Towards Detection of Unknown Polymorphic Patterns Using Prior Knowledge
Ładowanie...
Data
2023
Autorzy
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
The presented paper proposes a novel approach for detecting unknown
polymorphic patterns in sequences composed of random symbols and
of known polymorphic patterns. We propose to represent rules that drive
pattern generation as regular expressions. To detect unknown patterns, we
first incorporate knowledge on known rules into a Convolutional Autoencoder
(CAE), then we train the CAE with additional objective to prevent
weights from learning the already known patterns. Analysis of training results
provides statistically significant information on presence or absence of
polymorphic patterns that were not previously known.
Opis
Słowa kluczowe
polymorphic pattern detection, knowledge and learning integration, Convolutional Autoencoder, wykrywanie wzorców polimorficznych, integracja wiedzy i uczenia się, autoenkoder konwolucyjny
Cytowanie
Kucharski P., Ślot K., Towards Detection of Unknown Polymorphic Patterns Using Prior Knowledge. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 131-136, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.19.