Understanding Research Related to Designing for Children's Privacy and Security: A Document Analysis

Kumar, Priya; O’Connell, Francis; Lucy, Li; Byrne, Virginia L.; Chetty, Marshini; Clegg, Tamara; Vitak, Jessica

doi:10.1145/3585088.3589375

Cited by 7 publications

(3 citation statements)

References 120 publications

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“…However, their study does not address potential barriers to the effectiveness of these interventions, such as children's attention, engagement, and comprehension of educational materials. Kumar et al (2023) explored the complexities of designing for children's privacy and security, emphasizing the need for designers to incorporate children's perspectives into their work and offering recommendations to enhance privacy and security efforts [30]. Yet, their research does not extensively involve children in guiding the research process, potentially overlooking valuable insights from the target audience.…”

Section: Related Workmentioning

confidence: 99%

Securing Tomorrow's Generation: An Approach Utilizing Machine Learning Models for Children's Online Safety

Pir,

Rabbi,

Islam

2024

Preprint

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The increasing usage of online platforms by children in the fast-changing digital environment has raised worries over potential privacy and security hazards. Despite previous study efforts, there are still significant unresolved concerns, particularly the absence of a methodical and all-encompassing approach to comprehending the social safety concerns associated with digital platforms. This involves integrating security and privacy elements with qualitative and categorical data gathered from the viewpoints of children. In order to fill this void, our study undertakes a comprehensive analysis of children's online encounters, collecting firsthand observations from children themselves. Prior to the primary investigation, a preliminary survey was carried out using a cohort of 30 children to authenticate our methodology, hence guiding the development of survey questionnaires. Afterwards, data from a total of 383 children were gathered for analysis. The study develops two models for the dataset—Privacy (Model-I) and Security (Model-II). Employing Principal Component Analysis (PCA) and machine learning algorithms such as Decision Tree, Logistic Regression, Random Forest, and Gaussian Naive Bayes, these models address specific privacy and security concerns. The results unveil intriguing insights into children's perspectives on online privacy and security. In Model-I, 90.1% of children report preserved privacy, with 9.9% reporting violations, while in Model-II, 71.3% of children perceive their security as preserved, with 28.7% reporting violations. Comparing children's perspectives in both models enhances digital safety. This research provides actionable insights from a systematic approach using statistical and machine learning techniques. Our key new finding underscores the importance of considering children's perspectives in policy development for online safety, informing evidence-based interventions and policies. Our systematic approach, built from different techniques, offers a practical and scalable solution for defining privacy and security violations among a vast population of children, enabling policymakers and related child-concerning bodies to easily identify and address such issues across diverse regions and sectors.

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Section: Related Workmentioning

confidence: 99%

Securing Tomorrow's Generation: An Approach Utilizing Machine Learning Models for Children's Online Safety

Pir,

Rabbi,

Islam

2024

Preprint

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“…Privacy literacy projects that connect with such lobbying efforts could send a powerful signal to their participants about how youth can make a difference in regulation and policymaking. Design changes: Privacy literacy scholars and practitioners can push technology design practices that center the privacy interests of those most affected by technologies. For instance, Kumar et al (2023) offer guidance on how technology developers can engage with privacy theory to grapple with design tensions and use child- and community-centered design processes to integrate privacy protections directly into technologies. Privacy literacy projects that connect with design efforts can help transform practice at the level of industry. Organizational changes: Privacy literacy scholars and practitioners can work to change organizational policies and practices to better protect the privacy of the communities they serve.…”

Section: Aligning Privacy Literacy and Critical Literacymentioning

confidence: 99%

“…Design changes: Privacy literacy scholars and practitioners can push technology design practices that center the privacy interests of those most affected by technologies. For instance,Kumar et al (2023) offer guidance on how technology developers can engage with privacy theory to grapple with design tensions and use child-and community-centered design processes to integrate privacy protections directly into technologies. Privacy literacy projects that connect with design efforts can help transform practice at the level of industry.…”

mentioning

confidence: 99%

Orienting privacy literacy toward social change

Kumar

2023

ILS

Self Cite

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Purpose This article advocates that privacy literacy research and praxis mobilize people toward changing the technological and social conditions that discipline subjects toward advancing institutional, rather than community, goals. Design/methodology/approach This article analyzes theory and prior work on datafication, privacy, data literacy, privacy literacy and critical literacy to provide a vision for future privacy literacy research and praxis. Findings This article (1) explains why privacy is a valuable rallying point around which people can resist datafication, (2) locates privacy literacy within data literacy, (3) identifies three ways that current research and praxis have conceptualized privacy literacy (i.e. as knowledge, as a process of critical thinking and as a practice of enacting information flows) and offers a shared purpose to animate privacy literacy research and praxis toward social change and (4) explains how critical literacy can help privacy literacy scholars and practitioners orient their research and praxis toward changing the conditions that create privacy concerns. Originality/value This article uniquely synthesizes existing scholarship on data literacy, privacy literacy and critical literacy to provide a vision for how privacy literacy research and praxis can go beyond improving individual understanding and toward enacting social change.

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A Review of Social Network Regulations and Mechanisms for Safeguarding Children’s Privacy

Abreu,

Viegas,

Santin

2024

Lecture Notes on Data Engineering and Communications Technologies

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Understanding Research Related to Designing for Children's Privacy and Security: A Document Analysis

Cited by 7 publications

References 120 publications

Securing Tomorrow's Generation: An Approach Utilizing Machine Learning Models for Children's Online Safety

Securing Tomorrow's Generation: An Approach Utilizing Machine Learning Models for Children's Online Safety

Orienting privacy literacy toward social change

A Review of Social Network Regulations and Mechanisms for Safeguarding Children’s Privacy

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