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Expert Knowledge for Contextualized Warnings
Technische Universität Darmstadt.
Technische Universität Darmstadt.ORCID-id: 0000-0003-2674-4043
2014 (Engelska)Rapport (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Technische Universität Darmstadt , 2014.
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-47231OAI: oai:DiVA.org:kau-47231DiVA, id: diva2:1051252
Tillgänglig från: 2016-12-01 Skapad: 2016-11-18 Senast uppdaterad: 2019-10-14Bibliografiskt granskad

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Volkamer, Melanie

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Totalt: 152 träffar
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