We leverage the Gibbs inequality and its natural generalization to Rényi entropies to derive closed-form parametric expressions of the optimal lower bounds of$\rho \text{th}$-order guessing entropy (guessing moment) of a secret taking values on a finite set, in terms of the Rényi-Arimoto$\alpha$-entropy. This is carried out in an non-asymptotic regime when side information may be available. The resulting bounds yield a theoretical solution to a fundamental problem in side-channel analysis: Ensure that an adversary will not gain much guessing advantage when the leakage information is sufficiently weakened by proper countermeasures in a given cryptographic implementation. Practical evaluation for classical leakage models show that the proposed bounds greatly improve previous ones for analyzing the capability of an adversary to perform side-channel attacks.

A common countermeasure against side-channel attacks on secret key cryptographic implementations is $d$ thorder masking, which splits each sensitive variable into $d + 1$ random shares. In this paper, maximal leakage bounds on the probability of success of any side-channel attack are derived for any masking order. Maximal leakage (Sibson's information of order infinity) is evaluated between the sensitive variable and the noisy leakage, and is related to the conditional "min-entropy" (Arimoto's entropy of order infinity) of the sensitive variable given the leakage. The latter conditional entropy is then lower-bounded in terms of the conditional entropies for each share using majorization inequalities. This yields a generalization of Mrs. Gerber's lemma for min-entropy in finite Abelian groups.

Embedded cryptographic devices are usually protected against side-channel attacks by masking strategies. In this paper, the security of protected cryptographic implementations is evaluated for any masking order, using alpha-information measures. Universal upper bounds on the probability of success of any type of side-channel attack are derived. These also provide lower bounds on the minimum number of queries required to achieve a given success rate. An important issue, solved in this paper, is to remove the loss factor due to the masking field size.

In a theoretical context of side-channel attacks, optimal bounds between success rate and guessing entropy are derived with a simple majorization (Schur-concavity) argument. They are further theoretically refined for different versions of the classical Hamming weight leakage model, in particular assuming a priori equiprobable secret keys and additive white Gaussian measurement noise. Closed-form expressions and numerical computation are given. A study of the impact of the choice of the substitution box with respect to side-channel resistance reveals that its nonlinearity tends to homogenize the expressivity of success rate and guessing entropy. The intriguing approximate relation$GE=1/SR$is observed in the case of 8-bit bytes and low noise.