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The economic cost of publicly announced information security breaches: empirical evidence from the stock market*

Campbell, Katherine, Gordon, Lawrence A., Loeb, Martin P., Zhou, Lei·2003·Journal of Computer Security

Abstract

This study examines the economic effect of information security breaches reported in newspapers on publicly traded US corporations. We find limited evidence of an overall negative stock market reaction to public announcements of information security breaches. However, further investigation reveals that the nature of the breach affects this result. We find a highly significant negative market reaction for information security breaches involving unauthorized access to confidential data, but no significant reaction when the breach does not involve confidential information. Thus, stock market participants appear to discriminate across types of breaches when assessing their economic impact on affected firms. These findings are consistent with the argument that the economic consequences of information security breaches vary according to the nature of the underlying assets affected by the breach.

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Metadata

Authors
Campbell, K., Gordon, L. A., Loeb, M. P., & Zhou, L.
Venue
Journal of Computer Security
Published
2003-07-01
Volume
11
Issue
3
Pages
431-448
ISSN
  • 0926-227X (ISSN-L)
  • 1875-8924
OpenAlex
W1863670505
Cited by
735
References
0
FWCI
40.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The economic cost of publicly announced information security breaches: empirical evidence from the stock market*. https://app.cochat.ai/papers/10.3233/jcs-2003-11308
The paper
Campbell, K., Gordon, L. A., Loeb, M. P., & Zhou, L. (2003). The economic cost of publicly announced information security breaches: empirical evidence from the stock market*. Journal of Computer Security. https://doi.org/10.3233/jcs-2003-11308

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.