PREDICTIVE CYBER INSURANCE POLICY ANALYSIS: ENHANCING CYBER SECURITY MANAGEMENT

Abstract

In today's world, the reality of modern cyberattacks and their severe impacts has become apparent, highlighting the fact that relying solely on risk mitigation measures is not enough for organizational cybersecurity management. As a result, cyber insurance has emerged as a necessary complement to existing safeguards. Some notable cybersecurity attacks with critical severity include WannaCry and NotPetya in 2017, which wreaked havoc on thousands of companies across various regions and industries. Additionally, there was a ransomware attack that affected major governmental organizations in the USA, such as the Departments of Defense, Homeland Security, State, Treasury, Energy, Commerce, and others. These incidents underscore the urgency of bolstering cybersecurity defenses. Today, the digital landscape is filled with advanced cyber threats of high severity, including crypto jacking, malware, supply-chain attacks, ransomware, business email compromise, and more. In this context, cyber insurance has gained increasing importance as organizations face the ever-growing menace of cyberattacks and data breaches. To address this critical issue, accurate prediction of cyber insurance policy patterns can play a vital role. By predicting these patterns, insurance companies can better assess risk, set appropriate premiums, and design effective coverage strategies. To achieve this, a novel methodology is proposed in this work, combining two powerful techniques: TF-IDF (Term Frequency-Inverse Document Frequency) feature extraction and a multinomial naive Bayes classifier. The TF-IDF algorithm is utilized to represent policy documents as numerical feature vectors, which capture the significance of terms within the documents. Subsequently, the multinomial naive Bayes classifier is employed to classify the policy patterns based on the extracted features. This approach presents a promising way to enhance cybersecurity management through predictive cyber insurance policy analysis. By leveraging advanced techniques and algorithms, organizations can better prepare themselves for potential cyber threats, making informed decisions to safeguard their interests and assets.