Measuring Users’ Socio-contextual Attributes for Self-adaptive Privacy Within Cloud-Computing Environments

Abstract

The examination of users’ socio-contextual attributes and their impact on their privacy management is of great importance in order for self-adaptive privacy preserving schemes to be effectively designed within cloud computing environments. However, several ambitious adaptive privacy schemes, presented in previous literature, seem to fail to examine those attributes in depth. To address that, this paper proposes the development of an interdisciplinary measurement scale, embodying validated metrics from both privacy and sociological literature. The scale provides the thoroughly identification of users’ social landscape interrelated with their privacy behaviours and its utilization is expected to lay the ground for the developers to meet efficiently both users’ social requirements and systems’ technical ones, before performing adaptive privacy mechanisms in cloud.