Massive cloud infrastructure capabilities, including efficient, scalable, and elastic computing resources, have led to a widespread adoption of Internet of Things (IoT) cloud-enabled services. This involves giving complete control to cloud service providers (CSPs) of sensitive IoT data by moving data storage and processing in cloud. An efficient and lightweight advanced encryption standard (AES) cryptosystem can play a major role in protecting IoT data from exposure to CSPs by protecting the privacy of outsourced data. However, AES lacks computation capabilities, which is a critical factor that prevents individuals and organizations from taking full advantage of cloud computing services. When Intel software guard extensions (SGX) is used with AES cryptosystem, the developing framework can provide a practical solution to build a confidentiality-based data analytics framework for IoT-enabled applications in various domains. In this paper, a privacy-preserving data analytics framework is developed that relies on a hybrid-integrated approach, in which both software- and hardware-based solutions are applied to ensure confidentiality and process-sensitive outsourced data in the cloud environment.

大规模的云基础设施功能，包括高效、可扩展和弹性的计算资源，已导致物联网 (IoT) 支持云的服务得到广泛采用。这涉及通过在云中移动数据存储和处理来完全控制敏感物联网数据的云服务提供商 (CSP)。高效轻量级的高级加密标准 (AES) 密码系统可以通过保护外包数据的隐私，在保护物联网数据免于暴露给 CSP 方面发挥重要作用。然而，AES 缺乏计算能力，这是阻止个人和组织充分利用云计算服务的关键因素。当英特尔软件防护扩展 (SGX) 与 AES 密码系统一起使用时，开发框架可以提供实用的解决方案，为各个领域的物联网应用构建基于机密性的数据分析框架。在本文中，开发了一种基于混合集成方法的隐私保护数据分析框架，其中应用基于软件和硬件的解决方案来确保云环境中的机密性和流程敏感的外包数据。