12,008 research outputs found
DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution
Recent research has demonstrated the vulnerability of fingerprint recognition
systems to dictionary attacks based on MasterPrints. MasterPrints are real or
synthetic fingerprints that can fortuitously match with a large number of
fingerprints thereby undermining the security afforded by fingerprint systems.
Previous work by Roy et al. generated synthetic MasterPrints at the
feature-level. In this work we generate complete image-level MasterPrints known
as DeepMasterPrints, whose attack accuracy is found to be much superior than
that of previous methods. The proposed method, referred to as Latent Variable
Evolution, is based on training a Generative Adversarial Network on a set of
real fingerprint images. Stochastic search in the form of the Covariance Matrix
Adaptation Evolution Strategy is then used to search for latent input variables
to the generator network that can maximize the number of impostor matches as
assessed by a fingerprint recognizer. Experiments convey the efficacy of the
proposed method in generating DeepMasterPrints. The underlying method is likely
to have broad applications in fingerprint security as well as fingerprint
synthesis.Comment: 8 pages; added new verification systems and diagrams. Accepted to
conference Biometrics: Theory, Applications, and Systems 201
Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction
Assessing systemic risk in financial markets is of great importance but it
often requires data that are unavailable or available at a very low frequency.
For this reason, systemic risk assessment with partial information is
potentially very useful for regulators and other stakeholders. In this paper we
consider systemic risk due to fire sales spillover and portfolio rebalancing by
using the risk metrics defined by Greenwood et al. (2015). By using the Maximum
Entropy principle we propose a method to assess aggregated and single bank's
systemicness and vulnerability and to statistically test for a change in these
variables when only the information on the size of each bank and the
capitalization of the investment assets are available. We prove the
effectiveness of our method on 2001-2013 quarterly data of US banks for which
portfolio composition is available.Comment: 36 pages, 6 figures, Accepted on Journal of Economic Dynamics and
Contro
A Hybrid Intelligent Early Warning System for Predicting Economic Crises: The Case of China
This paper combines artificial neural networks (ANN), fuzzy optimization and time-series econometric models in one unified framework to form a hybrid intelligent early warning system (EWS) for predicting economic crises. Using quarterly data on 12 macroeconomic and financial variables for the Chinese economy during 1999 and 2008, the paper finds that the hybrid model possesses strong predictive power and the likelihood of economic crises in China during 2009 and 2010 remains high.Computational intelligence; artificial neural networks; fuzzy optimization; early warning system; economic crises
On the simulation of the seismic energy transmission mechanisms
In recent years, considerable attention has been paid to research and
development methods able to assess the seismic energy propagation on the
territory. The seismic energy propagation is strongly related to the complexity
of the source and it is affected by the attenuation and the scattering effects
along the path. Thus, the effect of the earthquake is the result of a complex
interaction between the signal emitted by the source and the propagation
effects. The purpose of this work is to develop a methodology able to reproduce
the propagation law of seismic energy, hypothesizing the "transmission"
mechanisms that preside over the distribution of seismic effects on the
territory, by means of a structural optimization process with a predetermined
energy distribution. Briefly, the approach, based on a deterministic physical
model, determines an objective correction of the detected distributions of
seismic intensity on the soil, forcing the compatibility of the observed data
with the physical-mechanical model. It is based on two hypotheses: (1) the
earthquake at the epicentre is simulated by means of a system of distortions
split into three parameters; (2) the intensity is considered coincident to the
density of elastic energy. The optimal distribution of the beams stiffness is
achieved, by reducing the difference between the values of intensity
distribution computed on the mesh and those observed during four regional
events historically reported concerning the Campania region (Italy)
Pseudo-Separation for Assessment of Structural Vulnerability of a Network
Based upon the idea that network functionality is impaired if two nodes in a
network are sufficiently separated in terms of a given metric, we introduce two
combinatorial \emph{pseudocut} problems generalizing the classical min-cut and
multi-cut problems. We expect the pseudocut problems will find broad relevance
to the study of network reliability. We comprehensively analyze the
computational complexity of the pseudocut problems and provide three
approximation algorithms for these problems.
Motivated by applications in communication networks with strict
Quality-of-Service (QoS) requirements, we demonstrate the utility of the
pseudocut problems by proposing a targeted vulnerability assessment for the
structure of communication networks using QoS metrics; we perform experimental
evaluations of our proposed approximation algorithms in this context
Some Remarks about the Complexity of Epidemics Management
Recent outbreaks of Ebola, H1N1 and other infectious diseases have shown that
the assumptions underlying the established theory of epidemics management are
too idealistic. For an improvement of procedures and organizations involved in
fighting epidemics, extended models of epidemics management are required. The
necessary extensions consist in a representation of the management loop and the
potential frictions influencing the loop. The effects of the non-deterministic
frictions can be taken into account by including the measures of robustness and
risk in the assessment of management options. Thus, besides of the increased
structural complexity resulting from the model extensions, the computational
complexity of the task of epidemics management - interpreted as an optimization
problem - is increased as well. This is a serious obstacle for analyzing the
model and may require an additional pre-processing enabling a simplification of
the analysis process. The paper closes with an outlook discussing some
forthcoming problems
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