Optimizing Information Leakage In Cloud Storage Services
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Date
2024
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Publisher
NHCE
Abstract
Recently, a lot of innovative systems have been developed for data storage across various clouds. Since no single point of attack can leak all the information, users are automatically given some degree of information leakage control when data is distributed among several cloud storage providers (CSPs). Even when using numerous clouds, however, uncontrolled distribution of data chunks can result in excessive information disclosure. In this research project, we investigate a significant data leakage issue resulting from unplanned data distribution in multi cloud storage systems. Next, we introduce Store Sim, a multi cloud storage system that is mindful of information leaks. In order to reduce user information leakage across various clouds, Store Sim seeks to store syntactically similar data on the same cloud. To efficiently produce similarity-preserving signatures for data chunks, we build an approximation approach based on Create a function to calculate the information leakage based on these signatures, as well as the Min Hash and Bloom filters. We then introduce a clustering-based efficient storage plan generation approach that distributes data chunks over many clouds with low information leakage.