This paper presents a novel approach to address the challenges of self-adaptive privacy in cloud computing environments (CCE). Under the Cloud-InSPiRe project, the aim is to provide an interdisciplinary framework and a beta-version tool for self-adaptive privacy design, effectively focusing on the integration of technical measures with social needs. To address that, a pilot taxonomy that aligns technical, infrastructural, and social requirements is proposed after two supplementary surveys that have been conducted, focusing on users’ privacy needs and developers’ perspectives on self-adaptive privacy. Through the integration of users’ social identity-based practices and developers’ insights, the taxonomy aims to provide clear guidance for developers, ensuring compliance with regulatory standards and fostering a user-centric approach to self-adaptive privacy design tailored to diverse user groups, ultimately enhancing satisfaction and confidence in cloud services.

The rapid development of cloud computing environments has resulted in various advances and personalized services for users, raising thus several privacy issues. Towards this, research focused on privacy safeguard in the cloud, indicating solutions on the area of self-adaptive privacy. A detailed review is produced to bring forward the carried out work and to analyze it in terms of privacy interdisciplinary standards. In this regard, our work presents the existing self-adaptive privacy approaches and identifies the context for which they have been developed. Moreover, a corresponding classification scheme is provided. The findings give also insights on the proposed tools, which were critically analyzed. This review aims at indicating the developments and limitations of the area, providing potentials of future work in less discussed aspects of the self-adaptive privacy in cloud under an interdisciplinary point of view.