PRICING CYBERSECURITY INSURANCE RISK PREMIUM WITH MARKOV MODEL FOR SEVERAL NETWORK TOPOLOGIES

• Main Author: Josephine, Michelle
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/64805
• Institution: Institut Teknologi Bandung

During the COVID-19 pandemic, people are encouraged to keep their distance and do everything from home as much as possible. Nowadays, all activities can be done easily from home via online with the internet and information technologies that continue to grow in this digital era. As a result, internet users are increasing day by day, which causes the risk of financial losses due to cyber-attacks to also increase. This matter provides an opportunity for insurance companies to be able to develop insurance products as a protection against wealth in the form of digitally stored data. This final project discusses the financial loss model for several network topologies using the Markov approach. Furthermore, financial losses arising from cyber-attacks are assumed to be a proportion that follows the Beta distribution. From the financial loss model, the cybersecurity insurance risk premium will be calculated for several network topologies based on data from the Monte Carlo simulation. The cybersecurity insurance risk premium for each network topology will be calculated using two principles, namely the standard deviation principle and the equivalent utility principle. The result of this study indicates that the type of network topology used can affect the amount of financial loss due to the risk of cyber-attacks. The amount of financial loss can also be affected by the parameters used in the cybersecurity insurance scenario.