Efficient Authentication of Outsourced String Similarity Search

TL;DR

This paper introduces AutoS3, a secure authentication mechanism for outsourced string similarity search in cloud computing, ensuring soundness and completeness with efficient verification methods and an innovative indexing structure.

Contribution

It presents AutoS3, combining a new authenticated string index (MBtree) with lightweight verification methods (VS2 and EVS2) for secure outsourced string similarity search.

Findings

AutoS3 effectively detects cheating behaviors.

Verification methods are lightweight and cost-efficient.

Experimental results show high efficiency on real datasets.

Abstract

Cloud computing enables the outsourcing of big data analytics, where a third party server is responsible for data storage and processing. In this paper, we consider the outsourcing model that provides string similarity search as the service. In particular, given a similarity search query, the service provider returns all strings from the outsourced dataset that are similar to the query string. A major security concern of the outsourcing paradigm is to authenticate whether the service provider returns sound and complete search results. In this paper, we design AutoS3, an authentication mechanism of outsourced string similarity search. The key idea of AutoS3 is that the server returns a verification object VO to prove the result correctness. First, we design an authenticated string indexing structure named MBtree for VO construction. Second, we design two lightweight authentication methods named VS2 and EVS2 that can catch the service provider various cheating behaviors with cheap verification cost. Moreover, we generalize our solution for top k string similarity search. We perform an extensive set of experiment results on real world datasets to demonstrate the efficiency of our approach.