When outsourcing data to an untrusted database server, the data should be encrypted. When using thin clients or low-bandwidth networks it is best to perform most of the work at the server. In this paper we present a method, inspired by secure multi-party computation, to search efficiently in encrypted data. XML elements are translated to polynomials. A polynomial is split into two parts: a random polynomial for the client and the difference between the original polynomial and the client polynomial for the server. Since the client polynomials are generated by a random sequence generator only the seed has to be stored on the client. In a combined effort of both the server and the client a query can be evaluated without traversing the whole tree and without the server learning anything about the data or the query.

/pdf/using-secret-sharing-for-searching-in-encrypted-data-1u9q6q899n.pdf

Using secret sharing for searching in encrypted data

Database outsourcing model is emerging as an important new trend beside the “application-as-a service” model. In this model, since a service provider is typically not fully trusted, security and privacy of outsourced data are significant issues. These problems are referred to as data confidentiality, user privacy, data privacy, and query assurance. Among them, query assurance takes a crucial role to the success of the database outsourcing model. To the best of our knowledge, however, query assurance, especially for outsourced XML databases, has not been concerned reasonably in any previous work. In this paper, we propose a novel index structure, named Nested Merkle B+-Tree, combining the advantages of B+-tree and Merkle Hash Tree to completely deal with three issues of query assurance known as correctness, completeness and freshness in dynamic outsourced XML databases. Experimental results with real-world datasets prove the efficiency of our proposed solution.

/pdf/a-novel-solution-to-query-assurance-verification-for-dynamic-31r5yjge8m.pdf

A Novel Solution to Query Assurance Verification for Dynamic Outsourced XML Databases

With rapid developments of network technologies, database outsourcing is emerging as an important new trend beside the "application-as-a-service". In this model, data owners ship their data to external service providers. Service providers do data management tasks and offer their clients a mechanism to manipulate outsourced databases. Since a service provider is not always fully trusted, security and privacy of outsourced data are significant issues. These problems are referred to as data confidentiality, user privacy, data privacy and query assurance. Among them, query assurance takes a crucial role to the success of the database outsourcing model. To the best of our knowledge, however, query assurance, especially for outsourced XML databases, has not been concerned reasonably in any previous work. In this paper, we propose a novel index structure, nested Merkle B+ -tree, combining the advantages of B+-tree and Merkle hash tree to completely deal with three issues of query assurance known as correctness, completeness and freshness in dynamic outsourced XML databases. Experimental results with real datasets prove the efficiency of our proposed solution

http://www.cse.hcmut.edu.vn/~khanh/papers/FARES_ARES2007.pdf

Query Assurance Verification for Dynamic Outsourced XML Databases

Random walk graph and Markov chain based models are used heavily in many data and system analysis domains, including web, bioinformatics, and queueing. These models enable the description and analysis of various behaviors of stochastic systems. If the system being modelled has certain properties, such as if it is irreducible and aperiodic, close form formulations corresponding to its stationary behavior can be used to analyze its behavior. However, if the system does not have these properties or if the user is not interested in the stationary behavior, then an iterative approach needs to be used to determine potential outcomes based on the initial probability distribution inputs to the model. In this paper, we focus on access-privacy enabled outsourced Markov chain based data analysis applications, where a non-trusted service provider takes (hidden) user queries that are described in terms of initial state distributions, and evaluates them iteratively in an oblivious manner. We show that this iterative process can leak information regarding the possible values of the hidden input if the server has a priori knowledge about the underlying Markovian process. Hence as opposed to simple obfuscation mechanisms, we develop an algorithm based on methodical addition of extra states, which guarantees unbounded feasible regions for the inputs, thus preventing a malicious host from having an informed guess regarding the inputs.

/pdf/access-private-outsourcing-of-markov-chain-and-randomwalk-8fv69udxmm.pdf

Access-Private Outsourcing of Markov Chain and RandomWalk based Data Analysis Applications

Steganographic file system

With the increasing use of Web services, many new challenges concerning data security are becoming critical. Especially in mobile services, where clients are generally thin in terms of computation power and storage space, a remote server can be outsourced for the computation or can act as a data store. Unfortunately, such a data store may not always be trustworthy, and clients with sensitive data and queries may want protection from malicious attacks. This article presents a technique to hide tree-structured data from potentially malicious data stores, while allowing clients to traverse the data to locate an object of interest without leaking information to the data store. The two motivating applications for this approach are hiding (1) tree-like XML data as well as XML queries that are in the form of tree-paths, and (2) tree-structured indexes and queries executed on such data structures. We show that this task is achievable through a one-server protocol that introduces only a limited and adjust...

/pdf/hiding-tree-structured-data-and-queries-from-untrusted-data-27c2mhzbd7.pdf

Hiding Tree Structured Data and Queries from Untrusted Data Stores

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Hiding Tree Structured Data and Queries from Untrusted Data Stores