An Active Cyber Insurance Policy Against Cybersecurity Risks Using Fuzzy Q-Learning

an application of fuzzy logic for car insurance underwriting

در ایران بیمه خودرو سهم بزرگی در صنعت بیمه دارد. تعیین حق بیمه مناسب و عادلانه نیازمند طبقه بندی خریداران بیمه نامه براساس خطرات احتمالی آنها است. عوامل ریسکی فراوانی می تواند بر این قیمت گذاری تاثیر بگذارد. طبقه بندی و تعیین میزان تاثیر گذاری هر عامل ریسکی بر قیمت گذاری بیمه خودرو پیچیدگی خاصی دارد. در این پایان نامه سعی در ارائه راهی جدید برای طبقه بندی عوامل ریسکی با استفاده از اصول و روش ها...

Cyber-sword v. cyber-shield: The Dynamics of US Cybersecurity Policy Priorities

Recent efforts to address cybersecurity risks have focused on leveraging the immense technical capacity of the American intelligence community to protect the nation’s information technology infrastructure, and to project power in a new domain. This creates a potential conflict of interest: the joint duties of breaking into foreign systems while securing our own raises questions about competing ...

Anomaly Detection using Fuzzy Q-learning Algorithm

Wireless networks are increasingly overwhelmed by Distributed Denial of Service (DDoS) attacks by generating flooding packets that exhaust critical computing and communication resources of a victim’s mobile device within a very short period of time. This must be protected. Effective detection of DDoS attacks requires an adaptive learning classifier, with less computational complexity, and an ac...

Cyber Risk Exposure and Prospects for Cyber Insurance

This study draws attention to the ubiquitous and borderless nature of cybercrime. It examines the prospect of introducing customized cyber insurance policy in the Nigerian market. As secondary data was not available, the study conducted a survey by administering three sets of questionnaire to purposively selected top executives in four Trade Groups that rely heavily on Internet transactions for...

Cybersecurity Insurance: Modeling and Pricing