@article{Lakhno_Kazmirchuk_Kovalenko_Myrutenko_Zhmurko_2016, title={Design of adaptive system of detection of cyber-attacks, based on the model of logical procedures and the coverage matrices of features}, volume={3}, url={https://journals.uran.ua/eejet/article/view/71769}, DOI={10.15587/1729-4061.2016.71769}, abstractNote={<p>The results of the research aimed at the further development of detection models of cyber threats, as well as of common classes of anomalies and cyber-attacks in mission critical computer systems (MCCS) are presented.</p><p>It is shown that one of the promising directions of synthesis of adaptive systems of detection and prevention of cyber-attacks is the application of models of logical procedures of detection, based on the coverage matrices of features of anomalies, threats and cyber-attacks within the known and new classes of the MCCS intrusions.    The model of detection of cyber-attacks, anomalies and threats to MCCS was designed, which is based on the application of learning samples in the form of matrices of features and elementary classifiers for each of the modeled classes.</p><p>The studies on minimization of the number of training samples, represented in a binary form of discerning features were carried out. The program "Threat Analyzer” was developed which allows automatic generation of dimensions of training matrix of features of anomalies, cyber threats, or cyber-attacks, without requiring the participation of experts.</p><p>It is shown that for the object detection within known classes of cyber threats, attacks, anomalies, the usage in the training matrices of representative sets of 3-4 features long allows maximizing the effectiveness of the algorithm, reaching up to 98 %. </p>}, number={9(81)}, journal={Eastern-European Journal of Enterprise Technologies}, author={Lakhno, Valeriy and Kazmirchuk, Svitlana and Kovalenko, Yulia and Myrutenko, Larisa and Zhmurko, Tetyana}, year={2016}, month={Jun.}, pages={30–38} }