StoreSim: Optimizing Information Leakage in Multi-Cloud Storage Services

Abstract

Abstract: Many schemes have been recently advanced for storing data on multiple clouds. Distributing data over different cloud storage providers (CSPs) automatically provides users with a certain degree of information leakage control, as no single point of attack can leak all a user’s information. However, unplanned distribution of data chunks can lead to high information disclosure even while using multiple clouds. In this paper, to address this problem, we present Store-Sim, an information leakage-aware storage system in multi cloud. Store-Sim aims to store syntactically similar data on the same cloud, thus minimizing the user’s information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity- preserving signatures for data chunks based on Min-Hash and Bloom filters, and design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluated our scheme using two real datasets from Wikipedia and GitHub. We show that our scheme can reduce information leakage by up to 60-70 Percent. Keywords: Min-Hash, Bloom-Filter, Multi-Cloud, StoreSim, Data Leakage.