The vigorous development of the Internet has spurred exponential data growth, yet data is predominantly stored in isolated user entities, hampering its full value realization. In large-scale deployment of ``AI+industries'' such as smart medical care, intelligent transportation and smart homes, the gap between data supply and demand continues to widen, and establishing an effective data sharing mechanism is the core of promoting high-quality industrial development. However, data sharing faces significant challenges in security, performance, and functional adaptability. Privacy-enhancing encryption technologies, including Attribute-Based Encryption (ABE), Proxy Re-encryption (PRE), and Searchable Encryption (SE), offer promising solutions with distinct advantages in enhancing security, improving flexibility, and enabling efficient sharing. Statistical analysis of relevant literature from 2020 to 2025 reveals a rising research trend in ABE, PRE and SE, focusing on their data sharing applications. Firstly, this work proposes a data sharing process framework and identifies 20 potential attacks across its stages. Secondly, this work integrates ABE, SE, PRE with 12 enhancement technologies and examines their multi-dimensional impacts on the security, performance, and functional adaptability of data sharing schemes. Lastly, this work outlines key application scenarios, challenges, and future research directions, providing valuable insights for advancing data sharing mechanisms based on privacy-enhancing encryption technologies.

翻译：互联网的蓬勃发展推动了数据的指数级增长，然而数据主要存储于孤立的用户实体中，阻碍了其全部价值的实现。在智慧医疗、智能交通和智能家居等“人工智能+产业”的大规模部署中，数据供需差距持续扩大，建立有效的数据共享机制是推动产业高质量发展的核心。然而，数据共享在安全性、性能和功能适应性方面面临重大挑战。包括属性基加密（ABE）、代理重加密（PRE）和可搜索加密（SE）在内的隐私增强加密技术，提供了有前景的解决方案，在增强安全性、提升灵活性和实现高效共享方面具有独特优势。对2020年至2025年间相关文献的统计分析显示，ABE、PRE和SE的研究呈上升趋势，重点关注其数据共享应用。首先，本文提出了一个数据共享过程框架，并识别了其各阶段可能面临的20种潜在攻击。其次，本文将ABE、SE、PRE与12种增强技术相结合，并审视了它们对数据共享方案安全性、性能和功能适应性的多维度影响。最后，本文概述了关键应用场景、挑战和未来研究方向，为推进基于隐私增强加密技术的数据共享机制提供了宝贵见解。