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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 ...
The MANTIS Book. Cyber Physical System Based Proactive Collaborative Maintenance
(River Publishers, 2018)
Success Stories on Real Pilots
(River Publishers, 2018)
A study of the personalization of spam content using Facebook public information
(Oxford University Press, 2017)
Millions of users per day are affected by unsolicited email campaigns. Spam filters are capable of detecting and avoiding an increasing number of messages, but researchers have quantified a response rate of a 0.006% [1], ...
A Mood Analysis on Youtube Comments and a Method for Improved Social Spam Detection
(Springer, 2018)
In the same manner that Online Social Networks (OSN) usage increases, non-legitimate campaigns over these types of web services are growing. This is the reason why signi cant number of users are affected by social spam ...
Null is Not Always Empty: Monitoring the Null Space for Field-Level Anomaly Detection in Industrial IoT Environments
(IEEE, 2018)
Industrial environments have vastly changed sincethe conception of initial primitive and isolated networks. Thecurrent full interconnection paradigm, where connectivity be-tween different devices and the Internet has become ...
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). ...
SDRS: A new lossless dimensionality reduction for text corpora
(Elsevier Ltd., 2020)
In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, ...
Interpreting Remaining Useful Life estimations combining Explainable Artificial Intelligence and domain knowledge in industrial machinery
(IEEE, 2020)
This paper presents the implementation and explanations of a remaining life estimator model based on machine learning, applied to industrial data. Concretely, the model has been applied to a bushings testbed, where fatigue ...