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- Yevgeniy Dodis, Ariel Elbaz, Roberto Oliveira, Ran Raz
- APPROX-RANDOM
- 2004

Given two independent weak random sources X,Y , with the same length l and min-entropies bX , bY whose sum is greater than l + Ω(polylog(l/ε)), we construct a deterministic two-source extractor (aka “blender”) that extracts max(bX , bY ) + (bX + bY − l − 4 log(1/ε)) bits which are ε-close to uniform. In contrast, best previously published construction [4]… (More)

- Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andrew Wan
- Journal of Machine Learning Research
- 2005

We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possible examples. Previous research has suggested that the Random Walk model is more powerful than comparable standard models of learning from independent examples, by exhibiting… (More)

- Seung Geol Choi, Ariel Elbaz, Ari Juels, Tal Malkin, Moti Yung
- ASIACRYPT
- 2007

We consider a new model for online secure computation on encrypted inputs in the presence of malicious adversaries. The inputs are independent of the circuit computed in the sense that they can be contributed by separate third parties. The model attempts to emulate as closely as possible the model of “Computing with Encrypted Data” that was put forth in… (More)

We present the problem of Oblivious Image Matching, where two parties want to determine whether they have images of the same object or scene, without revealing any additional information. While image matching has attracted a great deal of attention in the computer vision community, it was never treated in a cryptographic sense. In this paper we study the… (More)

- Shai Avidan, Ariel Elbaz, Tal Malkin
- 2008 15th IEEE International Conference on Image…
- 2008

We give efficient and practical protocols for privacy preserving pattern classification that allow a client to have his data classified by a server, without revealing information to either party, other than the classification result. We illustrate the advantages of such a framework on several real-world scenarios and give secure protocols for several… (More)

- Seung Geol Choi, Ariel Elbaz, Tal Malkin, Moti Yung
- ASIACRYPT
- 2009

Multi-party secure computations are general important procedures to compute any function while keeping the security of private inputs. In this work we ask whether preprocessing can allow low latency (that is, small round) secure multi-party protocols that are universally-composable (UC). In particular, we allow any polynomial time preprocessing as long as… (More)

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