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Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. On the Identification of Decision Boundaries for Anomaly Detection in CPPS
 Institute of Electrical and Electronics Engineers IEEE; IEEE Industrial Electronics Society IES; Federation University Australia: IEEE International Conference on Industrial Technology, ICIT 2019. Proceedings : Melbourne, Australia, 1315 February 2019 Piscataway, NJ: IEEE, 2019 ISBN: 9781538663769 ISBN: 9781538663752 ISBN: 9781538663776 pp.13111316 
 International Conference on Industrial Technology (ICIT) <20, 2019, Melbourne> 
 Bundesministerium für Bildung und Forschung BMBF (Deutschland) 03PSIPT5B 

 English 
 Conference Paper 
 Fraunhofer IOSB () 
Abstract
In this work, a new datadriven approach to anomaly detection in CyberPhysicalProductionSystems (CPPS) is developed, which uses the geometric structure nonconvex hull to build a decision boundary for the classification of new observations. A novel algorithm based on MixtureofExperts model is presented to estimate ndimensional nonconvex hulls. Furthermore, a new method is proposed to solve the point in nonconvex hull problem. With these two methods in hand, a novel algorithm for anomaly detection is developed. Compared with convex hulls based anomaly detection methods, our approach can handle data sets with arbitrary shapes. Since the presented geometric approach does not make any assumption about either the probability density or the structure of given data, it can be combined with different machine learning algorithms. The effectiveness of this approach is evaluated with real world data collected from wind turbines.