@inproceedings{15820,
  author       = {{Al-Khatib, Khalid and Hou, Yufang and Wachsmuth, Henning and Jochim, Charles and Bonin, Francesca and Stein, Benno}},
  booktitle    = {{Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)}},
  pages        = {{7367 -- 7374}},
  title        = {{{End-to-End Argumentation Knowledge Graph Construction}}},
  year         = {{2020}},
}

@inproceedings{15821,
  author       = {{Bondarenko, Alexander and Hagen, Matthias and Potthast, Martin and Wachsmuth, Henning and Beloucif, Meriem and Biemann, Chris and Panchenko, Alexander and Stein, Benno}},
  booktitle    = {{Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020)}},
  pages        = {{517--523}},
  title        = {{{Touché: First Shared Task on Argument Retrieval}}},
  year         = {{2020}},
}

@inproceedings{15825,
  author       = {{Kiesel, Johannes and Lang, Kevin and Wachsmuth, Henning and Hornecker, Eva and Stein, Benno}},
  booktitle    = {{Proceedings of the 2020 ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR 2020)}},
  pages        = {{53--62}},
  title        = {{{Investigating Expectations for Voice-based and Conversational Argument Search on the Web}}},
  year         = {{2020}},
}

@article{15836,
  author       = {{Bellman, K. and Dutt, N. and Esterle, L. and Herkersdorf, A. and Jantsch, A. and Landauer, C. and R. Lewis, P. and Platzner, Marco and TaheriNejad, N. and Tammemäe, K.}},
  journal      = {{ACM Transactions on Cyber-Physical Systems}},
  pages        = {{1--24}},
  title        = {{{Self-aware Cyber-Physical Systems}}},
  volume       = {{Accepted for Publication}},
  year         = {{2020}},
}

@article{15025,
  abstract     = {{In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available.}},
  author       = {{Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}},
  journal      = {{Evolutionary Computation}},
  number       = {{2}},
  pages        = {{165–193}},
  publisher    = {{MIT Press Journals}},
  title        = {{{Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets}}},
  doi          = {{10.1162/evco_a_00266}},
  volume       = {{28}},
  year         = {{2020}},
}

@inproceedings{15169,
  author       = {{Castenow, Jannik and Kolb, Christina and Scheideler, Christian}},
  booktitle    = {{Proceedings of the 21st International Conference on Distributed Computing and Networking (ICDCN)}},
  location     = {{Kolkata, Indien}},
  publisher    = {{ACM}},
  title        = {{{A Bounding Box Overlay for Competitive Routing in Hybrid Communication Networks}}},
  year         = {{2020}},
}

@inbook{15267,
  author       = {{Yigitbas, Enes and Jovanovikj, Ivan and Sauer, Stefan and Engels, Gregor}},
  booktitle    = {{Handling Security, Usability, User Experience and Reliability in User-Centered Development Processes - IFIP WG 13.2/13.5}},
  publisher    = {{Springer, LNCS}},
  title        = {{{On the Development of Context-aware Augmented Reality Applications }}},
  year         = {{2020}},
}

@inproceedings{16213,
  abstract     = {{Automated synthesis of approximate circuits via functional approximations is of prominent importance to provide efficiency in energy, runtime, and chip area required to execute an application. Approximate circuits are usually obtained either through analytical approximation methods leveraging approximate transformations such as bit-width scaling or via iterative search-based optimization methods when a library of approximate components, e.g., approximate adders and multipliers, is available. For the latter, exploring the extremely large design space is challenging in terms of both computations and quality of results. While the combination of both methods can create more room for further approximations, the \textit{Design Space Exploration}~(DSE) becomes a crucial issue. In this paper, we present such a hybrid synthesis methodology that applies a low-cost analytical method followed by parallel stochastic search-based optimization. We address the DSE challenge through efficient pruning of the design space and skipping unnecessary expensive testing and/or verification steps. The experimental results reveal up to 10.57x area savings in comparison with both purely analytical or search-based approaches. }},
  author       = {{Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}},
  booktitle    = {{Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020}},
  location     = {{Beijing, China}},
  pages        = {{421--426}},
  publisher    = {{ACM}},
  title        = {{{A Hybrid Synthesis Methodology for Approximate Circuits}}},
  doi          = {{10.1145/3386263.3406952}},
  year         = {{2020}},
}

@inproceedings{16219,
  abstract     = {{Network function virtualization (NFV) proposes
to replace physical middleboxes with more flexible virtual
network functions (VNFs). To dynamically adjust to everchanging
traffic demands, VNFs have to be instantiated and
their allocated resources have to be adjusted on demand.
Deciding the amount of allocated resources is non-trivial.
Existing optimization approaches often assume fixed resource
requirements for each VNF instance. However, this can easily
lead to either waste of resources or bad service quality if too
many or too few resources are allocated.

To solve this problem, we train machine learning models
on real VNF data, containing measurements of performance
and resource requirements. For each VNF, the trained models
can then accurately predict the required resources to handle
a certain traffic load. We integrate these machine learning
models into an algorithm for joint VNF scaling and placement
and evaluate their impact on resulting VNF placements. Our
evaluation based on real-world data shows that using suitable
machine learning models effectively avoids over- and underallocation
of resources, leading to up to 12 times lower resource
consumption and better service quality with up to 4.5 times
lower total delay than using standard fixed resource allocation.}},
  author       = {{Schneider, Stefan Balthasar and Satheeschandran, Narayanan Puthenpurayil and Peuster, Manuel and Karl, Holger}},
  booktitle    = {{IEEE Conference on Network Softwarization (NetSoft)}},
  location     = {{Ghent, Belgium}},
  publisher    = {{IEEE}},
  title        = {{{Machine Learning for Dynamic Resource Allocation in Network Function Virtualization}}},
  year         = {{2020}},
}

@inproceedings{16222,
  author       = {{Zafeiropoulos, A. and Fotopoulou, E. and Peuster, Manuel and Schneider, Stefan Balthasar and Gouvas, P. and Behnke, D. and Müller, M. and Bök, P. and Trakadas, P. and Karkazis, P. and Karl, Holger}},
  booktitle    = {{IEEE Conference on Network Softwarization (NetSoft)}},
  title        = {{{Benchmarking and Profiling 5G Verticals' Applications: An Industrial IoT Use Case}}},
  year         = {{2020}},
}

@inproceedings{16274,
  author       = {{Jovanovikj, Ivan and Nagaraj, Achyuth and Yigitbas, Enes and Anjorin, Anthony and Sauer, Stefan and Engels, Gregor}},
  booktitle    = {{Proceedings of the 1st IEEE/ACM International Conference on Automation of Software Test AST}},
  location     = {{Seoul}},
  pages        = {{31--40}},
  publisher    = {{ACM}},
  title        = {{{Validating Test Case Migration via Mutation Analysis }}},
  year         = {{2020}},
}

@article{16278,
  abstract     = {{Currently, the coexistence of multiple users and devices challenges the network's ability to reliably connect them. This article proposes a novel communication architecture that satisfies the requirements of fifth-generation (5G) mobile network applications. In particular, this architecture extends and combines ultra-dense networking (UDN), multi-access edge computing (MEC), and virtual infrastructure manager (VIM) concepts to provide a flexible network of moving radio access (RA) nodes, flying or moving to areas where users and devices struggle for connectivity and data rate. Furthermore, advances in radio communications and non-orthogonal multiple access (NOMA), virtualization technologies and energy-awareness mechanisms are integrated towards a mobile UDN that not only allows RA nodes to follow the user but also enables the virtualized network functions (VNFs) to adapt to user mobility by migrating from one node to another. Performance evaluation shows that the underlying network improves connectivity of users and devices through the flexible deployment of moving RA nodes and the use of NOMA.}},
  author       = {{Nomikos, Nikolaos and Michailidis, Emmanouel T. and Trakadas, Panagiotis and Vouyioukas, Demosthenes and Karl, Holger and Martrat, Josep and Zahariadis, Theodore and Papadopoulos, Konstantinos and Voliotis, Stamatis}},
  issn         = {{2214-2096}},
  journal      = {{Vehicular Communications}},
  title        = {{{A UAV-based moving 5G RAN for massive connectivity of mobile users and IoT devices}}},
  doi          = {{10.1016/j.vehcom.2020.100250}},
  year         = {{2020}},
}

@article{16280,
  abstract     = {{Assigning bands of the wireless spectrum as resources to users is a common problem in wireless networks. Typically, frequency bands were assumed to be available in a stable manner. Nevertheless, in recent scenarios where wireless networks may be deployed in unknown environments, spectrum competition is considered, making it uncertain whether a frequency band is available at all or at what quality. To fully exploit such resources with uncertain availability, the multi-armed bandit (MAB) method, a representative online learning technique, has been applied to design spectrum scheduling algorithms. This article surveys such proposals. We describe the following three aspects: how to model spectrum scheduling problems within the MAB framework, what the main thread is following which prevalent algorithms are designed, and how to evaluate algorithm performance and complexity. We also give some promising directions for future research in related fields.}},
  author       = {{Li, Feng and Yu, Dongxiao and Yang, Huan and Yu, Jiguo and Karl, Holger and Cheng, Xiuzhen}},
  issn         = {{1536-1284}},
  journal      = {{IEEE Wireless Communications}},
  pages        = {{24--30}},
  title        = {{{Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey}}},
  doi          = {{10.1109/mwc.001.1900280}},
  year         = {{2020}},
}

@article{16299,
  author       = {{Castenow, Jannik and Fischer, Matthias and Harbig, Jonas and Jung, Daniel and Meyer auf der Heide, Friedhelm}},
  issn         = {{0304-3975}},
  journal      = {{Theoretical Computer Science}},
  pages        = {{289--309}},
  title        = {{{Gathering Anonymous, Oblivious Robots on a Grid}}},
  doi          = {{10.1016/j.tcs.2020.02.018}},
  volume       = {{815}},
  year         = {{2020}},
}

@inproceedings{16363,
  author       = {{Hansmeier, Tim and Kaufmann, Paul and Platzner, Marco}},
  booktitle    = {{GECCO '20: Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-7127-8}},
  location     = {{Cancún, Mexico}},
  pages        = {{125--126}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Enabling XCSF to Cope with Dynamic Environments via an Adaptive Error Threshold}}},
  doi          = {{10.1145/3377929.3389968}},
  year         = {{2020}},
}

@inproceedings{16400,
  abstract     = {{Softwarization facilitates the introduction of smart
manufacturing applications in the industry. Manifold devices
such as machine computers, Industrial IoT devices, tablets,
smartphones and smart glasses are integrated into factory networks
to enable shop floor digitalization and big data analysis. To
handle the increasing number of devices and the resulting traffic,
a flexible and scalable factory network is necessary which can be
realized using softwarization technologies like Network Function
Virtualization (NFV). However, the security risks increase with
the increasing number of new devices, so that cyber security must
also be considered in NFV-based networks.

Therefore, extending our previous work, we showcase threat
detection using a cloud-native NFV-driven intrusion detection
system (IDS) that is integrated in our industrial-specific network
services. As a result of the threat detection, the affected network
service is put into quarantine via automatic network reconfiguration.
We use the 5GTANGO service platform to deploy our
developed network services on Kubernetes and to initiate the
network reconfiguration.}},
  author       = {{Müller, Marcel and Behnke, Daniel and Bök, Patrick-Benjamin and Schneider, Stefan Balthasar and Peuster, Manuel and Karl, Holger}},
  booktitle    = {{IEEE Conference on Network Softwarization (NetSoft) Demo Track}},
  location     = {{Ghent, Belgium}},
  publisher    = {{IEEE}},
  title        = {{{Cloud-Native Threat Detection and Containment for Smart Manufacturing}}},
  year         = {{2020}},
}

@inproceedings{13868,
  author       = {{Pukrop, Simon and Mäcker, Alexander and Meyer auf der Heide, Friedhelm}},
  booktitle    = {{Proceedings of the 46th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM)}},
  title        = {{{Approximating Weighted Completion Time for Order Scheduling with Setup Times}}},
  year         = {{2020}},
}

@article{10330,
  author       = {{Kiesel, Dora and Riehmann, Patrick and Wachsmuth, Henning and Stein, Benno and Fröhlich, Bernd}},
  journal      = {{IEEE Transactions of Visualization & Computer Graphics}},
  number       = {{2}},
  pages        = {{1139--1148}},
  title        = {{{Visual Analysis of Argumentation in Essays}}},
  volume       = {{27}},
  year         = {{2020}},
}

@inproceedings{25336,
  abstract     = {{OpenPGP and S/MIME are two major standards for securing email communication introduced in the early 1990s. Three recent classes of attacks exploit weak cipher modes (EFAIL Malleability Gadgets, or EFAIL-MG), the flexibility of the MIME email structure (EFAIL Direct Exfiltration, or EFAIL-DE), and the Reply action of the email client (REPLY attacks). Although all three break message confidentiality by using standardized email features, only EFAIL-MG has been mitigated in IETF standards with the introduction of AEAD algorithms. So far, no uniform and reliable countermeasures have been adopted by email clients to prevent EFAIL-DE and REPLY attacks. Instead, email clients implement a variety of different ad-hoc countermeasures which are only partially effective, cause interoperability problems, and fragment the secure email ecosystem.We present the first generic countermeasure against both REPLY and EFAIL-DE attacks by checking the decryption context including SMTP headers and MIME structure during decryption. The decryption context is encoded into a string DC and used as Associated Data (AD) in the AEAD encryption. Thus the proposed solution seamlessly extends the EFAIL-MG countermeasures. The decryption context changes whenever an attacker alters the email source code in a critical way, for example, if the attacker changes the MIME structure or adds a new Reply-To header. The proposed solution does not cause any interoperability problems and legacy emails can still be decrypted. We evaluate our approach by implementing the decryption contexts in Thunderbird/Enigmail and by verifying their correct functionality after the email has been transported over all major email providers, including Gmail and iCloud Mail.}},
  author       = {{Schwenk, Jörg and Brinkmann, Marcus and Poddebniak, Damian and Müller, Jens and Somorovsky, Juraj and Schinzel, Sebastian}},
  booktitle    = {{Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security}},
  isbn         = {{9781450370899}},
  keywords     = {{decryption contexts, EFAIL, OpenPGP, S/MIME, AEAD}},
  pages        = {{1647–1664}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{Mitigation of Attacks on Email End-to-End Encryption}}},
  doi          = {{10.1145/3372297.3417878}},
  year         = {{2020}},
}

@phdthesis{16935,
  author       = {{Moussalem, Diego Campos}},
  title        = {{{Knowledge Graphs for Multilingual Language Translation and Generation}}},
  doi          = {{10.17619/UNIPB/1-980}},
  year         = {{2020}},
}

