Abstract
Intrusion detection and prevention are necessary security measures for modern systems and networks which provide the services we use every day. This survey will attempt to provide a comprehensive overview on modern Intrusion Detection and Prevention Systems. Included will be a summarization of the literature which was studied from and sources which aide that research. The topics which are described within this survey involve implementing new Intrusion Detection and Prevention System (IDPS) architectures, methodologies, and polymerizing different technologies to create new methods of automated detection and prevention. Among these topics are implementations of Network IDPSs, creation of algorithms for Industrial Network Intrusion Detection Systems, generation of benchmark datasets for training Machine Learning models, creating new datasets for training Machine Learning models, using Neural Network models to create automated IDPSs, protecting Smart Grid technologies using IDPS, and implementing Intrusion Detection and Prevention tools using microcomputers.
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