Towards Secure Data Outsourcing

The networked and increasingly ubiquitous nature of today’s data management services mandates assurances to detect and deter malicious or faulty behavior. This is particularly relevant for outsourced data frameworks in which clients place data management with specialized service providers. Clients are reluctant to place sensitive data under the control of a foreign party without assurances of confidentiality. Additionally, once outsourced, privacy and data access correctness (data integrity and query completeness) become paramount. Today’s solutions are fundamentally insecure and vulnerable to illicit behavior, because they do not handle these dimensions. In this chapter we will explore the state of the art in data outsourcing mechanisms providing strong security assurances of (1) correctness, (2) confidentiality, and (3) data access privacy. There exists a strong relationship between such assurances; for example, the lack of access pattern privacy usually allows for statistical attacks compromising data confidentiality. Confidentiality can be achieved by data encryption. However, to be practical, outsourced data services should allow expressive client queries (e.g., relational joins with arbitrary predicates) without compromising confidentiality. This is a hard problem because decryption keys cannot be directly provided to potentially untrusted servers. Moreover, if the remote server cannot be fully trusted, protocol correctness become essential. Here we will discuss query mechanisms targeting outsourced relational data that (i) ensure queries have been executed with integrity and completeness over their respective target data sets, (ii) allow queries to be executed with confidentiality over encrypted data, (iii) guarantee the privacy of client queries and data access patterns. We will then propose protocols that adapt to the existence of trusted hardware — so critical functionality can be delegated securely from clients to servers. We have successfully started exploring the feasibility of such solutions for providing assurances for query execution and the handling of binary predicate JOINs with full privacy in outsourced scenarios. The total cost of ownership of data management infrastructure is 5–10 times greater than the hardware costs, and more data is produced and lives digitally every day. In the coming years, secure, robust, and efficient outsourced data management will be demanded by users. It is thus important to finally achieve outsourced data management a trustworthy solution, viable in both personal-level and large corporate settings.