Secure Public Auditing For Internet-of-vehicle Data

The Internet of Vehicles(Io V)is a new type of industry that deeply integrates fields such as automobiles,electronics,communications,transportation,and management,in which data has huge commercial and social value.To improve the efficient application of Io V data,more and more cloud service providers have proposed different Io V-cloud solutions.The cloud storage of data has become an inevitable demand of the Io V industry.In fact,the endless cloud security incidents have greatly affected users’ confidence in cloud services.Therefore,the cloud data security audit technique has been widely proposed to guarantee the storage integrity of outsourced data.However,the Io V data puts forward higher requirements on cloud audit schemes due to its various types,wide sources,and diverse applications.To solve the integrity problem of Io V data stored in the cloud,this dissertation proposes different audit schemes for different data application scenarios,combined with audit requirements for security and performance.The main researches are as follows:First,for the audit requirements of users on the data’s application as well as the diversity and multi-source of Io V data,a multi-sourced data audit scheme based on the data mapping table is proposed,which can fully achieve the essential function and security requirements,such as classified auditing,multi-source auditing and privacy protection.Particularly,we design a new authenticated data structure,called the data mapping table,to track the distribution of each type of Io V data to ensure fine and rapid audits.Moreover,our scheme can reduce the overheads for both the key management and the generation of block tags.The security of the proposed scheme can be confirmed from the security analysis.In addition,the experimental results reveal that the communication and computation costs of the proposed scheme are outperformer than the previous ones.Second,for the application scenario of data sharing on the Io V environment,the integrity verification of shared data after desensitization has become a challenging issue.To solve the above problem,a public data audit scheme supporting privacy protection is proposed.First,we design a tag conversion algorithm to calculate the new authentication tag for shared data,which can realize personalized integrity verification of desensitization data.Compared with the traditional solution,our scheme can greatly reduce the computing and communication overhead on the user side.Second,this scheme adding random masks to the data proof value during the auditing process to achieve privacy protection.The security of the scheme can be proved from security analysis formally.The experiences results show that the computational cost of our scheme in the tag conversion phase and audit phase is much lower than the existing schemes.Third,for the credibility of third-party auditors is difficult to guarantee,a public data auditing scheme leveraging smart contracts is proposed,which can achieve all the necessary auditing requirements for function and security,including resist-collusion auditing,resist-violation auditing,resist-forge auditing,and data privacy protection.Specifically,a challenge generation algorithm based on smart contracts are designed to generate fair random sampling blocks;an audit consolidation algorithm based on smart contracts is designed to resist procrastinating auditors.Moreover,we propose a Postaudit verification mechanism to repeat the auditing results.Based on this,the audit work can be verified once the dispute occurs.Furthermore,the Proof of Auditing Computation strategy is presented to monitor whether the auditor provides a true audit report.The security of the proposed scheme can be confirmed from the security analysis.The theoretical analyses and experimental results reveal that our scheme is feasible and efficient in its implementation.