<![CDATA[The rapid expansion of cloud computing has steered in an era where cloud storage is increasingly prevalent, offering significant advantages in terms of reducing local storage burden. However, this technological shift has also introduced complex security challenges, including data integrity and privacy concerns. In response to these challenges, various data integrity auditing (DIA) protocols have been developed, aiming to enable efficient and secure verification of data stored in cloud environments. This survey paper provides a comprehensive analysis of existing DIA mechanisms, focusing on methods like homomorphic linear authentication, dynamic hash tables, and watermarking techniques for integrity and privacy preservation. It critically evaluates these methods in terms of their advantages, limitations, and the unique challenges they face in practical applications, such as scalability, efficiency in multi-owner contexts, and real-time auditing. Furthermore, the paper identifies key research gaps, including the need for optimizing largescale data handling, balancing watermarking imperceptibility with embedding capacity, and developing comprehensive solutions for decentralized public auditing. The survey serves as a critical resource for researchers to understand the current background of cloud data integrity auditing and the future directions in this evolving field.]]>
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