A. Kuznetsov, S. Kavun, Oleksii Smirnov, V. Babenko, O. Nakisko, K. Kuznetsova
{"title":"Malware Correlation Monitoring in Computer Networks of Promising Smart Grids","authors":"A. Kuznetsov, S. Kavun, Oleksii Smirnov, V. Babenko, O. Nakisko, K. Kuznetsova","doi":"10.1109/ESS.2019.8764228","DOIUrl":null,"url":null,"abstract":"The structure and features of the construction for intrusion detection and prevention network systems, as well as methods for the correlation analysis of telecommunication traffic in computer systems and networks are considered. Method for detecting malicious software based on the correlation analysis of network traffic is proposed. In particular, it is shown that using the results of statistical studies of time series on the basis of calculating the difference of correlation integrals (BDS-testing) allows to detect the malicious software traffic to improve the computer networks security of promising Smart Grids systems.","PeriodicalId":187043,"journal":{"name":"2019 IEEE 6th International Conference on Energy Smart Systems (ESS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 6th International Conference on Energy Smart Systems (ESS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESS.2019.8764228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
The structure and features of the construction for intrusion detection and prevention network systems, as well as methods for the correlation analysis of telecommunication traffic in computer systems and networks are considered. Method for detecting malicious software based on the correlation analysis of network traffic is proposed. In particular, it is shown that using the results of statistical studies of time series on the basis of calculating the difference of correlation integrals (BDS-testing) allows to detect the malicious software traffic to improve the computer networks security of promising Smart Grids systems.