Name
Abstract | ||
|---|---|---|
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 \(O(\log _2\psi )\) range queries, where \(\psi = N{/}H\). To address this lacuna, we present SPLIT, a new encryption scheme where the adversary requires exponentially more—\({\mathbf{O}}(\psi )\)—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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s41019-018-0081-5 | DASFAA |
Keywords | DocType | Volume |
Security, SQL, Range, Cloud | Journal | 3 |
Issue | ISSN | Citations |
4 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 14 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manish Kesarwani | 1 | 0 | 1.35 |
| Akshar Kaul | 2 | 0 | 2.03 |
| Gagandeep Singh | 3 | 0 | 1.01 |
| Prasad M. Deshpande | 4 | 1145 | 197.03 |
| Jayant R. Haritsa | 5 | 2004 | 228.38 |