Kitsiou Angeliki, Sideri Maria, Pantelelis Michail, Simou Stavros, Mavroeidi Aikaterini-Georgia, Vgena Katerina, Tzortzaki Eleni, Kalloniatis Christos
PRIVASI Lab, Department of Cultural Technology & Communication, University of the Aegean, 81100 Mytilene, Greece.
Sensors (Basel). 2024 May 19;24(10):3227. doi: 10.3390/s24103227.
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.
本文提出了一种新颖的方法来应对云计算环境（CCE）中自适应隐私方面的挑战。在Cloud-InSPiRe项目下，目标是提供一个跨学科框架和一个用于自适应隐私设计的测试版工具，有效地专注于技术措施与社会需求的整合。为了解决这一问题，在进行了两项补充调查后，提出了一种将技术、基础设施和社会需求相结合的试验性分类法，这两项调查聚焦于用户的隐私需求以及开发者对自适应隐私的看法。通过整合基于用户社会身份的实践和开发者的见解，该分类法旨在为开发者提供明确的指导，确保符合监管标准，并促进以用户为中心的方法来进行针对不同用户群体的自适应隐私设计，最终提高对云服务的满意度和信心。
