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QMS: Evaluating the Side-Channel Resistance of Masked Software from Source Code

Published: 01 June 2014 Publication History

Abstract

Many commercial systems in the embedded space have shown weakness against power analysis based side-channel attacks in recent years. Designing countermeasures to defend against such attacks is both labor intensive and error prone. Furthermore, there is a lack of formal methods for quantifying the actual strength of a countermeasure implementation. Security design errors may therefore go undetected until the side-channel leakage is physically measured and evaluated. We show a better solution based on static analysis of C source code. We introduce the new notion of Quantitative Masking Strength (QMS) to estimate the amount of information leakage from software through side channels. The QMS can be automatically computed from the source code of a countermeasure implementation. Our experiments, based on side-channel measurement on real devices, show that the QMS accurately quantifies the side-channel resistance of the software implementation.

References

[1]
J. Balasch, B. Gierlichs, R. Verdult, L. Batina, and I. Verbauwhede. Power analysis of Atmel CryptoMemory - recovering keys from secure EEPROMs. In CT-RSA, 2012.
[2]
A. Bayrak, F. Regazzoni, D. Novo, and P. Ienne. Sleuth: Automated verification of software power analysis countermeasures. In CHES, 2013.
[3]
G. Bertoni, J. Daemen, M. Peeters, G. V. Assche, and R. V. Keer. Keccak implementation overview. URL: http://keccak.neokeon.org/Keccak-implementation-3.2.pdf.
[4]
J. Blömer, J. Guajardo, and V. Krummel. Provably secure masking of AES. In Selected Areas in Cryptography, 2004.
[5]
J. Boyar and R. Peralta. A small depth-16 circuit for the AES S-Box. In SEC, pages 287--298, 2012.
[6]
E. M. Clarke, O. Grumberg, and D. A. Peled. Model Checking. MIT Press, Cambridge, MA, 1999.
[7]
B. Dutertre and L. de Moura. A fast linear-arithmetic solver for DPLL(T). In CAV, pages 81--94, 2006.
[8]
H. Eldib and C. Wang. An SMT based method for optimizing arithmetic computations in embedded software code. In FMCAD, 2013.
[9]
H. Eldib, C. Wang, and P. Schaumont. SMT based verification of software countermeasures against side-channel attacks. In TACAS, 2014.
[10]
L. Goubin. A sound method for switching between boolean and arithmetic masking. In CHES, pages 3--15, 2001.
[11]
C. Herbst, E. Oswald, and S. Mangard. An AES smart card implementation resistant to power analysis attacks. In ACNS. pages 239--252, 2006.
[12]
P. C. Kocher, J. Jaffe, and B. Jun. Differential power analysis. In CRYPTO, pages 388--397, 1999.
[13]
B. Li, C. Wang, and F. Somenzi. A satisfiability-based approach to abstraction refinement in model checking. ENTCS, 89(4), 2003.
[14]
S. Mangard, E. Oswald, and T. Popp. Power Analysis Attacks -- Revealing the Secrets of Smart Sards. Springer, 2007.
[15]
T. S. Messerges. Securing the AES finalists against power analysis attacks. In Fast Software Encryption, 2000.
[16]
A. Moradi, A. Barenghi, T. Kasper, and C. Paar. On the vulnerability of FPGA bitstream encryption against power analysis attacks - extracting keys from Xilinx Virtex-II FPGAs. IACR Cryptology, 2011.
[17]
NIST. Keccak reference code submission to the SHA-3 competition. URL: http://csrc.nist.gov/groups/ST/hash/sha-3/Round3/documents/Keccak_FinalRnd.zip.
[18]
C. Paar, T. Eisenbarth, M. Kasper, T. Kasper, and A. Moradi. Keeloq and side-channel analysis-evolution of an attack. In FDTC, pages 65--69, 2009.
[19]
E. Prouff and M. Rivain. Masking against side-channel attacks: A formal security proof. In EUROCRYPT. 2013.
[20]
A. Sabelfeld and A. C. Myers. Language-based information-flow security. IEEE Journal on Selected Areas in Communications, 21(1):5--19, 2003.
[21]
M. Taha and P. Schaumont. Differential power analysis of MAC-Keccak at any key-length. In IWSEC, 2013.
[22]
C. Wang, G. D. Hachhtel, and F. Somenzi. Abstraction Refinement for Large Scale Model Checking. Springer, 2006.
[23]
C. Wang, H. Jin, G. Hachtel, and F. Somenzi. Refining the SAT decision ordering for bounded model checking. In DAC, San Diego, CA, 2004.
[24]
Xilinx. Microblaze soft processor core. URL: http://www.xilinx.com/tools/microblaze.htm.
[25]
Z. Yang, C. Wang, F. Ivančić, and A. Gupta. Mixed symbolic representations for model checking software programs. In MEMOCODE, pages 17--24, July 2006.

Cited By

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  • (2024)Compositional Verification of First-Order Masking Countermeasures against Power Side-Channel AttacksACM Transactions on Software Engineering and Methodology10.1145/363570733:3(1-38)Online publication date: 14-Mar-2024
  • (2024)Information-Theoretic EvaluationMathematical Foundations for Side-Channel Analysis of Cryptographic Systems10.1007/978-3-031-64399-6_5(221-266)Online publication date: 12-Jul-2024
  • (2023)LeakageVerif: Efficient and Scalable Formal Verification of Leakage in Symbolic ExpressionsIEEE Transactions on Software Engineering10.1109/TSE.2023.3252671(1-16)Online publication date: 2023
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cover image ACM Other conferences
DAC '14: Proceedings of the 51st Annual Design Automation Conference
June 2014
1249 pages
ISBN:9781450327305
DOI:10.1145/2593069
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 June 2014

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Author Tags

  1. SMT solver
  2. Side channel attack
  3. countermeasure
  4. differential power analysis
  5. quantitative masking strength

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Cited By

View all
  • (2024)Compositional Verification of First-Order Masking Countermeasures against Power Side-Channel AttacksACM Transactions on Software Engineering and Methodology10.1145/363570733:3(1-38)Online publication date: 14-Mar-2024
  • (2024)Information-Theoretic EvaluationMathematical Foundations for Side-Channel Analysis of Cryptographic Systems10.1007/978-3-031-64399-6_5(221-266)Online publication date: 12-Jul-2024
  • (2023)LeakageVerif: Efficient and Scalable Formal Verification of Leakage in Symbolic ExpressionsIEEE Transactions on Software Engineering10.1109/TSE.2023.3252671(1-16)Online publication date: 2023
  • (2022)Cache Refinement Type for Side-Channel Detection of Cryptographic SoftwareProceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security10.1145/3548606.3560672(1583-1597)Online publication date: 7-Nov-2022
  • (2022)Symbolic Predictive Cache Analysis for Out-of-Order ExecutionFundamental Approaches to Software Engineering10.1007/978-3-030-99429-7_10(163-183)Online publication date: 29-Mar-2022
  • (2021)Cumulant Expansion of Mutual Information for Quantifying Leakage of a Protected Secret2021 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT45174.2021.9517886(2596-2601)Online publication date: 12-Jul-2021
  • (2020)SpecuSymProceedings of the ACM/IEEE 42nd International Conference on Software Engineering10.1145/3377811.3380428(1235-1247)Online publication date: 27-Jun-2020
  • (2020)Formal verification of masking countermeasures for arithmetic programsProceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering10.1145/3324884.3418920(1385-1387)Online publication date: 21-Dec-2020
  • (2020)Formal Verification of Masking Countermeasures for Arithmetic ProgramsIEEE Transactions on Software Engineering10.1109/TSE.2020.3008852(1-1)Online publication date: 2020
  • (2020)Moving Target Defense Mechanism for Side-Channel AttacksIEEE Systems Journal10.1109/JSYST.2019.292258914:2(1810-1819)Online publication date: Jun-2020
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