Networking Things - Securing the IoT through SDN and virtualization

  • Boussard M.

The talk will present results from an internal Bell Labs project that aims at giving back to users control over their connected lives. By using virtualization and software-defined networking we scout the future of connected environments, in which dedicated, isolated network overlays, within and across administrative domains, are automatically set up on behalf of the user. The resulting solution provides means for users to have fine grained control over the sharing and composition of their IoT resources, by explicitly defining which resources should be shared, with whom and how, while relieving them of the underlying networking technical complexity. We will describe the overall solution before illustrating its behavior in a number of scenarios, insisting on its benefits and challenges such as security & privacy.

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 ...