Modelling Cyber-Risk in an Economic Perspective

Ioannis Bothos, Vasileios Vlachos, D. Kyriazanos, I. Stamatiou, K. Thanos, Pantelis Tzamalis, Sotirios E. Nikoletseas, S. Thomopoulos
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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.
经济视角下的网络风险建模
在本文中,我们提出了一种关于估计网络安全风险的计量经济学建模的理论方法,使用时间序列分析方法,或者使用基于机器学习(ML)的深度学习方法。此外,我们还介绍了在SAINT H2020项目[1]框架下进行的工作,该项目涉及基于自动web抓取的创新数据挖掘技术,用于检索相关时间序列数据。最后,我们回顾了对抗性人工智能的快速发展给网络风险评估带来的新挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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