TY - GEN
T1 - Strong non-interference and type-directed higher-order masking
AU - Barthe, Gilles
AU - Belaïd, Sonia
AU - Dupressoir, François
AU - Fouque, Pierre Alain
AU - Grégoire, Benjamin
AU - Strub, Pierre Yves
AU - Zucchini, Rébecca
N1 - Publisher Copyright:
© 2016 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2016/10/24
Y1 - 2016/10/24
N2 - Differential power analysis (DPA) is a side-channel attack in which an adversary retrieves cryptographic material by measuring and analyzing the power consumption of the device on which the cryptographic algorithm under attack executes. An effective countermeasure against DPA is to mask secrets by probabilistically encoding them over a set of shares, and to run masked algorithms that compute on these encodings. Masked algorithms are often expected to provide, at least, a certain level of probing security. Leveraging the deep connections between probabilistic information flow and probing security, we develop a precise, scalable, and fully automated methodology to verify the probing security of masked algorithms, and generate them from unprotected descriptions of the algorithm. Our methodology relies on several contributions of independent interest, including a stronger notion of probing security that supports compositional reasoning, and a type system for enforcing an expressive class of probing policies. Finally, we validate our methodology on examples that go significantly beyond the state-of-the-art.
AB - Differential power analysis (DPA) is a side-channel attack in which an adversary retrieves cryptographic material by measuring and analyzing the power consumption of the device on which the cryptographic algorithm under attack executes. An effective countermeasure against DPA is to mask secrets by probabilistically encoding them over a set of shares, and to run masked algorithms that compute on these encodings. Masked algorithms are often expected to provide, at least, a certain level of probing security. Leveraging the deep connections between probabilistic information flow and probing security, we develop a precise, scalable, and fully automated methodology to verify the probing security of masked algorithms, and generate them from unprotected descriptions of the algorithm. Our methodology relies on several contributions of independent interest, including a stronger notion of probing security that supports compositional reasoning, and a type system for enforcing an expressive class of probing policies. Finally, we validate our methodology on examples that go significantly beyond the state-of-the-art.
U2 - 10.1145/2976749.2978427
DO - 10.1145/2976749.2978427
M3 - Conference contribution
AN - SCOPUS:84995528466
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 116
EP - 129
BT - CCS 2016 - Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery
T2 - 23rd ACM Conference on Computer and Communications Security, CCS 2016
Y2 - 24 October 2016 through 28 October 2016
ER -