Dynamic and Public Evaluation Using Accurate Cloud Data in Imbalance



Customers of cloud services lose control over their data, making it more difficult to ensure its safety. New methods such as "provable data ownership" and "proofs of irretrievability" have been created as a solution to this problem; however, they are designed to audit static archive material and hence do not take data dynamics into consideration. As an added complication, the threat models used by these schemes often assume the data owner to be trustworthy and focus on identifying a hostile cloud service provider, even if the latter might be the source of any harmful action. Thus, there should be a public auditing mechanism that takes data dynamics into account and uses fair means to settle disputes. Specifically, we develop an index switcher to effectively handle data dynamics by doing away with the limitation of index use in tag computation imposed by conventional methods. We create new extensions to existing threat models and use the signature exchange idea to design fair arbitration mechanisms for resolving future disputes, all with the goal of ensuring that no one may participate in unfair activity without being discovered. Our approach seems secure, according to the security analysis, and the performance evaluation indicates that the extra work required for data dynamics and conflict resolution is not insurmountable.


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