Measuring attitude towards personal data for adaptive cybersecurity

Addae, Joyce; Brown, Michael; Sun, Xu; Towey, Dave; Radenkovic, Milena

doi:10.1108/ics-11-2016-0085

Cited by 20 publications

(27 citation statements)

References 34 publications

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“…To minimize respondent fatigue, the APD scale adopted from (Addae et al, 2017) was simplified by selecting only eight items based on overall cluster membership predictor importance of the APD factors as well as the reliability score of the measured items. Consequently, questions on Personal Data Awareness (PDA), Personal Data Protection (PDP) and Privacy Concerns (PC) measured reflectively, captured the major facets of the APD as a Type II second-order construct.…”

Section: Methodsmentioning

confidence: 99%

“…Haddadi et al (2015) highlighted the complex nature of personal data as a construct and how users' preferences and concerns differ based on context and sociological factors. To aid the inclusion of APD in cybersecurity behavioural research models such as ours, we conducted a study that explored APD dimensions towards the development of a personal data attitudes measurement scale (Addae et al, 2017). Based on findings from this study, we hypothesise that users who are generally protective towards their personal data are more likely to adopt cybersecurity measures.…”

Section: Attitude To Personal Data (Apd)mentioning

confidence: 99%

“…To minimize survey fatigue, the APD scale adopted from (Addae et al, 2017) is simplified based overall cluster membership predictor importance of the APD factors as well as reliability score of the measured items. Protection PDP 1: I regularly look out for new policies on personal data protection PDP 2: I consider the privacy policy of institutions where I give out such personal details PDP 3: I don't always optimize my privacy settings when I create an online profile (Reverse Coded) Awareness PDA 1: Such details about me are of value to external organizations PDA 2: Researchers don't need my consent to access my personal details (Reverse Coded) PDA 3: Data collection organizations need to disclose the way the data are collected pro-cessed and used.…”

Section: Part 2 (B) -Attitude To Personal Data (Apd)mentioning

confidence: 99%

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Exploring user behavioral data for adaptive cybersecurity

Addae

Sun

Towey

et al. 2019

User Model User-Adap Inter

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This paper describes an exploratory investigation into the feasibility of predictive analytics of user behavioural data as a possible aid in developing effective user models for adaptive cybersecurity. Partial Least Squares Structural Equation Modelling (PLS-SEM) is applied to the domain of cybersecurity by collecting data on users' attitude towards digital security, and analysing how that influences their adoption and usage of technological security controls. Bayesian-network modeling is then applied to integrate the behavioural variables with simulated sensory data from the web browser and other empirical data gathered to support personalized adaptive cybersecurity decision-making. Results from the empirical study show that predictive analytics is feasible in the context of behavioural cybersecurity, and can aid in the generation of useful heuristics for the design and development of adaptive cybersecurity mechanisms. Predictive analytics can also aid in encoding digital security behavioural knowledge that can support the adaptation and/or automation of operations in the domain of cybersecurity. The experimental results demonstrate the effectiveness of the techniques applied to extract input data for the Bayesian-based models for personalized adaptive cybersecurity assistance.

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Section: Methodsmentioning

confidence: 99%

Section: Attitude To Personal Data (Apd)mentioning

confidence: 99%

Section: Part 2 (B) -Attitude To Personal Data (Apd)mentioning

confidence: 99%

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Exploring user behavioral data for adaptive cybersecurity

Addae

Sun

Towey

et al. 2019

User Model User-Adap Inter

Self Cite

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“…When a user becomes aware that their personal data can be a tradeable asset, the valuation of their personal data changes (Spiekermann and Korunovska, 2017). Moreover, users who are concerned about their privacy tend to have a greater awareness of the value associated with their personal data (Addae et al, 2017). Consequently, conceptualising data as being a tradable asset leads to users being more concerned about privacy and encourages active protection of their data.…”

Section: Awarenessmentioning

confidence: 99%

“…This interpretation is supported by the idea that the privacy calculus has a situational nature, where each privacy decision is determined impulsively (Masur, 2019), dependent on the context in which the information is being disclosed. Furthermore, Addae et al (2017) found that in comparison to health data, users do not view their social media data as sensitive. As such, the aspects that encourage or discourage disclosure might fluctuate depending on the situation.…”

Section: Supportedmentioning

confidence: 99%

Understanding the disclosure of personal data online

Parker

Flowerday

2021

ICS

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Purpose Social media has created a new level of interconnected communication. However, the use of online platforms brings about various ways in which a user’s personal data can be put at risk. This study aims to investigate what drives the disclosure of personal information online and whether an increase in awareness of the value of personal information motivates users to safeguard their information. Design/methodology/approach Fourteen university students participated in a mixed-methods experiment, where responses to Likert-type scale items were combined with responses to interview questions to provide insight into the cost–benefit analysis users conduct when disclosing information online. Findings Overall, the findings indicate that users are able to disregard their concerns due to a resigned and apathetic attitude towards privacy. Furthermore, subjective norms enhanced by fear of missing out (FOMO) further allows users to overlook potential risks to their information in order to avoid social isolation and sanction. Alternatively, an increased awareness of the personal value of information and having experienced a previous privacy violation encourage the protection of information and limited disclosure. Originality/value This study provides insight into privacy and information disclosure on social media in South Africa. To the knowledge of the researchers, this is the first study to include a combination of the theory of planned behaviour and the privacy calculus model, together with the antecedent factors of personal valuation of information, trust in the social media provider, FOMO.

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