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Privacy Risk Assessment in Siemens


Nowadays we have an unprecedented opportunities of sensing, storing and analysing data describing human activities at extreme detail and resolution.
Unfortunately, personal data are sensitive, because they may allow re-identification of individuals in a de-identified database.

18 August 2017
30 September, 2017

Risk Analysis for Publishing Vehicular Data @ Toyota


Mobility data are an important source of knowledge useful for understanding human behaviour and for developing a wide range of user services. Unfortunately, this kind of data is sensitive, because people's whereabouts may allow re-identification of individuals in a de-identified database. Therefore, Data Providers, before sharing those data, must apply any sort of anonymization to lower the privacy risks, but they must be aware and capable of controlling also the data quality, since these two factors are often a trade-off.

1 July 2014
31 March, 2015

Big Data For Smart Energy

The project has the objective of creating a framework to aggregate data collected by sensors deployed in a portion of a distribution grid. The system provides functionalities to model the topological properties of the distribution grid, to harmonize and integrate readings coming from the sensors, to store and query efficiently the data, to visualize with a clear interface the timeseries collected.
1 July 2014
31 December, 2015

An Adaptive, highly Scalable Analytics Platform

This project proposes a unified, open-source execution framework for scalable data analytics. Data analytics tools have become essential for harnessing the power of our era's data deluge. Current technologies are restrictive, as their efficacy is usually bound to a single data and compute model, often depending on proprietary systems. The main idea behind ASAP is that no single execution model is suitable for all types of tasks and no single data model (and store) is suitable for all types of data. The project makes the following innovative contributions:
1 January 2015
31 December, 2016

ORANGE Telecom Projects

This project includes several experiences we have done with Orange Telecom. The first was in the in 2010 with the objective of analysing GSM data by means of algorithms developed in our lab integrated in M-Atlas system. A second experience in 2012 lead to the developing of GSM-specific algorithms able to cope with the uncertainty of this kind of data and taking advantage from the representativeness of the population presence in the long period, the result was the correlation pattern algorithm.
1 August 2011
31 December, 2014