Identifying Privacy Related Requirements for the Design of Self-Adaptive Privacy Protections Schemes in Social Networks

Abstract

Social Networks (SNs) bring new types of privacy risks threats for users; which developers should be aware of when designing respective services. Aiming at safeguarding users’ privacy more effectively within SNs, self-adaptive privacy preserving schemes have been developed, considered the importance of users’ social and technological context and specific privacy criteria that should be satisfied. However, under the current self-adaptive privacy approaches, the examination of users’ social landscape interrelated with their privacy perceptions and practices, is not thoroughly considered, especially as far as users’ social attributes concern. This study, aimed at elaborating this examination in depth, in order as to identify the users’ social characteristics and privacy perceptions that can affect self-adaptive privacy design, as well as to indicate self-adaptive privacy related requirements that should be satisfied for users’ protection in SNs. The study was based on an interdisciplinary research instrument, adopting constructs and metrics from both sociological and privacy literature. The results of the survey lead to a pilot taxonomic analysis for self-adaptive privacy within SNs and to the proposal of specific privacy related requirements that should be considered for this domain. For further establishing of our interdisciplinary approach, a case study scenario was formulated, which underlines the importance of the identified self-adaptive privacy related requirements. In this regard, the study provides further insight for the development of the behavioral models that will enhance the optimal design of self-adaptive privacy preserving schemes in SNs, as well as designers to support the principle of PbD from a technical perspective.

Specification of Self-Adaptive Privacy-Related Requirements within Cloud Computing Environments (CCE)

“…Under this light, two supplementary surveys have been elaborated [9,17], regarding (a) users' needs for privacy within cloud computing environments based on their social groups and (b) developers' perspectives on privacy, focusing on self-adaptive privacy in cloud environments. The integration of developers' and users' perspectives is crucial for confronting the challenges of self-adaptive privacy in cloud computing environments.…”

“…The first supplementary survey focused on understanding users' self-presentation and self-disclosure practices within cloud services, particularly in relation to their social group affiliations. By conducting a quantitative survey among students across universities in Greece, England, and Spain, the study provided valuable insights into how users' social identities influenced their privacy behaviors [17]. In this regard, the foundational research question formulated to guide our study was RQ 1: "Does belonging to a social group affect users' privacy management within CCE?".…”

The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites

“…Several researchers have investigated ways in which user awareness, engagement and utilization of privacy features can be improved [4,[10][11][12][13][14][15]. This paper specifically addresses adaptive approaches that involve modelling user privacy preferences and automatically tailoring privacy settings to match these preferences [10,12,14,16].…”