, named Shortest Distance First (SDF), to extract power traces with the smallest estimated noise by taking advantage of known plaintexts. In addition, to maximize the variance of the exploitable component while minimizing the noise, we refer to the SNR estimation model and propose another novel extractor named Maximizing Estimated SNR First (MESF). Finally, we further propose an advanced extractor called Mean-optimized MESF (MMESF) that exploits the mean power consumption of each plaintext byte value to more accurately and reasonably estimate the data-dependent power consumption of the corresponding samples. Experiments on both simulated power traces and measurements from an ATmega328p micro-controller demonstrate the superiority of our new extractors. National Research Foundation (NRF) Accepted version This work was supported in part by the National ResearchFoundation, Singapore, under Grant NRF2016NCR-NCR001-006. 2021-03-31T07:04:01Z 2021-03-31T07:04:01Z 2021 Journal Article Ou, C., Lam, S., Sun, D., Zhou, X., Qiao, K. & Wang, Q. (2021). SNR-centric power trace extractors for side-channel attacks. IEEE Transactions On Computer-Aided Design of Integrated Circuits and Systems, 40(4), 620-632. https://dx.doi.org/10.1109/TCAD.2020.3003849 0278-0070 https://hdl.handle.net/10356/147252 10.1109/TCAD.2020.3003849 2-s2.0-85087507862 4 40 620 632 en NRF2016NCR-NCR001-006 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems © 2020 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. The published version is available at: https://doi.org/10.1109/TCAD.2020.3003849 application/pdf |
| spellingShingle | Engineering::Computer science and engineering Security Power Demand Ou, Changhai Lam, Siew-Kei Sun, Degang Zhou, Xinping Qiao, Kevin Wang, Qu SNR-centric power trace extractors for side-channel attacks |
| title | SNR-centric power trace extractors for side-channel attacks |
| title_full | SNR-centric power trace extractors for side-channel attacks |
| title_fullStr | SNR-centric power trace extractors for side-channel attacks |
| title_full_unstemmed | SNR-centric power trace extractors for side-channel attacks |
| title_short | SNR-centric power trace extractors for side-channel attacks |
| title_sort | snr centric power trace extractors for side channel attacks |
| topic | Engineering::Computer science and engineering Security Power Demand |
| url | https://hdl.handle.net/10356/147252 |
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