Name
Abstract | ||
|---|---|---|
In this article we introduce a technique, guaranteeing access pattern privacy against a computationally bounded adversary, in outsourced data storage, with communication and computation overheads orders of magnitude better than existing approaches. In the presence of a small amount of temporary storage (enough to store O(√n log n) items and IDs, where n is the number of items in the database), we can achieve access pattern privacy with computational complexity of less than O(log2 n) per query (as compared to, for instance, O(log4 n) for existing approaches). We achieve these novel results by applying new insights based on probabilistic analyses of data shuffling algorithms to Oblivious RAM, allowing us to significantly improve its asymptotic complexity. This results in a protocol crossing the boundary between theory and practice and becoming generally applicable for access pattern privacy. We show that on off-the-shelf hardware, large data sets can be queried obliviously orders of magnitude faster than in existing work. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2019599.2019605 | ACM Trans. Inf. Syst. Secur. |
Keywords | DocType | Volume |
Oblivious RAM,temporary storage,access pattern privacy,large data set,log2 n,asymptotic complexity,outsourced data storage,n log n,log4 n,computational complexity,Practical Oblivious Outsourced Storage | Journal | 14 |
Issue | ISSN | Citations |
2 | 1094-9224 | 3 |
PageRank | References | Authors |
0.44 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Williams | 1 | 689 | 81.07 |
| Radu Sion | 2 | 1252 | 81.36 |
| Miroslava Sotakova | 3 | 23 | 1.60 |