Marcin Szpyrka

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Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly(More)
We propose a solution which provides a system operator with valuation of security risk introduced by various components of the communication and information system. This risk signature of the system enables the operator to make an informed decision about which network elements shall be used in order to provide a service requested by the user while(More)
BPMN is a leading visual notation for modeling business processes. Although there is many tools that allows for modeling using BPMN, they mostly do not support formal verification of models. The Alvis language was developed for modeling and verification of embedded systems. However, it is suitable for the modeling of any information systems with parallel(More)
The article describes the method of malware activities identification using ontology and rules. The method supports detection of malware at host level by observing its behavior. It sifts through hundred thousands of regular events and allows to identify suspicious ones. They are then passed on to the second building block responsible for malware tracking(More)
The exclusion rule-based system, proposed in the paper, is an alternative method of designing a rule-based system for an expert or a control system. The starting point of the approach is the set of all possible decisions the considered system can generate. Then, on the basis of the exclusion rules, the set of decisions is limited to the ones permissible in(More)