April 01, 2017

Hashing Garbled Circuits for Free

  • Fan X.
  • Ganesh C.
  • Kolesnikov V.

We show how to generate Garbled Circuit (GC) hash at no extra overhead during GC generation. This is in contrast with state-of-the-art approaches, which hash GCs at computational cost of about $6times$ of GC generation. GC hashing is at the core of the cut-and-choose technique of GC-based secure function evaluation (SFE). Our main idea is to intertwine hash generation/verification with GC generation and evaluation. While we allow an adversary to generate a GC $widehat{GC}$ whose hash collides with an honestly generated $GC$, such a $widehat{GC}$ w.h.p. will fail evaluation and cheating will be discovered. Our GC hash is simply a (slightly massaged) XOR of all the gate table rows of GC. We show that this is sufficient for GC-based SFE. With today's network speeds being not far behind hardware-assisted fixed-key garbling throughput, eliminating the GC hashing cost will significantly improve SFE performance. Our estimates show cost reduction by $36%$ in a typical setting, and up to factor $6$ in specialized applications relying on GC hashes.

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Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...