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A Qualitative Empirical Analysis of Human Post-Exploitation Behavior
Honeypots are a well-studied defensive measure in network security.
Cryptography and Security Computer Science and Game Theory
Using Temporal and Topological Features for Intrusion Detection in Operational Networks
Industrial systems are commonly used for several decades, updates are often difficult and expensive.
Evaluation of Machine Learning-based Anomaly Detection Algorithms on an Industrial Modbus/TCP Data Set
In the context of the Industrial Internet of Things, communication technology, originally used in home and office environments, is introduced into industrial applications.
Highly Scalable and Flexible Model for Effective Aggregation of Context-based Data in Generic IIoT Scenarios
To keep track of this data in order to detect attacks and errors in the production site, it is necessary to smartly aggregate and evaluate the data.
Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data
Matrix Profiles perform well with almost no parameterisation needed.
