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Intrusion detection algorithm based on OCSVM in industrial control system

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-27186-1_8openalex-snapshot
Optimization Conditions of OCSVM for Erroneous GPS Data Filtering
inferredcites →https://doi.org/10.1007/978-3-642-34500-5_33openalex-snapshot
Analysis of Intrusion Detection in Control System Communication Based on Outlier Detection with One-Class Classifiers
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Detecting Abnormal Behavior in SCADA Networks Using Normal Traffic Pattern Learning
inferredcites →https://doi.org/10.1007/s11071-010-9851-yopenalex-snapshot
Local density one-class support vector machines for anomaly detection
inferredcites →https://doi.org/10.1016/j.cose.2008.08.003openalex-snapshot
Anomaly-based network intrusion detection: Techniques, systems and challenges
inferredcites →https://doi.org/10.1016/j.cose.2014.06.006openalex-snapshot
Selection of Candidate Support Vectors in incremental SVM for network intrusion detection
inferredcites →https://doi.org/10.1016/j.eswa.2013.08.066openalex-snapshot
A novel hybrid intrusion detection method integrating anomaly detection with misuse detection
inferredcites →https://doi.org/10.1016/j.ins.2013.12.019openalex-snapshot
Clustering-based ensembles for one-class classification
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Two methods of selecting Gaussian kernel parameters for one-class SVM and their application to fault detection
inferredcites →https://doi.org/10.1016/j.neucom.2007.11.023openalex-snapshot
Kernel-based online machine learning and support vector reduction
inferredcites →https://doi.org/10.1016/j.patcog.2009.09.003openalex-snapshot
Optimal feature selection for support vector machines
inferredcites →https://doi.org/10.1016/j.patrec.2009.05.007openalex-snapshot
Least squares one-class support vector machine
inferredcites →https://doi.org/10.1049/el.2014.2897openalex-snapshot
Integrated OCSVM mechanism for intrusion detection in SCADA systems
inferredcites →https://doi.org/10.1109/cyberc.2013.22openalex-snapshot
Anomaly Detection via One Class SVM for Protection of SCADA Systems
inferredcites →https://doi.org/10.1109/icassp.2013.6638322openalex-snapshot
A new one-class SVM for anomaly detection
inferredcites →https://doi.org/10.1109/ijcnn.2014.6889583openalex-snapshot
Kernel-based semi-supervised learning for novelty detection
inferredcites →https://doi.org/10.1109/issnip.2007.4496866openalex-snapshot
Detecting Selective Forwarding Attacks in Wireless Sensor Networks using Support Vector Machines
inferredcites →https://doi.org/10.1109/nss.2009.82openalex-snapshot
Building a SCADA Security Testbed
inferredcites →https://doi.org/10.1109/ntms.2011.5720582openalex-snapshot
Inductive Intrusion Detection in Flow-Based Network Data Using One-Class Support Vector Machines
inferredcites →https://doi.org/10.1109/ths.2012.6459831openalex-snapshot
A transfer function based intrusion detection system for SCADA systems
inferredcites →https://doi.org/10.1145/2500853.2500857openalex-snapshot
Enhancing one-class support vector machines for unsupervised anomaly detection
inferredcites →https://doi.org/10.14236/ewic/icscsr2013.12openalex-snapshot
Intrusion Detection via Machine Learning for SCADA System Protection
inferredcites →https://doi.org/10.14569/ijarai.2014.031006openalex-snapshot
A real time OCSVM Intrusion Detection module with low overhead for SCADA systems
inferredcites →https://doi.org/10.4028/www.scientific.net/amm.490-491.1745openalex-snapshot
Modbus/TCP Communication Anomaly Detection Based on PSO-SVM

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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