@InProceedings{MachicaoBrun:2018:FiPaEx,
author = "Machicao, Jeaneth and Bruno, Odemir M.",
affiliation = "{Instituto de F{\'{\i}}sica de S{\~a}o Carlos} and {Instituto
de F{\'{\i}}sica de S{\~a}o Carlos}",
title = "Finding Patterns and Exploiting Pseudo-randomness using Complex
Systems",
booktitle = "Proceedings...",
year = "2018",
editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and
Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and
Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez,
Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de
and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa,
Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus,
Klaus de and Scheer, Sergio",
organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "patterns, pseudo-randomness, pattern recognition, complex systems,
chaos theory.",
abstract = "In this work, we present patterns and pseudo-randomness in an
approach that relates both concepts, which traditionally are seen
as opposites. This approach uses the mathematical basis of complex
systems for two purposes: to exploit the spectrum of
pseudo-randomness of chaotic systems in a quest to achieve true
randomness and, the development of pattern recognition methods
based on artificial life in complex networks that finally
intertwined the search for patterns in pseudo-random sequences. In
the first part, we developed a method to explore the depth
properties of chaotic systems, specifically in the logistic map
and tent map, as sources of pseudo-randomness. We observe that the
patterns disappear and the pseudo-randomness is increased by
removing k-digits to the right of the decimal separator of the
chaotic orbits. Thus, a rapid transition from {"}weak to strong{"}
randomness was evidenced as k tends to infinity, which allows a
parametrically pseudo-randomness. In the second part, it was
proposed the combination of cellular automata in the network
topology (also called network-automata), to characterize networks
in a pattern recognition context. Four problems were explored:
identifying online social networks; identify organisms from
different domains of life through their metabolic networks; the
problem of authorship identification; and classifying stomatal
distribution patterns varying according to different environmental
conditions. Finally, this same approach was used to analyze the
sequences of pseudo-random numbers generated by the gold standard
k-logistic map PRNG in a context of pattern recognition. The
proposed approach allowed to explore patterns and
pseudo-randomness extracted from a myriad of systems with
successful results in terms of accuracy and good
pseudo-randomness. This work has brought significant advances in
real-world pattern recognition tasks across a wide range of fields
such as cryptography, cryptoanalysis, biology, and data science.",
conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
conference-year = "29 Oct.-1 Nov. 2018",
language = "en",
ibi = "8JMKD3MGPAW/3S3E6JL",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3S3E6JL",
targetfile = "camara-ready.pdf",
urlaccessdate = "2024, Apr. 28"
}