Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Efficient Set Intersection with Simulation-Based Security
IACR Journal of Cryptology (J Crypt), September 2014.
Michael J. Freedman, Carmit Hazay*, Kobbi Nissim^, Benny Pinkas†
* Faculty of Engineering, Bar-Ilan University
^ Dept. of Computer Science, Ben-Gurion University
† Dept. of Computer Science, Bar Ilan University
We consider the problem of computing the intersection of private datasets of two parties, where the datasets contain lists of elements taken from a large domain. This problem has many applications for online collaboration. In this work we present protocols based on the use of homomorphic encryption and different hashing schemes for both the semi-honest and malicious environments. The protocol for the semi-honest environment is secure in the standard model, while the protocol for the malicious environment is secure in the random oracle model. Our protocols obtain linear communication and computation overhead. We further implement different variants of our semi-honest protocol. Our experiments show that the asymptotic overhead of the protocol is affected by different constants. (In particular, the degree of the polynomials evaluated by the protocol matters less than the number of polynomials that are evaluated.) As a result, the protocol variant with the best asymptotic overhead is not necessarily preferable for inputs of reasonable size.
FULL PAPER: pdf