Research On Data Integrity Audit And Optimization Strategy In Cloud Environment

With the rapid development of information technology,various information management systems have been widely applied in various industries such as government,enterprises,and institutions.In the application process of these management systems,the amount of data collected by the system has also sharply increased.How to effectively store and scientifically manage these massive amounts of data has not only become a problem that various industries need to face,but also an important issue that urgently needs to be solved in the information age management field.As a new technology with large storage capacity,strong scalability and convenient access,cloud storage has emerged as the times require,and has become one of the core means of data management.In the cloud storage environment,relevant departments can migrate business data migration to the cloud to save local storage space,reduce maintenance costs,and solve the information silo problem.However,after outsourcing and storing data to cloud servers,the original owner loses direct control over the data.Due to the existence of various subjective and objective factors,instances of cloud servers losing or damaging user data often occur,and data integrity is a key prerequisite for data value and a core reliance for information system assisted decision-making.Therefore,how to audit the data integrity in the cloud storage environment is extremely important.As a new research direction in the field of information management,it has been highly valued by the academic community.This article is guided by practical application requirements,supported by modern information technology,and follows the research approach of "private audit,quasi private audit,and then public audit",focusing on building an efficient and secure data integrity audit mechanism in the cloud environment.By studying and optimizing existing cloud audit mechanisms,we ensure the integrity and reliability of data in the management and use process,and provide objective and effective support for the correct implementation of auxiliary decision-making in information management systems.The research content and main contributions include:(1)A practical private audit model and an optimized implementation based on error correction codes and homomorphic authentication technology have been constructed to address the issue of insufficient characterization of existing private audit models and their actual usability.The existing private audit model is a good portrayal of the application scenario where users conduct integrity audits themselves.However,these models and existing implementations face usability challenges to some extent.This article analyzes the current popular private audit models and corresponding UCSA protocols,and proposes a model optimization implementation that first performs error correction coding on stored data,and then adds parity codes for homomorphic authentication.By comparing and analyzing the security and performance of this implementation,its advantages in specific practical processes were verified.(2)Aiming at the problem that private audit model is difficult to implement outsourcing audit and public audit model is inefficient,this paper constructs a quasi-private audit model that combines the efficiency of private audit and the outsourcing of public audit.In the outsourcing preprocessing process of raw data,authentication labels are first generated in the form of the inner product of data vectors,and then the number of labels is flexibly set for each data block to control its security level.This model can balance the efficiency advantages of private auditing with the suitability for outsourcing of public auditing.The efficiency comparison with existing private audit schemes and public audit schemes indicates that the proposed quasi private audit mechanism is more flexible and convenient.(3)To address the issue of traditional public audit models where data owners not only need to generate authentication labels for each data block,but also need to manage their public key certificates,an identity based public audit model is proposed for different scenarios.In the identity-based cloud audit model,the data owner only needs to use their public information(such as email address,office phone number,etc.)as the public key,without the need to apply for certificates,verify certificates,and other additional operations on the public key.For application scenarios that require specifying third-party validators,an identity-based cloud audit model with designated validators is proposed,and an implementation scheme and analysis of this scheme are provided based on relevant mechanisms such as key negotiation;In response to the lack of data privacy protection in existing identity-based cloud audit models,a model with privacy protection function was constructed and implemented based on random mask method.In addition,in the implementation process of the two models,the refinement and segmentation of data blocks and label aggregation methods were fully utilized,thereby reducing the storage and communication costs of data and providing a methodological basis for secure data storage and management in different application scenarios.(4)In response to the issue of user key escrow in the identity-based cloud audit model,a non certified cloud audit model with privacy protection function was further constructed.Considering the existing unlicensed cloud audit security model and the audit vulnerabilities in the model implementation process,this article has optimized and improved the unlicensed cloud audit model,and provided a specific implementation of the optimization model based on the existing cloud audit mechanism.In addition,a detailed security and performance analysis was also provided.The results indicate that the optimization model proposed in this article has reliable audit security and good performance,and can meet the needs of practical data management applications.In summary,through systematic research on several models such as private audit,quasi private audit,identity based public audit,and certificateless public audit,as well as implementation of models based on different technologies,this research work can effectively improve the reliability of data outsourcing storage in cloud environments,providing reliable theoretical support for the field of data security management in the information age,and also providing a prerequisite for achieving upper level management decisions based on data.