Data Science and Engineering

Collusion-Resistant Processing of SQL Range Predicates

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Prior solutions for securely handling SQL range predicates in outsourced Cloud-resident databases have primarily focused on passive attacks in the Honest-but-Curious adversarial model, where the server is only permitted to observe the encrypted query processing. We consider here a significantly more powerful adversary, wherein the server can launch an active attack by clandestinely issuing specific range queries via collusion with a few compromised clients. The security requirement in this environment is that data values from a plaintext domain of size N should not be leaked to within an interval of size H. Unfortunately, all prior encryption schemes for range predicate evaluation are easily breached with only O(log 2 ψ) range queries, where ψ= N/ H. To address this lacuna, we present SPLIT, a new encryption scheme where the adversary requires exponentially more—O(ψ) —range queries to breach the interval constraint and can therefore be easily detected by standard auditing mechanisms. The novel aspect of SPLIT is that each value appearing in a range-sensitive column is first segmented into two parts. These segmented parts are then independently encrypted using a layered composition of a secure block cipher with the order-preserving encryption and prefix-preserving encryption schemes, and the resulting ciphertexts are stored in separate tables. At query processing time, range predicates are rewritten into an equivalent set of table-specific sub-range predicates, and the disjoint union of their results forms the query answer. A detailed evaluation of SPLIT on benchmark database queries indicates that its execution times are well within a factor of two of the corresponding plaintext times, testifying its efficiency in resisting active adversaries.


20 Nov 2018


Data Science and Engineering