Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-06T10:54:56.921Z Has data issue: false hasContentIssue false

30 - Near-Misses and Decision Making Under Uncertainty in the Context of Cybersecurity

Published online by Cambridge University Press:  13 December 2017

Ali E. Abbas
Affiliation:
University of Southern California
Milind Tambe
Affiliation:
University of Southern California
Detlof von Winterfeldt
Affiliation:
University of Southern California
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baron, J., & Hershey, J. C. (1988). Outcome bias in decision evaluation. Journal of Personality and Social Psychology, 54, 569579.CrossRefGoogle ScholarPubMed
Canfield, C., Fischhoff, B., & Davis, A. (2015). Using signal detection theory to measure phishing detection ability and behavior. Working paper, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
Dillon, R. L., & Tinsley, C. H. (2008). How near-misses influence decision making under risk: A missed opportunity for learning. Management Science, 54(8), 14251440.Google Scholar
Dillon, R. L., Tinsley, C. H., & Burns, W. J. (2014a). Evolving risk perceptions about near-miss terrorist events. Decision Analysis, 11(1), 2742.Google Scholar
Dillon, R. L., Tinsley, C. H., & Burns, W. J. (2014b). Near-misses and future disaster preparedness. Risk Analysis, 34(10), 19071922.Google Scholar
Dillon, R. L., Tinsley, C. H., & Cronin, M A. (2011). Why near-miss events can decrease an individual’s protective response to hurricanes. Risk Analysis, 31(3), 440449.CrossRefGoogle ScholarPubMed
Henneberger, M. (2014, February 5). Can credit card data breaches be prevented? The Washington Post. Accessed at: www.stltoday.com/business/local/can-credit-card-data-breaches-be-prevented/article_67246ae9-1325-581b-978d-9aeff021279c.html.Google Scholar
Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Science, 37(1), 1731.Google Scholar
Leonning, C. (2014, September 29). White House fence-jumper made it far deeper into building than previously known. The Washington Post. Accessed at: www .washingtonpost.com/politics/white-house-fence-jumper-made-it-far-deeper-into-building-than-previously-known/2014/09/29/02efd53e-47ea-11e4-a046-120a8a855cca_story.html.Google Scholar
March, J. G., Sproul, L., & Tamuz, M. (1991). Learning from samples of one or fewer. Organization Science, 2, 113.Google Scholar
Paté-Cornell, M. E. (1985). Warning systems and risk reduction. Risk analysis in the private sector. Advances in Risk Analysis, 220, 469482.Google Scholar
Pilkinton, E. (2010, July 23). Deepwater Horizon alarms were switched off “to help workers sleep.” The Guardian. Accessed at: www.theguardian.com/environment/2010/jul/23/deepwater-horizon-oil-rig-alarms.Google Scholar
Riley, M., Elgin, B., Lawrence, D., & Matlack, C. (2014, March 13). Missed alarms and 40 million stolen credit card numbers: How Target blew it. Business Week. Accessed at: www.businessweek.com/printer/articles/189573-missed-alarms-and-40-million-stolen-credit-card-numbers-how-target-blew-it.Google Scholar
Singer, P. W., & Friedman, A. (2014). Cybersecurity and cyberwar: What everyone needs to know. Oxford: Oxford University Press.Google Scholar
Tinsley, C. H., Dillon, R. L., & Cronin, M. A. (2012). How near-miss events amplify or attenuate risky decision making. Management Science, 58(9), 15961613.Google Scholar
Tinsley, C. H., Dillon, R. L., & Madsen, P. M. (2011, April). How to avoid catastrophe. Harvard Business Review, 9097.Google Scholar
Vaughan, D. (1996). The Challenger launch decision: Risky technology, culture, and deviance at NASA. Chicago, IL: University of Chicago Press.Google Scholar
Yi, W., & Bier, V. (1998). An application of copulas to accident precursor analysis. Management Science, 44(12), S257S270.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×