As the integration of Internet of Things devices with cloud computing proliferates, the paramount importance of privacy preservation comes to the forefront. This survey paper meticulously explores the landscape of privacy issues in the dynamic intersection of IoT and cloud systems. The comprehensive literature review synthesizes existing research, illuminating key challenges and discerning emerging trends in privacy preserving techniques. The categorization of diverse approaches unveils a nuanced understanding of encryption techniques, anonymization strategies, access control mechanisms, and the burgeoning integration of artificial intelligence. Notable trends include the infusion of machine learning for dynamic anonymization, homomorphic encryption for secure computation, and AI-driven access control systems. The culmination of this survey contributes a holistic view, laying the groundwork for understanding the multifaceted strategies employed in securing sensitive data within IoT-based cloud environments. The insights garnered from this survey provide a valuable resource for researchers, practitioners, and policymakers navigating the complex terrain of privacy preservation in the evolving landscape of IoT and cloud computing

翻译：随着物联网设备与云计算融合的普及，隐私保护的重要性日益凸显。本综述论文深入探讨了物联网与云系统动态交互中的隐私问题。通过全面的文献综述，本文综合了现有研究，揭示了关键挑战并识别了隐私保护技术中的新兴趋势。对不同方法的分类揭示了加密技术、匿名化策略、访问控制机制以及新兴人工智能融合的细致理解。显著趋势包括机器学习用于动态匿名化、同态加密用于安全计算，以及人工智能驱动的访问控制系统。本综述的最终成果提供了一个整体视角，为理解物联网云环境中保护敏感数据的多层面策略奠定了基础。本综述获得的见解为研究人员、从业者和政策制定者在物联网与云计算不断发展的格局中应对隐私保护的复杂领域提供了宝贵资源。