Robust Personal Data Security in Insurance

This book explores the impact of Web 2.0 and the Fourth Industrial Revolution (4IR) on data security in Kenya's insurance sector, where vast volumes of personal data are processed daily. With increasing threats from malicious actors targeting online personal data, there is an urgent need for stronger, proactive, and intelligent security frameworks. The study investigates the integration of Digital Twin technology and multi-agent models into insurance data systems to reinforce protection strategies. Using a mixed-methods approach-descriptive surveys and quasi-experimental designs-data was gathered from selected Nairobi insurance firms. Tools such as R Script, Tableau, PyOD, MATLAB, and MTA-KDD-19 algorithms were used to analyze threats, detect anomalies, and simulate security models. Results revealed significant vulnerabilities, with existing mechanisms falling short of current cybersecurity standards. The findings advocate for advanced, AI-driven security frameworks to safeguard sensitive personal data in Kenya's evolving digital insurance landscape.