02179naa a22003858i 4500 5328 5328 00005328 FR-PaOEC 20211006062617.0 a o d i cr || |||m|n|| 190601s2018 ||| o i|0| 0 eng d (FR-PaOEC) FR-PaOEC ES-MaONT Bothos, John M.A. 3365 Correlation and dependence analysis on cyberthreat alerts / John M.A. Bothos ... [el al.] Geneva : International Telecommunication Union, 2018. 7 p. texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier In this paper, a methodology for the enhancement of computer networks' cyber-defense is presented. Using a time-series dataset, drawn for a 60-day period and for 12 hours per day and depicting the occurrences of cyberthreat alerts at hourly intervals, the correlation and dependency coefficients that occur in an organization's network between different types of cyberthreat alerts are determined. Certain mathematical methods like the Spearman correlation coefficient and the Poisson regression stochastic model are used. For certain types of cyberthreat alerts, results show a significant positive correlation and dependence between them. The analysis methodology presented could help the administrative and IT managers of an organization to implement organizational policies for cybersecurity. Tecnologías habilitadoras digitales 18 Science and Technology Thanos, Konstantinos-Georgios 3366 Kyriazanos, Dimitris M. 3367 Vardoulias, George 3368 Zalonis, Andreas 3369 Papadopoulou, Eirini 3370 Corovesis, Yannis 3371 Thomopoulos, Stelios C.A. 3372 4843 ITU Journal: ICT Discoveries Vol. 2018, no. 1, p. 129-135 2018:1<129 2616-8375 itu-ilibrary.org https://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2018-15-PDF-E.pdf Acceso al documento 0 pdf ART udc 0 0 0 3 1 6278 01 01 online 2019-09-12 0 1000020175577 2019-09-12 00:00:00 2019-09-12 ART