Historic turning point or just another chapter? The results of a foreign-policy summit. EPC Post-Summit Analysis, 24 March 2014

The March 2014 European Council could enter the history books as a turning point, not only in the EU’s relations with Russia but also in its role as a foreign policy actor. Events in Ukraine inevitably dominated the Summit, with EU leaders adopting a balanced approach aimed at achieving three key objectives – de-escalation, containment/deterrence and cooperation – based on political and economic support for Ukraine, increased but limited pressure on Russia, and moves to strengthen ties with other EU neighbours. The Summit also discussed a range of economic and environmental policy issues, with the situation in Ukraine casting a long shadow over the discussion on energy policy, but failed to reach agreement on the EU’s climate goals to 2030, or to put more flesh on the bones of calls for a European “industrial renaissance”. However, two other developments were particularly significant: the creation of the second pillar of the future banking union, establishing a single regime for winding down failing banks; and changes to the savings tax directive, bringing years of negotiation to an end.

Ukraine and the EU: turning the Association Agreement into a success story1. EPC Policy Brief, 23 April 2014

It is paradoxical and symbolic that it has taken Ukraine two waves of mass protests to conclude a new agreement with the EU. As a result, the political and geopolitical implications of the Association Agreement between the EU and Ukraine are very high. This means that it cannot be regarded merely as one of many trade agreements signed by the EU with its numerous trading partners. More attention needs to be paid to the role and impact of the Association Agreement on Ukraine. This requires screening, prioritising and sequencing of the approximation process at the national, sectoral and regional levels. Implementing the Agreement in a cost-effective way will allow Ukraine to derive benefits in the short-to-medium term, at the very time when Russia is sparing no efforts to inflict harm on the Ukrainian economy to punish the country for its European orientation.

Economic policies in the EU at a turning point. EuropEos Commentary No. 8/28 March 2011

Culminating an almost unprecedented tour de force of Council meetings in various formations, the European Council reached agreement on a comprehensive economic policy package on March 24-25th that effectively completes the economic arm of economic and monetary union (EMU) and, if consistently applied, holds out the promise of ending stagnation and dismal employment performance throughout the European Union.

EU Naval Force EUNAVFOR MED sets sail in troubled waters. CEPS Commentary, 26 June 2015

Apprehending pirates in the Indian Ocean is one thing. Defeating the networks through which smugglers traffic migrants through North Africa is quite another. The European Union’s new naval force deployment in the Mediterranean - EUNAVFOR MED - drew criticism from international partners and the general public alike when plans for a “boat-sinking” operation were unveiled, raising fears about unacceptable levels of violence and collateral damage; a European version of Mexico’s drug war. Yet the problems of EUNAVFOR MED lie less in clumsy public diplomacy than in the perilous mismatch between its stated objectives and the absence of a clear strategy and mandate, and this creates both operational and political risks for member states. Phase 1 of the operation: surveillance and assessment, has begun with no legal mandate to carry out the crucial phases 2 and 3: seek and destroy, whose military planning and outcomes are undetermined. Despite these limitations, the naval force could nevertheless mark a turning point in the EU’s security narrative, because it means that the Union is finally addressing the threats to security and the humanitarian tragedies in its southern neighbourhood.

Is the EU turning a blind eye to the 'new strongmen' of the Balkans? CEPS Commentary, 11 July 2016

"We are working on a daily basis with each and every one, to make steps towards the European integration of the Western Balkans." High Representative/Vice President Federica Mogherini Western Balkans Summit, Paris, 4 July 2016

Lightweight Internet Traffic Classification - A Subject Based Solution with Word Embeddings

Internet traffic classification is a relevant and mature research field, anyway of growing importance and with still open technical challenges, also due to the pervasive presence of Internet-connected devices into everyday life. We claim the need for innovative traffic classification solutions capable of being lightweight, of adopting a domain-based approach, of not only concentrating on application-level protocol categorization but also classifying Internet traffic by subject. To this purpose, this paper originally proposes a classification solution that leverages domain name information extracted from IPFIX summaries, DNS logs, and DHCP leases, with the possibility to be applied to any kind of traffic. Our proposed solution is based on an extension of Word2vec unsupervised learning techniques running on a specialized Apache Spark cluster. In particular, learning techniques are leveraged to generate word-embeddings from a mixed dataset composed by domain names and natural language corpuses in a lightweight way and with general applicability. The paper also reports lessons learnt from our implementation and deployment experience that demonstrates that our solution can process 5500 IPFIX summaries per second on an Apache Spark cluster with 1 slave instance in Amazon EC2 at a cost of $ 3860 year. Reported experimental results about Precision, Recall, F-Measure, Accuracy, and Cohen's Kappa show the feasibility and effectiveness of the proposal. The experiments prove that words contained in domain names do have a relation with the kind of traffic directed towards them, therefore using specifically trained word embeddings we are able to classify them in customizable categories. We also show that training word embeddings on larger natural language corpuses leads improvements in terms of precision up to 180%.