ERCIM News 107
October 2016
Special theme Machine Learning
Guest editors Sander Bohte (CWI ) and Hung Son Nguyen (University of Warsaw)
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- Category: Research and Innovation
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by Patrizio Dazzi (ISTI-CNR)
Cloud Computing and mobile applications are key drivers for innovation. However, mobile device limitations still hinder today’s mobile applications from reaching their full potential. The joint South-Korea and EU Horizon 2020 project BASMATI is developing an integrated brokerage platform that targets federated clouds and supports the dynamic needs of mobile applications and users.
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- Category: Research and Innovation
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by Olivier Parisot and Benoît Otjacques (Luxembourg Institute of Science and Technology)
In order to support knowledge extraction from data streams, we propose a visual platform for quickly identifying main features and for computing predictive models in real time. To this end, we have adapted state-of-the-art algorithms in stream learning and visualisation.
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- Category: Research and Innovation
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by Marios Dikaiakos, George Pallis (University of Cyprus) and Evangelos Markatos (FORTH)
MANDOLA wants to make a bold step towards improving our understanding of the prevalence and spread of online hate speech and towards empowering ordinary citizens and policy makers to monitor and report hate speech.
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- Category: Research and Innovation
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by Markus Wurzenberger and Florian Skopik (AIT Austrian Institute of Technology)
Recent years have seen a dramatic increase in damage caused by cyber-criminals. Although there are many IT security tools on the market, there is currently no way to test, compare and evaluate them without actually running them in real systems. The BÆSE testbed offers a solution to challenge and benchmark IT security solutions for dedicated network environments under attack conditions, without putting real systems in danger.
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- Category: Research and Innovation
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by Dimitrios Serpanos (University of Patras and ISI), Howard Shrobe (CSAIL/MIT) and Muhammad Taimoor Khan (University of Klagenfurt)
Behaviour-based security enables industrial control systems to address a wider range of risks than classical IT security, providing an integrated approach to detecting security attacks, dependability failures and violation of safety properties.
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- Category: Research and Innovation
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by Nicolas Mayer, Jocelyn Aubert, Hervé Cholez, Eric Grandry and Eric Dubois
The objective of our project is to adapt and facilitate Information System (IS) security risk management in the telecommunications sector. To this end, we have developed: first, a model-based approach and a tool to support the adoption of IS security risk management by Luxembourg’s telecommunications service providers (TSPs); and second, a framework to analyse the data collected by Luxembourg’s National Regulation Authority (NRA).
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- Category: Research and Innovation
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by Darko Brodić, Dejan Tanikić (University of Belgrade), and Alessia Amelio (University of Calabria)
Known laptop characteristics can be used to create a model that predicts the extremely low frequency magnetic field radiation emitted at the top and underside of laptops.
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- Category: Research and Innovation
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by Erkuden Rios (Tecnalia), Massimiliano Rak (Second University of Naples) and Samuel Olaiya Afolaranmi (Tampere University of Technology)
MUSA (MUlti-cloud Secure Applications) is an EU H2020 funded research project which is aimed at ensuring security in multi-cloud environments. The main goal of MUSA is to support the lifecycle of applications with strict security requirements over heterogenous cloud resources. MUSA will result in a security framework that includes security-by-design mechanisms as well as runtime security monitoring and enforcement to mitigate security incidents.