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Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends
(The Wiley Hindawi Partnership, 2017)
Industrial Networks (INs) are widespread environments where heterogeneous devices collaborate to control and monitor physical
processes. Some of the controlled processes belong to Critical Infrastructures (CIs), and, as ...
Deobfuscating leetspeak with deep learning to improve spam filtering
(UNIR - Universidad Internacional de La Rioja, 2023)
The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are ...
Different approaches for the detection of SSH anomalous connections
(Oxford Academic, 2016)
The Secure Shell Protocol (SSH) is a well-known standard protocol, mainly used for remotely accessing shell accounts on Unix-like operating systems to perform administrative tasks. As a result, the SSH service has been an ...
A neural-visualization IDS for honeynet data
(World Scientific, 2012)
Neural intelligent systems can provide a visualization of the network traffic for security staff, in order to reduce the widely known high false-positive rate associated with misuse-based Intrusion Detection Systems (IDSs). ...
Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge
(Taylor and Francis, 2022)
The 4th industrial revolution has connected machines and industrial plants, facilitating process monitoring and the implementation of predictive maintenance (PdM) systems that can save up to 60% of maintenance costs. ...
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
(Springer Science+Business Media, LLC, 2022)
Given the growing amount of industrial data in the 4th industrial revolution, deep learning solutions have become popular for predictive maintenance (PdM) tasks, which involve monitoring assets to anticipate their requirements ...
Adaptable and Explainable Predictive Maintenance: Semi-Supervised Deep Learning for Anomaly Detection and Diagnosis in Press Machine Data
(MDPI, 2021)
Predictive maintenance (PdM) has the potential to reduce industrial costs by anticipating failures and extending the work life of components. Nowadays, factories are monitoring their assets and most collected data belong ...
Software-Defined Networking approaches for intrusion response in Industrial Control Systems: A survey
(Elsevier, 2023)
Industrial Control Systems (ICSs) are a key technology for life-sustainability, social development and economic progress used in a wide range of industrial solutions, including Critical Infrastructures (CIs), becoming the ...
Deep packet inspection for intelligent intrusion detection in software-defined industrial networks: A proof of concept
(Oxford Academic, 2020)
Specifically tailored industrial control systems (ICSs) attacks are becoming increasingly sophisticated, accentuating the need of ICS cyber security. The nature of these systems makes traditional IT security measures not ...
On the use of MiniCPS for conducting rigorous security experiments in Software-Defined Industrial Control Systems
(Springer, 2024)
Software-Defined Networking (SDN) offers a global view over the network and the ability of centrally and dynamically managing network flows, making them ideal for creating security threat detection and mitigation solutions. ...
