RCVaR: an Economic Approach to Estimate Cyberattacks Costs using Data from Industry Reports

by   Muriel Figueredo Franco, et al.

Digitization increases business opportunities and the risk of companies being victims of devastating cyberattacks. Therefore, managing risk exposure and cybersecurity strategies is essential for digitized companies that want to survive in competitive markets. However, understanding company-specific risks and quantifying their associated costs is not trivial. Current approaches fail to provide individualized and quantitative monetary estimations of cybersecurity impacts. Due to limited resources and technical expertise, SMEs and even large companies are affected and struggle to quantify their cyberattack exposure. Therefore, novel approaches must be placed to support the understanding of the financial loss due to cyberattacks. This article introduces the Real Cyber Value at Risk (RCVaR), an economical approach for estimating cybersecurity costs using real-world information from public cybersecurity reports. RCVaR identifies the most significant cyber risk factors from various sources and combines their quantitative results to estimate specific cyberattacks costs for companies. Furthermore, RCVaR extends current methods to achieve cost and risk estimations based on historical real-world data instead of only probability-based simulations. The evaluation of the approach on unseen data shows the accuracy and efficiency of the RCVaR in predicting and managing cyber risks. Thus, it shows that the RCVaR is a valuable addition to cybersecurity planning and risk management processes.


Cyber Risk Assessment for Capital Management

Cyber risk is an omnipresent risk in the increasingly digitized world th...

SECAdvisor: a Tool for Cybersecurity Planning using Economic Models

Cybersecurity planning is challenging for digitized companies that want ...

Planning routes in road freight minimizing logistical costs and accident risks

The Vehicle Routing Problem (VRP) has been widely studied throughout its...

Latent Bayesian Inference for Robust Earnings Estimates

Equity research analysts at financial institutions play a pivotal role i...

HurriCast: An Automatic Framework Using Machine Learning and Statistical Modeling for Hurricane Forecasting

Hurricanes present major challenges in the U.S. due to their devastating...

It's more than just money: The real-world harms from ransomware attacks

As cyber-attacks continue to increase in frequency and sophistication, o...

Where does the Stimulus go? Deep Generative Model for Commercial Banking Deposits

This paper examines deposits of individuals ("retail") and large compani...

Please sign up or login with your details

Forgot password? Click here to reset