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On Understanding Context Modelling for Adaptive Authentication Systems
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AI
DOI：10.1145/3582696.png)
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摘要
En 中文
In many situations, it is of interest for authentication systems to adapt to context (e.g., when the user’s behavior differs from the previous behavior). Hence, representing the context with appropriate and well-designed models is crucial. We provide a comprehensive overview and analysis of research work on
C
ontext
M
odelling
f
or
A
daptive
A
uthentication systems
(CM4AA). To this end, we pursue three goals based on the
Systematic Mapping Study (SMS)
and
Systematic Literature Review (SLR)
research methodologies. We first present a SMS to structure the research area of CM4AA (
goal 1
). We complement the SMS with an SLR to gather and synthesise evidence about context information and its modelling for adaptive authentication systems (
goal 2
). From the knowledge gained from goal 2, we determine the desired properties of the context information model and its use for adaptive authentication systems (
goal 3
). Motivated to find out how to model context information for adaptive authentication, we provide a structured survey of the literature to date on CM4AA and a classification of existing proposals according to several analysis metrics. We demonstrate the ability of capturing a common set of contextual features that are relevant for adaptive authentication systems independent from the application domain. We emphasise that despite the possibility of a unified framework, no standard for CM4AA exists.
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