Statistical Machine Learning Analysis of Cyber Risk Data: Event Case Studies

27 Pages Posted: 21 Nov 2017 Last revised: 22 Feb 2018

See all articles by Gareth Peters

Gareth Peters

Department of Actuarial Mathematics and Statistics, Heriot-Watt University; University College London - Department of Statistical Science; University of Oxford - Oxford-Man Institute of Quantitative Finance; London School of Economics & Political Science (LSE) - Systemic Risk Centre; University of New South Wales (UNSW) - Faculty of Science

Pavel V. Shevchenko

Macquarie University; Macquarie University, Macquarie Business School

Ruben Cohen

Independent

Diane Maurice

Central Bank of Tunisia

Multiple version iconThere are 2 versions of this paper

Date Written: November 18, 2017

Abstract

This work explores the common attributes of different types of cyber risk with a view to better understanding the key attributes that contribute to each type of cyber risk category. In doing so we will explore event studies on a range of different market sectors, different countries, different demographics over time and categories of cyber risk event type.

To perform this study we will explore a modern machine learning based clustering method to explore the attributes of cyber risk and how they statistically can be categorized. We will then explore the properties of this statistics classification and interpret its implications for the current taxonomies being developed for this area of risk management.

In the process we will interpret and analyze the implications our analysis has on both operational risk modelling of cyber risk data, as well as the implications the findings have for cyber risk insurance products.

Keywords: Cyber Risk, Cyber Crime, Operational Risk, Cyber Insurance, Kernel K-Means, Clustering, Cyber Empirical Studies

Suggested Citation

Peters, Gareth and Shevchenko, Pavel V. and Cohen, Ruben and Maurice, Diane, Statistical Machine Learning Analysis of Cyber Risk Data: Event Case Studies (November 18, 2017). Available at SSRN: https://ssrn.com/abstract=3073704 or http://dx.doi.org/10.2139/ssrn.3073704

Gareth Peters (Contact Author)

Department of Actuarial Mathematics and Statistics, Heriot-Watt University ( email )

Edinburgh Campus
Edinburgh, EH14 4AS
United Kingdom

HOME PAGE: http://garethpeters78.wixsite.com/garethwpeters

University College London - Department of Statistical Science ( email )

1-19 Torrington Place
London, WC1 7HB
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

University of Oxford Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

London School of Economics & Political Science (LSE) - Systemic Risk Centre ( email )

Houghton St
London
United Kingdom

University of New South Wales (UNSW) - Faculty of Science ( email )

Australia

Pavel V. Shevchenko

Macquarie University ( email )

North Ryde
Sydney, New South Wales 2109
Australia

HOME PAGE: http://www.businessandeconomics.mq.edu.au/contact_the_faculty/all_fbe_staff/pavel_shevchenko

Macquarie University, Macquarie Business School ( email )

New South Wales 2109
Australia

Ruben Cohen

Independent ( email )

No Address Available

Diane Maurice

Central Bank of Tunisia ( email )

1080 Tunis
Tunisia

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