| Title | Modelling Cyber-Risk in an Economic Perspective |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Bothos, Ioannis, Vlachos, Vasileios, Kyriazanos, Dimitris M., Stamatiou, Ioannis, Thanos, Konstantinos Georgios, Tzamalis, Pantelis, Nikoletseas, Sotirios, Thomopoulos, Stelios C.A. |
| Conference Name | 2021 IEEE International Conference on Cyber Security and Resilience (CSR) |
| Keywords | Adaptation models, Analytical models, artificial intelligence, assessment, Biological system modeling, bug-bounties, cyber-security, data mining, Deep Learning, econometrics, human factors, machine learning, Management, Metrics, pubcrawl, resilience, risk, Scalability, Security Risk Estimation, Time series analysis, time-series, Training, vulnerabilities |
| Abstract | In this paper, we present a theoretical approach concerning the econometric modelling for the estimation of cyber-security risk, with the use of time-series analysis methods and alternatively with Machine Learning (ML) based, deep learning methodology. Also we present work performed in the framework of SAINT H2020 Project [1], concerning innovative data mining techniques, based on automated web scrapping, for the retrieving of the relevant time-series data. We conclude with a review of emerging challenges in cyber-risk assessment brought by the rapid development of adversarial AI. |
| DOI | 10.1109/CSR51186.2021.9527994 |
| Citation Key | bothos_modelling_2021 |
Modelling Cyber-Risk in an Economic Perspective