scholarly journals Probabilistic Characterization of Adversary Behavior in Cyber Security

2009 ◽  
Author(s):  
C Meyers ◽  
S Powers ◽  
D Faissol
Keyword(s):  
Cyber Security ◽  
Probabilistic Characterization

Probabilistic characterization of subsurface stratigraphic configuration with modified random field approach

2021 ◽  
pp. 106138
Author(s):  
Chao Zhao ◽  
Wenping Gong ◽  
Tianzheng Li ◽  
C. Hsein Juang ◽  
Huiming Tang ◽  
...  
Keyword(s):  
Random Field ◽  
Field Approach ◽  
Probabilistic Characterization

Classification and characterization of US consumers based on their perceptions of risk of tablet use in international hotels

2019 ◽  
Vol 10 (3) ◽  
pp. 233-254 ◽  
Author(s):  
Cristian Morosan ◽  
Agnes DeFranco
Keyword(s):  
Cyber Security ◽  
Risk Perceptions ◽  
Latent Profile Analysis ◽  
Profile Analysis ◽  
Cyber Attacks ◽  
Security Risk ◽  
Content Type ◽  
Perceptions Of Risk ◽  
Using Data

Purpose Cyber-attacks on hotel information systems could threaten the privacy of consumers and the integrity of the data they exchange upon connecting their mobile devices to hotel networks. As the perceived cyber-security risk may be reflected heterogeneously within the US consumer population traveling internationally, the purpose of this study is to examine such heterogeneity to uncover classes of US consumers based on their perceptions of risk of using tablets for various tasks when staying in hotels abroad. Design/methodology/approach Using data collected from 1,016 US consumers who stayed in hotels abroad, this study used latent profile analysis (LPA) to classify the consumers based on their perceptions of risk associated with several tablet use behaviors in hotels. Findings The analysis uncovered four latent classes and produced a characterization of these classes according to several common behavioral (frequency of travel, the continent of the destination, duration of stay and purpose of travel) and demographic (gender, age, income and education) consumer characteristics. Originality/value Being the first study that classifies consumers based on the risk of using tablets in hotels while traveling internationally, this study brings the following contributions: offers a methodology of classifying (segmenting) consumer markets based on their cyber-security risk perceptions, uses LPA, which provides opportunities for an accurate and generalizable characterization of multivariate data that comprehensively illustrate consumer behavior and broadens the perspective offered by the current literature by focusing on consumers who travel from their US residence location to international destinations.

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