The Hippocratic Oath has guided the conduct of physicians for centuries. Inspired by its tenet of preserving privacy, we argue that future database systems must include responsibility for the privacy of data they manage as a founding tenet. We enunciate the key privacy principles for such Hippocratic database systems. We propose a strawman design for Hippocratic databases, identify the technical challenges and problems in designing such databases, and suggest some approaches that may lead to solutions. Our hope is that this paper will serve to catalyze a fruitful and exciting direction for future database research. 1

Encryption is a well established technology for protecting sensitive data. However, once encrypted, data can no longer be easily queried aside from exact matches. We present an order-preserving encryption scheme for numeric data that allows any comparison operation to be directly applied on encrypted data. Query results produced are sound (no false hits) and complete (no false drops). Our scheme handles updates gracefully and new values can be added without requiring changes in the encryption of other values. It allows standard database indexes to be built over encrypted tables and can easily be integrated with existing database systems. The proposed scheme has been designed to be deployed in application environments in which the intruder can get access to the encrypted database, but does not have prior domain information such as the distribution of values and cannot encrypt or decrypt arbitrary values of his choice. The encryption is robust against estimation of the true value in such environments.

In the Outsourced Database (ODB) model, organizations outsource their data management needs to an external service provider. The service provider hosts clients' databases and offers seamless mechanisms to create, store, update and access (query) their databases. This model introduces several research issues related to data security. One of the core security requirements is providing efficient mechanisms to ensure data integrity and authenticity while incurring minimal computation and bandwidth overhead. In this work, we investigate the problem of ensuring data integrity and suggest secure and practical schemes that help facilitate authentication of query replies. We explore the applicability of popular digital signature schemes (RSA and DSA) as well as a recently proposed scheme due to Boneh et al. [1] and present their performance measurements.

Abstract. In an outsourced database (ODB) system the database owner publishes data through a number of remote servers, with the goal of enabling clients at the edge of the network to access and query the data more efficiently. As servers might be untrusted or can be compromised, query authentication becomes an essential component of ODB systems. In this chapter we present three techniques to authenticate selection range queries and we analyze their performance over different cost metrics. In addition, we discuss extensions to other query types. 1

Recent trends towards database outsourcing, as well as concerns and laws governing data privacy, have led to great interest in enabling secure database services. Previous approaches to enabling such a service have been based on data encryption, causing a large overhead in query processing. We propose a new, distributed architecture that allows an organization to outsource its data management to two untrusted servers while preserving data privacy. We show how the presence of two servers enables efficient partitioning of data so that the contents at any one server are guaranteed not to breach data privacy. We show how to optimize and execute queries in this architecture, and discuss new challenges that emerge in designing the database schema. 1

In this paper we propose and analyze a method for proofs of actual query execution in an outsourced database framework, in which a client outsources its data management needs to a specialized provider. The solution is not limited to simple selection predicate queries but handles arbitrary query types. While this work focuses mainly on read-only, computeintensive (e.g. data-mining) queries, it also provides preliminary mechanisms for handling data updates (at additional costs). We introduce query execution proofs; for each executed batch of queries the database service provider is required to provide a strong cryptographic proof that provides assurance that the queries were actually executed correctly over their entire target data set. We implement a proof of concept and present experimental results in a real-world data mining application, proving the deployment feasibility of our solution. We analyze the solution and show that its overheads are reasonable and are far outweighed by the added security benefits. For example an assurance level of over 95% can be achieved with less than 25% execution time overhead.

The scope and character of today’s computing environments are progressively shifting from traditional, one-on-one client-server interaction to the new cooperative paradigm. It then becomes of primary importance to provide means of protecting the secrecy of the information, while guaranteeing its availability to legitimate clients. Operating online querying services securely on open networks is very difficult; therefore many enterprises outsource their data center operations to external application service providers. A promising direction toward prevention of unauthorized access to outsourced data is represented by encryption. However, data encryption is often supported for the sole purpose of protecting the data in storage while allowing access to plaintext values by the server, which decrypts data for query execution. In this paper, we present a simple yet robust single-server solution for remote querying of encrypted databases on external servers. Our approach is based on the use of indexing information attached to the encrypted database, which can be used by the server to select the data to be This paper extends the previous work by the authors appeared under the title “Balancing

encryption We design an encryption scheme called Multi-dimensional Range Query over Encrypted Data (MRQED), to address the privacy concerns related to the sharing of network audit logs and various other applications. Our scheme allows a network gateway to encrypt summaries of network flows before submitting them to an untrusted repository. When network intrusions are suspected, an authority can release a key to an auditor, allowing the auditor to decrypt flows whose attributes (e.g., source and destination addresses, port numbers, etc.) fall within specific ranges. However, the privacy of all irrelevant flows are still preserved. We formally define the security for MRQED and prove the security of our construction under the decision bilinear Diffie-Hellman and decision linear assumptions in certain bilinear groups. We study the practical performance of our construction in the context of network audit logs. Apart from network audit logs, our scheme also has interesting applications for financial audit logs, medical privacy, untrusted remote storage, etc. In particular, we show that MRQED implies a solution to its dual problem, which enables investors to trade stocks through a broker in a privacy-preserving manner. 1

The erosion of trust put in traditional database servers and in Database Service Providers, the growing interest for different forms of data dissemination and the concern for protecting children from suspicious Internet content are different factors that lead to move the access control from servers to clients. Several encryption schemes can be used to serve this purpose but all suffer from a static way of sharing data. With the emergence of hardware and software security elements on client devices, more dynamic client-based access control schemes can be devised. This paper proposes an efficient client-based evaluator of access control rules for regulating access to XML documents.

Recently the cloud computing paradigm has been receiving significant excitement and attention in the media and blogosphere. To some, cloud computing seems to be little more than a marketing umbrella, encompassing topics such as distributed computing, grid computing, utility computing, and softwareas-a-service, that have already received significant research focus and commercial implementation. Nonetheless, there exist an increasing number of large companies that are offering cloud computing infrastructure products and services that do not entirely resemble the visions of these individual component topics. In this article we discuss the limitations and opportunities of deploying data management issues on these emerging cloud computing platforms (e.g., Amazon Web Services). We speculate that large scale data analysis tasks, decision support systems, and application specific data marts are more likely to take advantage of cloud computing platforms than operational, transactional database systems (at least initially). We present a list of features that a DBMS designed for large scale data analysis tasks running on an Amazon-style offering should contain. We then discuss some currently available open source and commercial database options that can be used to perform such analysis tasks, and conclude that none of these options, as presently architected, match the requisite features. We thus express the need for a new DBMS, designed specifically for cloud computing environments. 1