Goldmining in a River of Internet Content Traffic

  • Alessandro Finamore
  • Ben Houidi Z.
  • Ghamri-Doudane S.
  • Marco Mellia
  • Scavo G.
  • Stefano Traverso

With the advent of Over-The-Top content providers (OTTs), Internet Service Providers (ISPs) saw their portfolio of services shrink to the low margin role of data transporters. In order to counter this effect, some ISPs started to follow big OTTs like Facebook and Google in trying to turn their data into a valuable asset. In this paper, we explore the questions of what meaningful information can be extracted from network data, and what interesting insights it can provide. To this end, we tackle the first challenge of detecting ``user-URLs'', i.e., those that were clicked by users as opposed to those automatically generated by browsers and applications. We devise algorithms to pinpoint such URLs, and validate them on manually collected ground truth traces. We then apply them on a three-day long traffic trace spanning more than 19,000 residential users that requested around 190 million web objects. We find that only 1.6% of these observed URLs were actually clicked by users. As a first application for our methods, we answer the question of which platforms participate most in promoting the Internet content. Surprisingly, we find that, despite its notoriety, only 10% of the user URL visits are coming from Google search.

Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

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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

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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

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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 ...