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Expert Knowledge for Contextualized Warnings
Technische Universität Darmstadt.
Technische Universität Darmstadt.
2014 (English)Report (Other academic)
Abstract [en]

Users are bothered by too many security warnings in a vari- ety of applications. To reduce the number of unnecessary warnings, de- velopers cannot continue to report technical security problems. Instead, they need to consider the actual risks of the context for the decision of whether and how to warn – contextualized warnings. For this risk assess- ment, developers need to encode expert knowledge. Given the number and complexity of the risks – for example, in Web browsing –, eliciting and encoding the expert knowledge is challenging. In this paper, we pro- pose a holistic methodology for an abstract risk assessment that builds upon prior concepts from risk management, such as decision trees. The result of the methodology is an abstract risk model – a model to as- sess the risk for the concrete context. In a case study, we show how this methodology can be applied to warnings in Web browsers.

Place, publisher, year, edition, pages
Technische Universität Darmstadt , 2014.
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-47231OAI: oai:DiVA.org:kau-47231DiVA: diva2:1051252
Available from: 2016-12-01 Created: 2016-11-18 Last updated: 2016-12-20Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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