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The security of critical infrastructures is of paramount importance nowadays due to the growing complexity of components and applications. This paper collects the contributions to the industry dissemination session within the 14th International Conference on Critical Information Infrastructures Security (CRITIS 2019). As such, it provides an overview of recent practical experience reports in the field of critical infrastructure protection (CIP), involving major industry players. The set of cases reported in this paper includes the usage of serious gaming for training infrastructure operators, integrated safety and security management in the chemical/process industry, risks related to the cyber-economy for energy suppliers, smart troubleshooting in the Internet of Things (IoT), as well as intrusion detection in power distribution Supervisory Control And Data Acquisition (SCADA). The session has been organized to stimulate an open scientific discussion about industry challenges, open issues and future opportunities in CIP research.

Marked mix-nets were introduced by Pereira and Rivest as a mechanism to allow very efficient mixing that ensures privacy but at the cost of not guaranteeing integrity. This is useful in a number of e-voting schemes such as STAR-Vote and Selene. However, the proposed marked mix-net construction comes with no proof of security and, as we show in this paper, does not provide privacy even in the presence of a single corrupt authority. Fortunately, the attack that we present is easy to prevent and we show several possible ways to address it. Finally while the original marked mix-net paper worked with ElGamal, we identify conditions that the adopted encryption scheme should satisfy in order to be appropriate for a marked mix-net. This opens the possibility of building marked mix-nets based on intractability assumptions which are believed to hold in the presence of a quantum computer.

Recent years have seen many privacy violations that have cost both the users of software systems and the businesses that run them in a variety of ways. One potential cause of these violations may be the ad hoc nature of the implementation of privacy measures within software systems, which may stem from the poor representation of privacy within many Software Development LifeCycle (SDLC) processes. We propose to give privacy a higher priority within the SDLC through the creation of a confederated Privacy-Aware SDLC (PASDLC) which incorporates the Data Protection Impact Assessment (DPIA) lifecycle. The PASDLC brings stakeholders of the software system closer together through the implementation of multiple interception points, whilst prompting the stakeholders to consider privacy within the software system. We consider many challenges to the creation of the PASDLC, including potential communication issues from confederating the processes of a SDLC and the effective measurement of privacy as an attribute of a software system. Postprint

Our life depends more and more on intelligent machines that help us carry out our work or have completely taken our place in tasks which used to be wholly human. This also applies to the field of care and assistance for the sick and fragile: indeed, carebots are increasingly present by the patient’s bed and can collaborate in care work. However carebots are not objects like others that we use in our everyday life: unlike the tools through which we do things, robots have (and will more and more have) some level of autonomy. We intend to consider the type of relationship it is right to build with these devices and ask whether intelligent robots deserve some moral and legal relevance. The robot may be seen as a slave or an entity with which we can form friendships or loving relationships: we will maintain that it is our responsibility to prepare for future scenarios in which increasingly intelligent, autonomous machines will be not mere tools, but significant life companions.

In over fve years, Bornmann, Stefaner, de Moya Anegon, and Mutz (2014b) and Bornmann, Stefaner, de Moya Anegón, and Mutz (2014c, 2015) have published several releases of the www.excellencemapping.net tool revealing (clusters of) excellent institutions worldwide based on citation data. With the new release, a completely revised tool has been published. It is not only based on citation data (bibliometrics), but also Mendeley data (altmetrics). Thus, the institutional impact measurement of the tool has been expanded by focusing on additional status groups besides researchers such as students and librarians. Furthermore, the visualization of the data has been completely updated by improving the operability for the user and including new features such as institutional profle pages. In this paper, we describe the datasets for the current excellencemapping.net tool and the indicators applied. Furthermore, the underlying statistics for the tool and the use of the web application are explained.

This paper presents a demonstration of our PAAMS 2021 paper using data-driven analysis of airport terminal operations and An Agent-based Airport Terminal Operations Model Simulator (AATOM). The goal of this paper is to demonstrate and analyze the impact of the current COVID-19 and future pandemic-related measures on airport terminal operations and to identify plans that airport management agents can take into account to control the flow of passengers in a safe, efficient, secure and resilient way. To analyze the impact of the identified COVID-19 measures on the airport operations, the existing agent-based AATOM model was need to be modified in order to implement these measures. In this paper, we illustrate a demo of a developed simulator tool by investigating the effects of different degrees of physical distancing rules among agents on the performances of the airport. In the demo session the attendees will have the possibility to (i) work with the simulator tool on different relevant parameters regarding different sections and agents in the airport; (ii) view and analyze different performance indicator analyzers of the simulator.

Full list of authors: Gurvits, Leonid I.; Paragi, Zsolt ; Casasola, Viviana; Conway, John; Davelaar, Jordy; Falcke, Heino; Fender, Rob; Frey, Sándor; Fromm, Christian M.; Miró, Cristina García; Garrett, Michael A.; Giroletti, Marcello; Goddi, Ciriaco; Gómez, José-Luis; van der Gucht, Jeffrey; Guirado, José Carlos; Haiman, Zoltán; Helmich, Frank; Humphreys, Elizabeth; Impellizzeri, Violette; Kramer, Michael; Lindqvist, Michael; Linz, Hendrik; Liuzzo, Elisabetta; Lobanov, Andrei P.; Mizuno, Yosuke; Rezzolla, Luciano; Roelofs, Freek; Ros, Eduardo; Rygl, Kazi L. J.; Savolainen, Tuomas; Schuster, Karl; Venturi, Tiziana; Wiedner, Martina C.; Zensus, J. Anton.-- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/., This paper presents the ESA Voyage 2050 White Paper for a concept of TeraHertz Exploration and Zooming-in for Astrophysics (THEZA). It addresses the science case and some implementation issues of a space-borne radio interferometric system for ultra-sharp imaging of celestial radio sources at the level of angular resolution down to (sub-) microarcseconds. THEZA focuses at millimetre and sub-millimetre wavelengths (frequencies above ∼ 300 GHz), but allows for science operations at longer wavelengths too. The THEZA concept science rationale is focused on the physics of spacetime in the vicinity of supermassive black holes as the leading science driver. The main aim of the concept is to facilitate a major leap by providing researchers with orders of magnitude improvements in the resolution and dynamic range in direct imaging studies of the most exotic objects in the Universe, black holes. The concept will open up a sizeable range of hitherto unreachable parameters of observational astrophysics. It unifies two major lines of development of space-borne radio astronomy of the past decades: Space VLBI (Very Long Baseline Interferometry) and mm- and sub-mm astrophysical studies with “single dish” instruments. It also builds upon the recent success of the Earth-based Event Horizon Telescope (EHT) – the first-ever direct image of a shadow of the super-massive black hole in the centre of the galaxy M87. As an amalgam of these three major areas of modern observational astrophysics, THEZA aims at facilitating a breakthrough in high-resolution high image quality studies in the millimetre and sub-millimetre domain of the electromagnetic spectrum. © 2021, The Author(s)., With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709.

The ever-increasing number of published scientific articles has prompted the need for automated, data-driven approaches to summarizing the content of scientific articles. The Computational Linguistics Scientific Document Summarization Shared Task (CL-SciSumm 2019) has recently fostered the study and development of new text mining and machine learning solutions to the summarization problem customized to the academic domain. In CL-SciSumm, a Reference Paper (RP) is associated with a set of Citing Papers (CPs), all containing citations to the RP. In each CP, the text spans (i.e., citances) have been identified that pertain to a particular citation to the RP. The task of identifying the spans of text in the RP that most accurately reflect the citance is addressed using supervised approaches. This paper proposes a new, more effective solution to the CL-SciSumm discourse facet classification task, which entails identifying for each cited text span what facet of the paper it belongs to from a predefined set of facets. It proposes also to extend the set of traditional CL-SciSumm tasks with a new one, namely the discourse facet summarization task. The idea behind is to extract facet-specific descriptions of each RP consisting of a fixed-length collection of RP’s text spans. To tackle both the standard and the new tasks, we propose machine learning supported solutions based on the extraction of a selection of discriminating words, called pivot words. Predictive features based on pivot words are shown to be of great importance to rate the pertinence and relevance of a text span to a given facet. The newly proposed facet classification method performs significantly better than the best performing CL-SciSumm 2019 participant (i.e., the classification accuracy has increased by + 8%), whereas regression methods achieved promising results for the newly proposed summarization task.

In this demo paper, we describe a Multi Agent System (MAS) application for monitoring and evaluation of the ethical behavior of customer service agents in an online chat point w.r.t their institution/company’s codes of ethics and conduct. This MAS is realized using the state-of-the-art JaCaMo framework, and can be practically demonstrated to an audience.

[Context and motivation] Modern software engineering processes have shifted from traditional upfront requirements engineering (RE) to a more continuous way of conducting RE, particularly including data-driven approaches. [Question/problem] However, current research on data-driven RE focuses more on leveraging certain techniques such as natural language processing or machine learning than on making the concept fit for facilitating its use in the entire software development process. [Principal ideas/results] In this paper, we propose a research agenda composed of six distinct research directions. These include a data-driven RE infrastructure, embracing data heterogeneity, context-aware adaptation, data analysis and decision support, privacy and confidentiality, and finally process integration. Each of these directions addresses challenges that impede the broader use of data-driven RE. [Contribution] For researchers, our research agenda provides topics relevant to investigate. For practitioners, overcoming the underlying challenges with the help of the proposed research will allow to adopt a data-driven RE approach and facilitate its seamless integration into modern software engineering. For users, the proposed research will enable the transparency, control, and security needed to trust software systems and software providers. This work has been supported by: the Spanish project GENESIS (TIN2016-79269-R), the Christian Doppler Forschungsgesellschaft, the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, and the Austrian Science Fund (FWF) under the grant numbers J3998-N31, P28519-N31, and P30525-N31.