I nformation security investment has been getting increasing attention in recent years. Various methods have been proposed to determine the effective level of security investment. However, traditional expected value methods (such as annual loss expectancy) cannot fully characterize the information security risk confronted by organizations, considering some extremal yet perhaps relatively rare cases in which a security failure may be critical and cause high losses. In this research note we introduce the concept of value-at-risk to measure the risk of daily losses an organization faces due to security exploits and use extreme value analysis to quantitatively estimate the value at risk. We collect a set of internal daily activity data from a large financial institution in the northeast United States and then simulate its daily losses with information based on data snapshots and interviews with security managers at the institution. We illustrate our methods using these simulated daily losses. With this approach, decision makers can make a proper investment choice based on their own risk preference instead of pursuing a solution that minimizes only the expected cost.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.