Recently, a lot of innovative systems have been developed for data storage across various clouds. Since a single point of assault will release all the information, users are provided with some degree for data leakage control when data is distributed among several cloud storage providers (CSPs). Even when using numerous clouds, yet, uncontrolled dispersal of data chunks can result in excessive evidence disclosure. Here we investigate a significant information leakage issue brought on by random data distribution across multiple cloud storage providers. Next, we introduce Data Sim, a multi-cloud data loss conscious storage system. Data Sim seeks to minimize the consumer’s information leakage across various clouds by storing grammatically identical information on the identical cloud. We create a tool to calculate the information leakage depending on these signatures and an approximation algorithm for effectively developing similarity-preserving identities for information chunks depending on Min Hash and Bloom filter. We introduce a clustering-based efficient storage plan formation approach for spreading data chunks over various clouds by low information leakage. Moreover, the characteristics comprise Storage capacity offered by the cloud and Alert Notification while surpassing the permitted storage limit of the cloud.