8,349 research outputs found
Quantifying Shannon's Work Function for Cryptanalytic Attacks
Attacks on cryptographic systems are limited by the available computational
resources. A theoretical understanding of these resource limitations is needed
to evaluate the security of cryptographic primitives and procedures. This study
uses an Attacker versus Environment game formalism based on computability logic
to quantify Shannon's work function and evaluate resource use in cryptanalysis.
A simple cost function is defined which allows to quantify a wide range of
theoretical and real computational resources. With this approach the use of
custom hardware, e.g., FPGA boards, in cryptanalysis can be analyzed. Applied
to real cryptanalytic problems, it raises, for instance, the expectation that
the computer time needed to break some simple 90 bit strong cryptographic
primitives might theoretically be less than two years.Comment: 19 page
Quantifying Resource Use in Computations
It is currently not possible to quantify the resources needed to perform a
computation. As a consequence, it is not possible to reliably evaluate the
hardware resources needed for the application of algorithms or the running of
programs. This is apparent in both computer science, for instance, in
cryptanalysis, and in neuroscience, for instance, comparative neuro-anatomy. A
System versus Environment game formalism is proposed based on Computability
Logic that allows to define a computational work function that describes the
theoretical and physical resources needed to perform any purely algorithmic
computation. Within this formalism, the cost of a computation is defined as the
sum of information storage over the steps of the computation. The size of the
computational device, eg, the action table of a Universal Turing Machine, the
number of transistors in silicon, or the number and complexity of synapses in a
neural net, is explicitly included in the computational cost. The proposed cost
function leads in a natural way to known computational trade-offs and can be
used to estimate the computational capacity of real silicon hardware and neural
nets. The theory is applied to a historical case of 56 bit DES key recovery, as
an example of application to cryptanalysis. Furthermore, the relative
computational capacities of human brain neurons and the C. elegans nervous
system are estimated as an example of application to neural nets.Comment: 26 pages, no figure
The acoustic contrast between the Dutch consonants /t/ and /d/ is reduced in tracheoesophageal speech
Detecting and analysing spontaneous oral cancer speech in the wild
Oral cancer speech is a disease which impacts more than half a million people
worldwide every year. Analysis of oral cancer speech has so far focused on read
speech. In this paper, we 1) present and 2) analyse a three-hour long
spontaneous oral cancer speech dataset collected from YouTube. 3) We set
baselines for an oral cancer speech detection task on this dataset. The
analysis of these explainable machine learning baselines shows that sibilants
and stop consonants are the most important indicators for spontaneous oral
cancer speech detection.Comment: Accepted to Interspeech 202
Residual networks for resisting noise: analysis of an embeddings-based spoofing countermeasure
Scoring and Classifying Implicit Positive Interpretations:A Challenge of Class Imbalance
This paper reports on a reimplementation of a system on detecting implicit positive meaning from negated statements. In the original regression experiment, different positive interpretations per negation are scored according to their likelihood. We convert the scores to classes and report our results on both the regression and classification tasks. We show that a baseline taking the mean score or most frequent class is hard to beat because of class imbalance in the dataset. Our error analysis indicates that an approach that takes the information structure into account (i.e. which information is new or contrastive) may be promising, which requires looking beyond the syntactic and semantic characteristics of negated statements
Hall viscosity from gauge/gravity duality
In (2+1)-dimensional systems with broken parity, there exists yet another
transport coefficient, appearing at the same order as the shear viscosity in
the hydrodynamic derivative expansion. In condensed matter physics, it is
referred to as "Hall viscosity". We consider a simple holographic realization
of a (2+1)-dimensional isotropic fluid with broken spatial parity. Using
techniques of fluid/gravity correspondence, we uncover that the holographic
fluid possesses a nonzero Hall viscosity, whose value only depends on the
near-horizon region of the background. We also write down a Kubo's formula for
the Hall viscosity. We confirm our results by directly computing the Hall
viscosity using the formula.Comment: 12 page
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