An Autonomous Reputation Framework for Physical Locations based on WiFi Signals

  • Acer U.
  • Kawsar F.
  • Mashhadi A.
  • Vanderhulst G.

Online reviews are used on a large scale to assess the quality and reputation of urban venues like hotels, restaurants, museums, etc. However, contributing reviews requires manual effort in the digital world, undertaken by only a small fraction of a venue's visitors. In this paper, we present a framework that automatically assigns an offline reputation score by only relying on the physical presence of a user at a venue. In our approach, we passively capture the list of preferred WiFi networks (PNL) radiating from users smartphone as part of WiFi Probe requests in order to anonymously detect similar and recurrent users and to derive a personalised reputation score for an urban venue. By leveraging these ubiquitous WiFi radio signals, we seek to gather participation from a much broader set of visitors than online contributors.

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 ...