Anomaly Detection in Smart Industrial Machinery through Hidden Markov Models and Autoencoders

R Sorostinean, Z Burghelea, A Gellert - IEEE Access, 2024 - ieeexplore.ieee.org
This study addresses the need to develop a sustainable manufacturing process in industrial
factories, as the industry desires to remain competitive while it is challenged to adopt eco …

Network anomaly detection by continuous hidden markov models: An evolutionary programming approach

JJ Flores, F Calderon, A Antolino… - Intelligent Data …, 2015 - content.iospress.com
Abstract Information security is an important and growing need. The most common schemes
used for detection systems include pattern-or signature-based and anomaly-based …

[PDF][PDF] Evolving hidden Markov models for network anomaly detection

JJ Flores, A Antolino, JM Garcia - … International Conference on …, 2010 - datascienceassn.org
This paper reports the results of a system that performs network anomaly detection through
the use of Hidden Markov Models (HMMs). The HMMs used to detect anomalies are …

[PDF][PDF] Hybrid network anomaly detection–learning hmms through evolutionary computation

JJ Flores, A Antolino, JM Garcia, FC Solorio - 2012 - academia.edu
Security threats for computer systems have increased immensely; these threats include
virus, denial of service, vulnerability break-in, etc. While many security mechanisms have …

Discrete fuzzy transform applied to computer anomaly detection

JMG Garcia - 2011 Annual Meeting of the North American …, 2011 - ieeexplore.ieee.org
Intrusion detection systems (IDS) are widely applied to computer networks and systems as
an information security control. Most of the current IDS work by detecting patterns of …