April 17, 2017

Providing for privacy in a network infrastructure protection context

Machine Learning and Big Data Analysis are seen as the silver bullet to detect and counteract attacks on critical communication infrastructure. Every message is analysed and is to some degree under suspicion. The principle of innocent until proven guilty does not seem to apply to modern communication usage. On the other hand, criminals would gain easily upper hand in communication networks that are not protected and on the outlook for attacks. This poses quite a problem for the technical implementation and handling of network communication traffic. How can a communication network provider protect user data against malicious activities without screening and data analysis and loss of the human right of privacy? This article provides a classification system for data usage, privacy sensitivity and risk through which we will illustrate on a concrete example how to provide user privacy, while still enabling protection.

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Recent Publications

June 04, 2017

A New PRACH Transmission Scheme in Unlicensed Spectrum

  • Luo Z.
  • Meng Y.
  • Tao T.

For the unlicensed spectrum, the occupied bandwidth requirement is demanded by some regulations. The legacy scheme of Physical Random Access Channel (PRACH) for Long Term Evolution (LTE) cannot satisfy it. In this paper, we propose a novel PRACH transmission scheme to satisfy the requirement of unlicensed spectrum based on preamble ...

June 01, 2017

Mutual service processes in Euclidean spaces: existence and ergodicity

  • Baccelli F.
  • Mathieu F.
  • Norros I.

Consider a set of objects, abstracted to points of a spatially stationary point process in R-d, that deliver to each other a service at a rate depending on their distance. Assume that the points arrive as a Poisson process and leave when their service requirements have been fulfilled. We show ...

June 01, 2017

Incentivizing social media users for mobile crowdsourcing

  • Aiello L.
  • Karaliopoulos M.
  • Koutsopoulos I.
  • Micholia P.
  • Morales G.
  • Quercia D.

We focus on the problem of contributor-task matching in mobile crowd-sourcing. The idea is to identify existing social media users who possess domain expertise (e.g., photography) and incentivize them to perform some tasks (e.g., take quality pictures). To this end, we propose a framework that extracts the potential contributors' expertise ...