@inbook{42654, author = {{Liebendörfer, Michael and Hochmuth, Reinhard and Biehler, Rolf and Schaper, Niclas and Büdenbender-Kuklinski, Christiane and Lankeit, Elisa and Ruge, Johanna and Schürmann, Mirko}}, booktitle = {{Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse}}, editor = {{Hochmuth, Reinhard and Biehler, Rolf and Liebendörfer, Michael and Schaper, Niclas}}, isbn = {{9783662648322}}, issn = {{2197-8751}}, pages = {{33--65}}, publisher = {{Springer}}, title = {{{Ein Rahmenmodell für hochschuldidaktische Maßnahmen in der Mathematik}}}, doi = {{10.1007/978-3-662-64833-9_2}}, year = {{2022}}, } @inbook{46160, author = {{Wessel, Lena and Leuders, Timo}}, booktitle = {{Practice-Oriented Research in Tertiary Mathematics Education}}, editor = {{Biehler, Rolf and Liebendörfer, Michael and Gueudet, G. and Rasmussen, C. and Winslow, C.}}, isbn = {{9783031141744}}, issn = {{1869-4918}}, pages = {{349--368}}, publisher = {{Springer International Publishing}}, title = {{{Profession-Specific Curriculum Design in Mathematics Teacher Education: Connecting Disciplinary Practice to the Learning of Group Theory}}}, doi = {{10.1007/978-3-031-14175-1_17}}, year = {{2022}}, } @inproceedings{53052, author = {{Kolbe, Tim and Wessel, Lena}}, booktitle = {{Fourth conference of the International Network for Didactic Research in University Mathematics}}, editor = {{Trigueros, Maria and Baerquero, Berta and Hochmuth, Reinhard and Peters, Jana}}, location = {{Hannover}}, pages = {{632--641}}, title = {{{Self-regulated learning in a mathematics course for engineers in the first semester: insights into students reported resource management and cognitive strategies}}}, year = {{2022}}, } @inbook{42655, author = {{Schürmann, Mirko and Liebendörfer, Michael and Büdenbender-Kuklinski, Christiane and Lankeit, Elisa and Ruge, Johanna and Schaper, Niclas and Biehler, Rolf and Hochmuth, Reinhard}}, booktitle = {{Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse}}, editor = {{Hochmuth, Reinhard and Biehler, Rolf and Liebendörfer, Michael and Schaper, Niclas}}, isbn = {{9783662648322}}, issn = {{2197-8751}}, pages = {{67--113}}, publisher = {{Springer}}, title = {{{Evaluation von Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen}}}, doi = {{10.1007/978-3-662-64833-9_3}}, year = {{2022}}, } @article{45334, author = {{Schönherr, Johanna and Schukajlow, S. and Blomberg, J. and Leopold, C.}}, journal = {{Applied Cognitive Psychology, ac3930}}, number = {{2}}, pages = {{402--417}}, title = {{{Effects of drawing instructions and strategic knowledge on mathematical modeling performance: Mediated by the use of the drawing strategy}}}, doi = {{10.1002/acp.3930}}, volume = {{36}}, year = {{2022}}, } @inproceedings{45339, author = {{Schönherr, Johanna and Schukajlow, S. and Leopold, C.}}, booktitle = {{Proceedings of the 45th PME Conference}}, pages = {{347–354}}, title = {{{Drawing instructions, strategic knowledge, strategy-based motivation, and students' use of drawings}}}, volume = {{3}}, year = {{2022}}, } @article{53952, author = {{Massacci, Fabio and Sabetta, Antonino and Mirkovic, Jelena and Murray, Toby and Okhravi, Hamed and Mannan, Mohammad and Rocha, Anderson and Bodden, Eric and Geer, Daniel E.}}, issn = {{1540-7993}}, journal = {{IEEE Security & Privacy}}, number = {{5}}, pages = {{16--21}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{“Free” as in Freedom to Protest?}}}, doi = {{10.1109/msec.2022.3185845}}, volume = {{20}}, year = {{2022}}, } @inproceedings{54435, abstract = {{Web browsers are among the most important but also complex software solutions to access the web. It is therefore not surprising that web browsers are an attractive target for attackers. Especially in the last decade, security researchers and browser vendors have developed sandboxing mechanisms like security-relevant HTTP headers to tackle the problem of getting a more secure browser. Although the security community is aware of the importance of security-relevant HTTP headers, legacy applications and individual requests from different parties have led to possible insecure configurations of these headers. Even if specific security headers are configured correctly, conflicts in their functionalities may lead to unforeseen browser behaviors and vulnerabilities. Recently, the first work which analyzed duplicated headers and conflicts in headers was published by Calzavara et al. at USENIX Security [1]. The authors focused on inconsistent protections by using both, the HTTP header X-Frame-Options and the framing protection of the Content-Security-Policy. We extend their work by analyzing browser behaviors when parsing duplicated headers, conflicting directives, and values that do not conform to the defined ABNF metalanguage specification. We created an open-source testbed running over 19,800 test cases, at which nearly 300 test cases are executed in the set of 66 different browsers. Our work shows that browsers conform to the specification and behave securely. However, all tested browsers behave differently when it comes, for example, to parsing the Strict-Transport-Security header. Moreover, Chrome, Safari, and Firefox behave differently if the header contains a character, which is not allowed by the defined ABNF. This results in the protection mechanism being fully enforced, partially enforced, or not enforced and thus completely bypassable.}}, author = {{Siewert, Hendrik and Kretschmer, Martin and Niemietz, Marcus and Somorovsky, Juraj}}, booktitle = {{2022 IEEE Security and Privacy Workshops (SPW)}}, publisher = {{IEEE}}, title = {{{On the Security of Parsing Security-Relevant HTTP Headers in Modern Browsers}}}, doi = {{10.1109/spw54247.2022.9833880}}, year = {{2022}}, } @inproceedings{29290, abstract = {{Classifying nodes in knowledge graphs is an important task, e.g., predicting missing types of entities, predicting which molecules cause cancer, or predicting which drugs are promising treatment candidates. While black-box models often achieve high predictive performance, they are only post-hoc and locally explainable and do not allow the learned model to be easily enriched with domain knowledge. Towards this end, learning description logic concepts from positive and negative examples has been proposed. However, learning such concepts often takes a long time and state-of-the-art approaches provide limited support for literal data values, although they are crucial for many applications. In this paper, we propose EvoLearner - an evolutionary approach to learn ALCQ(D), which is the attributive language with complement (ALC) paired with qualified cardinality restrictions (Q) and data properties (D). We contribute a novel initialization method for the initial population: starting from positive examples (nodes in the knowledge graph), we perform biased random walks and translate them to description logic concepts. Moreover, we improve support for data properties by maximizing information gain when deciding where to split the data. We show that our approach significantly outperforms the state of the art on the benchmarking framework SML-Bench for structured machine learning. Our ablation study confirms that this is due to our novel initialization method and support for data properties.}}, author = {{Heindorf, Stefan and Blübaum, Lukas and Düsterhus, Nick and Werner, Till and Golani, Varun Nandkumar and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{WWW}}, pages = {{818--828}}, publisher = {{ACM}}, title = {{{EvoLearner: Learning Description Logics with Evolutionary Algorithms}}}, doi = {{10.1145/3485447.3511925}}, year = {{2022}}, } @article{29851, author = {{Pestryakova, Svetlana and Vollmers, Daniel and Sherif, Mohamed and Heindorf, Stefan and Saleem, Muhammad and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}}, journal = {{Scientific Data}}, title = {{{CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications}}}, doi = {{10.1038/s41597-022-01298-2}}, year = {{2022}}, } @inproceedings{34674, abstract = {{Smart home systems contain plenty of features that enhance wellbeing in everyday life through artificial intelligence (AI). However, many users feel insecure because they do not understand the AI’s functionality and do not feel they are in control of it. Combining technical, psychological and philosophical views on AI, we rethink smart homes as interactive systems where users can partake in an intelligent agent’s learning. Parallel to the goals of explainable AI (XAI), we explored the possibility of user involvement in supervised learning of the smart home to have a first approach to improve acceptance, support subjective understanding and increase perceived control. In this work, we conducted two studies: In an online pre-study, we asked participants about their attitude towards teaching AI via a questionnaire. In the main study, we performed a Wizard of Oz laboratory experiment with human participants, where participants spent time in a prototypical smart home and taught activity recognition to the intelligent agent through supervised learning based on the user’s behaviour. We found that involvement in the AI’s learning phase enhanced the users’ feeling of control, perceived understanding and perceived usefulness of AI in general. The participants reported positive attitudes towards training a smart home AI and found the process understandable and controllable. We suggest that involving the user in the learning phase could lead to better personalisation and increased understanding and control by users of intelligent agents for smart home automation.}}, author = {{Sieger, Leonie Nora and Hermann, Julia and Schomäcker, Astrid and Heindorf, Stefan and Meske, Christian and Hey, Celine-Chiara and Doğangün, Ayşegül}}, booktitle = {{International Conference on Human-Agent Interaction}}, keywords = {{human-agent interaction, smart homes, supervised learning, participation}}, location = {{Christchurch, New Zealand}}, publisher = {{ACM}}, title = {{{User Involvement in Training Smart Home Agents}}}, doi = {{10.1145/3527188.3561914}}, year = {{2022}}, } @inproceedings{52924, author = {{Tirtarasa, Satyadharma and Turhan, Anni-Yasmin}}, booktitle = {{SAC ’22: The 37th {ACM/SIGAPP} Symposium on Applied Computing, Virtual Event, April 25 - 29, 2022}}, editor = {{Hong, Jiman and Bures, Miroslav and Park, Juw Won and Cerný, Tomás}}, pages = {{903–910}}, publisher = {{ACM}}, title = {{{Computing generalizations of temporal ϵL concepts with next and global}}}, doi = {{10.1145/3477314.3507136}}, year = {{2022}}, } @article{52918, author = {{Baader, Franz and Koopmann, Patrick and Michel, Friedrich and Turhan, Anni-Yasmin and Zarrieß, Benjamin}}, journal = {{Theory Pract. Log. Program.}}, number = {{2}}, pages = {{162–192}}, title = {{{Efficient TBox Reasoning with Value Restrictions using the Flower Reasoner}}}, doi = {{10.1017/S1471068421000466}}, volume = {{22}}, year = {{2022}}, } @inbook{54585, author = {{Manzoor, Ali and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{The Semantic Web – ISWC 2022}}, isbn = {{9783031194320}}, issn = {{0302-9743}}, publisher = {{Springer International Publishing}}, title = {{{REBench: Microbenchmarking Framework for Relation Extraction Systems}}}, doi = {{10.1007/978-3-031-19433-7_37}}, year = {{2022}}, } @inproceedings{47289, author = {{Huaman, Nicolas and Krause, Alexander and Wermke, Dominik and Klemmer, Jan H. and Stransky, Christian and Acar, Yasemin and Fahl, Sascha}}, booktitle = {{Eighteenth Symposium on Usable Privacy and Security, SOUPS 2022, Boston, MA, USA, August 7-9, 2022}}, editor = {{Chiasson, Sonia and Kapadia, Apu}}, pages = {{313–330}}, publisher = {{USENIX Association}}, title = {{{If You Can’t Get Them to the Lab: Evaluating a Virtual Study Environment with Security Information Workers}}}, year = {{2022}}, } @inproceedings{47844, author = {{Jancar, Jan and Fourné, Marcel and Braga, Daniel De Almeida and Sabt, Mohamed and Schwabe, Peter and Barthe, Gilles and Fouque, Pierre-Alain and Acar, Yasemin}}, booktitle = {{2022 IEEE Symposium on Security and Privacy (SP)}}, publisher = {{IEEE}}, title = {{{“They’re not that hard to mitigate”: What Cryptographic Library Developers Think About Timing Attacks}}}, doi = {{10.1109/sp46214.2022.9833713}}, year = {{2022}}, } @inproceedings{47286, author = {{Gutfleisch, Marco and Klemmer, Jan H. and Busch, Niklas and Acar, Yasemin and Sasse, M. Angela and Fahl, Sascha}}, booktitle = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}}, pages = {{893–910}}, publisher = {{IEEE}}, title = {{{How Does Usable Security (Not) End Up in Software Products? Results From a Qualitative Interview Study}}}, doi = {{10.1109/SP46214.2022.9833756}}, year = {{2022}}, } @inproceedings{47287, author = {{Stransky, Christian and Wiese, Oliver and Roth, Volker and Acar, Yasemin and Fahl, Sascha}}, booktitle = {{43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022}}, pages = {{860–875}}, publisher = {{IEEE}}, title = {{{27 Years and 81 Million Opportunities Later: Investigating the Use of Email Encryption for an Entire University}}}, doi = {{10.1109/SP46214.2022.9833755}}, year = {{2022}}, } @inproceedings{47283, author = {{Kaur, Harjot and Amft, Sabrina and Votipka, Daniel and Acar, Yasemin and Fahl, Sascha}}, booktitle = {{31st USENIX Security Symposium, USENIX Security 2022, Boston, MA, USA, August 10-12, 2022}}, editor = {{Butler, Kevin R. B. and Thomas, Kurt}}, pages = {{4041–4058}}, publisher = {{USENIX Association}}, title = {{{Where to Recruit for Security Development Studies: Comparing Six Software Developer Samples}}}, year = {{2022}}, } @article{47290, author = {{Huaman, Nicolas and Amft, Sabrina and Oltrogge, Marten and Acar, Yasemin and Fahl, Sascha}}, journal = {{IEEE Secur. Priv.}}, number = {{2}}, pages = {{49–60}}, title = {{{They Would Do Better If They Worked Together: Interaction Problems Between Password Managers and the Web}}}, doi = {{10.1109/MSEC.2021.3123795}}, volume = {{20}}, year = {{2022}}, }