A guided tour of Chernoff bounds
Information Processing Letters
Software protection and simulation on oblivious RAMs
Journal of the ACM (JACM)
Foundations of Cryptography: Basic Tools
Foundations of Cryptography: Basic Tools
Introduction to Algorithms
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Querying Databases Privately: A New Approach To Private Information Retrieval.
Querying Databases Privately: A New Approach To Private Information Retrieval.
The pynchon gate: a secure method of pseudonymous mail retrieval
Proceedings of the 2005 ACM workshop on Privacy in the electronic society
Improving the Robustness of Private Information Retrieval
SP '07 Proceedings of the 2007 IEEE Symposium on Security and Privacy
An Efficient PIR Construction Using Trusted Hardware
ISC '08 Proceedings of the 11th international conference on Information Security
Building castles out of mud: practical access pattern privacy and correctness on untrusted storage
Proceedings of the 15th ACM conference on Computer and communications security
Private information retrieval using trusted hardware
ESORICS'06 Proceedings of the 11th European conference on Research in Computer Security
PrivateFS: a parallel oblivious file system
Proceedings of the 2012 ACM conference on Computer and communications security
Access privacy and correctness on untrusted storage
ACM Transactions on Information and System Security (TISSEC)
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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.