50,005 research outputs found
Adding Value to Statistics in the Data Revolution Age
As many statistical offices in accordance with the European Statistical System commitment to Vision 2020, since the second half of 2014 Istat has implemented its internal standardisation and industrialisation process within the framework of a common Business Architecture. Istat modernisation programme aims at building services and infrastructures within a plug-and-play framework to foster innovation, promote reuse and move towards full integration and interoperability of statistical process, consistent with a service-oriented architecture. This is expected to lead to higher effectiveness and productivity by improving the quality of statistical information and reducing the response burden. This paper addresses the strategy adopted by Istat which is focused on exploiting administrative data and new data sources in order to achieve its key goals enhancing value to users. The strategy is based on some priorities that consider services centred on users and stakeholders as well as Linked Open Data, to allow Machine-to-Machine data and metadata integration through definition of common statistical ontologies and semantics
URLs in the OPAC : comparative reflections on US vs UK practice
To examine whether placing URLs into library OPACs has been an effective way of enhancing the role of the catalogue for the contemporary library user
The future of technology enhanced active learning – a roadmap
The notion of active learning refers to the active involvement of learner in the learning process,
capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap,
the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a
best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap
Measuring and mitigating AS-level adversaries against Tor
The popularity of Tor as an anonymity system has made it a popular target for
a variety of attacks. We focus on traffic correlation attacks, which are no
longer solely in the realm of academic research with recent revelations about
the NSA and GCHQ actively working to implement them in practice.
Our first contribution is an empirical study that allows us to gain a high
fidelity snapshot of the threat of traffic correlation attacks in the wild. We
find that up to 40% of all circuits created by Tor are vulnerable to attacks by
traffic correlation from Autonomous System (AS)-level adversaries, 42% from
colluding AS-level adversaries, and 85% from state-level adversaries. In
addition, we find that in some regions (notably, China and Iran) there exist
many cases where over 95% of all possible circuits are vulnerable to
correlation attacks, emphasizing the need for AS-aware relay-selection.
To mitigate the threat of such attacks, we build Astoria--an AS-aware Tor
client. Astoria leverages recent developments in network measurement to perform
path-prediction and intelligent relay selection. Astoria reduces the number of
vulnerable circuits to 2% against AS-level adversaries, under 5% against
colluding AS-level adversaries, and 25% against state-level adversaries. In
addition, Astoria load balances across the Tor network so as to not overload
any set of relays.Comment: Appearing at NDSS 201
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