Abstract
Objective: The harm that can be done to an information technology system is referred to as "information security risk" (IS). Data breaches, administrative actions, financial expenses, and reputational harm are just a few of the many possible dangers that fall under the broad category of information systems risks. IS hazards include hostile assaults, spam, viruses, human error, hardware and software malfunctions, and natural disasters like floods, hurricanes, and fires. Methods: Key security controls for applications are identified, evaluated, and implemented through security risk assessments. Another priority is to avoid security gaps and defects in software. This article analyzes documented historical research on natural disaster accounting. Based on the results of 35 publications on general topics, economic history, and accounting, 11 papers were selected and reviewed. By analyzing the scattered literature, emerging themes, investigated disasters, investigated time periods, and main contributions of published research were identified. Result: To compare the predictive capabilities of the machine learning models and validate the landslide, flood, and wildfire hazard maps, the area under the curve (AUC) was calculated. For the landslide, flood, and wildfire hazard maps, the RF model provided the highest AUC values (0.81, 0.85, and 0.94, respectively).
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