A Blockchain-Based Privacy-Preserving Mechanism for Attribute Matching in Social Networks

Trace Me If You Can: An Unlinkability Approach for Privacy-Preserving in Social Networks

IEEE Access ◽

10.1109/access.2021.3066176 ◽

2021 ◽

pp. 1-1

Author(s):

Kah Meng Chong ◽

Amizah Malip

Keyword(s):

Social Networks ◽

Privacy Preserving

Download Full-text

A Privacy-Preserving Friend Recommendation Mechanism for Online Social Networks

Proceedings of the 2020 4th International Conference on Cryptography, Security and Privacy ◽

10.1145/3377644.3377648 ◽

2020 ◽

Author(s):

Fukang Liu ◽

Guorui Wu ◽

Yang Liu

Keyword(s):

Social Networks ◽

Online Social Networks ◽

Privacy Preserving ◽

Friend Recommendation

Download Full-text

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

Future Internet ◽

10.3390/fi13020023 ◽

2021 ◽

Vol 13 (2) ◽

pp. 23

Author(s):

Angeliki Kitsiou ◽

Eleni Tzortzaki ◽

Christos Kalloniatis ◽

Stefanos Gritzalis

Keyword(s):

Social Networks ◽

Interdisciplinary Approach ◽

Privacy Preserving ◽

Social Characteristics ◽

Behavioral Models ◽

Social Landscape ◽

Technological Context ◽

Privacy Risks ◽

Self Adaptive

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.

Download Full-text