Comparative analysis of cybersecurity metrics to develop new hypotheses
Name
Madnick, Choucri, Li, Ferwerda (2011) Comparative analysis of cybersecurity.pdf
Description
Author's final manuscript.
Size
1.77 MB
Format
Adobe PDF
Checksum (MD5)
18d9bbd747467158f602326bc7c177ee
Author(s)
Madnick, Stuart E.
Choucri, Nazli
Li, Xitong
Ferwerda, Jeremy
Date Issued
November 2011
Publisher
© Elsevier B.V.
Citation
Madnick, S., Choucri, N., Li, X., & Ferwerda, J. (2011). Comparative analysis of cybersecurity metrics to develop new hypotheses. Proceedings of the Workshop on Information Security & Privacy (WISP2011) (Jointly hosted by AIS SIGSEC and IFIP TC11.1), Shanghai, China.
Version
Author's final manuscript.
Abstract
Few Internet security organizations provide comprehensive, detailed, and reliable quantitative metrics, especially in the international perspective across multiple countries, multiple years, and multiple categories. As common refrain to justify this situation, organizations ask why they should spend valuable time and resources collecting and standardizing data.
This report aims to provide an encouraging answer to this question by demonstrating the value that even limited metrics can provide in a comparative perspective. We present some findings generated through the use of a research tool, the Explorations in Cyber Internet Relations (ECIR) Data Dashboard. In essence, this dashboard consists of a simple graphing and analysis tool, coupled with a database consisting of data from disparate national-level cyber data sources provided by governments, Computer Emergency Response Teams (CERTs), and international organizations. Users of the dashboard can select relevant security variables, compare various countries, and scale information as needed.
In this paper, using this tool, we present an example of observations concerning the fight against cybercrime, along with several hypotheses attempting to explain the findings. We believe that these preliminary results suggest valuable ways in which such data could be used and we hope this research will help provide the incentives for organizations to increase the quality and quantity of standardized quantitative data available.
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