Detection of Unknown Polymorphic Patterns Using Feature-Extracting Part of a Convolutional Autoencoder
Background: The present paper proposes a novel approach for detecting the presence of unknown polymorphic patterns in random symbol sequences that also comprise already known polymorphic patterns. Methods: We propose to represent rules that define the considered patterns as regular expressions and s...
Main Authors: | Przemysław Kucharski, Krzysztof Ślot |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-09-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/19/10842 |
Similar Items
-
Unsupervised Domain Adaptation via Stacked Convolutional Autoencoder
by: Yi Zhu, et al.
Published: (2022-12-01) -
A Convolutional Autoencoder Based Fault Diagnosis Method for a Hydraulic Solenoid Valve Considering Unknown Faults
by: Seungjin Yoo, et al.
Published: (2023-08-01) -
Convolutional Autoencoding of Small Targets in the Littoral Sonar Acoustic Backscattering Domain
by: Timothy J. Linhardt, et al.
Published: (2022-12-01) -
1D Convolutional Autoencoder-Based PPG and GSR Signals for Real-Time Emotion Classification
by: Dong-Hyun Kang, et al.
Published: (2022-01-01) -
DOA Estimation Based on Convolutional Autoencoder in the Presence of Array Imperfections
by: Dah-Chung Chang, et al.
Published: (2023-02-01)