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The Darkweb is highly popular and widely used for several types of cybercrime. Darkweb marketplaces in particular, are meeting places that provide anonymity, illegal product and service variety, and ease of use. Botmasters can utilize these platforms to acquire the necessary components needed to set up and maintain a botnet infrastructure, but also provide their services to clients. Since botnets can also be viewed from a business perspective, these components can be characterized as elements of a business model, each associated with a different botnet set of activities. In this paper, we crawl 26 marketplace and with focus on botnet-related listings form a dataset of 36,314 listings, along with 1,163 vendors. We present our aggregated findings in regard to marketplace characteristics, listings, and vendors. Additionally, we utilize the botnet Value Chain Model to correlate the targeted listings to specific model segments. With this approach we gain insight on how the business model relates to the botnet market in real time, and what significance this holds from a botmaster's point of view. Our results suggest that botmasters have a wide variety of options on all of the activities related to the botnet setup, maintenance, and revenue generation, all available within the marketplaces, at quite low prices. Lastly, we utilize the usernames and PGP keys of the vendors, in an effort to detect their potential cross-platform activity throughout the 26 platforms.

Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cross-lingual and cross-cultural communication are still omnipresent. Language Technologies (LTs) are a powerful means to break down these barriers. While the last decade has seen various initiatives that created a multitude of approaches and technologies tailored to Europe's specific needs, there is still an immense level of fragmentation. At the same time, AI has become an increasingly important concept in the European Information and Communication Technology area. For a few years now, AI, including many opportunities, synergies but also misconceptions, has been overshadowing every other topic. We present an overview of the European LT landscape, describing funding programmes, activities, actions and challenges in the different countries with regard to LT, including the current state of play in industry and the LT market. We present a brief overview of the main LT-related activities on the EU level in the last ten years and develop strategic guidance with regard to four key dimensions. Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020). To appear

The incorporation of algorithmic procedures into the automation of image production has been gradual, but has reached critical mass over the past century, especially with the advent of photography, the introduction of digital computers and the use of artificial intelligence (AI) and machine learning (ML). Due to the increasingly significant influence algorithmic processes have on visual media, there has been an expansion of the possibilities as to how images may behave, and a consequent struggle to define them. This algorithmic turn highlights inner tensions within existing notions of the image, namely raising questions regarding the autonomy of machines, author- and viewer- ship, and the veracity of representations. In this sense, algorithmic images hover uncertainly between human and machine as producers and interpreters of visual information, between representational and non-representational, and between visible surface and the processes behind it. This paper gives an introduction to fundamental internal discrepancies which arise within algorithmically produced images, examined through a selection of relevant artistic examples. Focusing on the theme of uncertainty, this investigation considers how algorithmic images contain aspects which conflict with the certitude of computation, and how this contributes to a difficulty in defining images.

This project was set out to explore the role of the Turing Test in the development of Artificial Intelligence (AI), with emphasis on the historical perspective. This report contains an introductory presentation of the Turing Test and Artificial Intelligence. Furthermore, it presents two methods for analysis. The first method is a quantitative search in extracting the number of results from Google Scholars for search range between 1950 and 2019. The searched terms are ‘Turing Test’ and ‘Artificial Intelligence’. The second method is the one used for the analysis of two case studies, ELIZA and Google Duplex. In exploring the historical development, ELIZA is an early research topic from 1966 and Google Duplex is a contemporary project from 2018. This report concludes that the Turing Test appears to have played a role in the historical development of AI. Results from the quantitative search show that there is an exponential growth, followed by a short stabilisation, before it begins to decay towards the last decade. Both case studies failed when subjected to a strict Turing Test. Though when subjected to the Total Turing Test, Google Duplex seems to surpass it. Finally, this report also concludes that the Turing Test may no longer be relevant, as mediums for AI have evolved beyond text-based and most developments are no longer concerned with tricking humans.

In the paper we describe a new EU infrastructure project dedicated to lexicography. The project is part of the Horizon 2020 program, with a duration of four years (2018-2022). The result of the project will be an infrastructure which will (1) enable efficient access to high quality lexicographic data, and (2) bridge the gap between more advanced and less-resourced scholarly communities working on lexicographic resources. One of the main issues addressed by the project is the fact that current lexicographic resources have different levels of (incompatible) structuring, and are not equally suitable for application in in Natural Language Processing and other fields. The project will therefore develop strategies, tools and standards for extracting, structuring and linking lexicographic resources to enable their inclusion in Linked Open Data and the Semantic Web, as well as their use in the context of digital humanities.