By Naofumi Homma, Marcel Medwed
This e-book constitutes the completely refereed post-conference lawsuits of the 14th foreign convention on shrewdpermanent Card examine and complicated purposes, CARDIS 2015, held in Bochum, Germany, in November 2015.
The 17 revised complete papers awarded during this e-book have been rigorously reviewed and chosen from forty submissions. the point of interest of the convention used to be on all facets of the layout, improvement, deployment, validation, and alertness of shrewdpermanent playing cards and safe parts in safe structures or systems.
Read or Download Smart Card Research and Advanced Applications: 14th International Conference, CARDIS 2015, Bochum, Germany, November 4-6, 2015. Revised Selected Papers PDF
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Extra info for Smart Card Research and Advanced Applications: 14th International Conference, CARDIS 2015, Bochum, Germany, November 4-6, 2015. Revised Selected Papers
As for PCA, this choice might not be optimal when applying this reduction to side-channel traces. For the sake of comparison, all the selection methods proposed for the PCA (EGV, IPR and ELV) will be tested in association to the LDA as well. In the following subsection we will present a well-known problem that aﬀects the LDA in many practical contexts, and describe four methods that circumvent such a problem, with the intention to test them over side-channel data. 1 The Small Sample Size Problem In the special case in which the matrix SB is invertible, the generalized eigenvalue problem is convertible in a regular one, as in .
27 %; it means that for a 512-bit dp , randomized with a 64-bit value, our framework commits approximately 11 errors. The above result (11 errors) implies that a brute-force attack is feasible to recover the correct exponent assuming that an attacker can determining the locations of possible errors. Our frameworks outputs not only the recovered exponent bits but also conﬁdence probabilities of the correct guesses (where 3 Observe that our framework can be also used to attack another exponentiation algorithms, square-and-multiply always , for instance.
The process continues n and the respective re-computation of iteratively with the re-deﬁnition of ri,j n means μk,j till convergence. Usually, the convergence is veriﬁed when the current and the previous means are equal. Fuzzy k-means [31,33] is an extension of k-means and compute the probability of a sample tni,j to belong to a cluster k. Now, the cluster parameter, or probabilities, are p(tni,j |μnk,j ) ∈ [0, 1]. (p(tni,j |μnk,j )) η−1 = (4) 2 (p(tni,j |μnk,j )) η−1 where η is free parameter and usually set to 2.