@article{PrasseKnaebelMachlicaetal.2019, author = {Prasse, Paul and Knaebel, Rene and Machlica, Lukas and Pevny, Tomas and Scheffer, Tobias}, title = {Joint detection of malicious domains and infected clients}, series = {Machine learning}, volume = {108}, journal = {Machine learning}, number = {8-9}, publisher = {Springer}, address = {Dordrecht}, issn = {0885-6125}, doi = {10.1007/s10994-019-05789-z}, pages = {1353 -- 1368}, year = {2019}, abstract = {Detection of malware-infected computers and detection of malicious web domains based on their encrypted HTTPS traffic are challenging problems, because only addresses, timestamps, and data volumes are observable. The detection problems are coupled, because infected clients tend to interact with malicious domains. Traffic data can be collected at a large scale, and antivirus tools can be used to identify infected clients in retrospect. Domains, by contrast, have to be labeled individually after forensic analysis. We explore transfer learning based on sluice networks; this allows the detection models to bootstrap each other. In a large-scale experimental study, we find that the model outperforms known reference models and detects previously unknown malware, previously unknown malware families, and previously unknown malicious domains.}, language = {en} } @phdthesis{Ashouri2020, author = {Ashouri, Mohammadreza}, title = {TrainTrap}, school = {Universit{\"a}t Potsdam}, pages = {XIX, 103}, year = {2020}, language = {en} } @article{LaskovGehlKruegeretal.2006, author = {Laskov, Pavel and Gehl, Christian and Kr{\"u}ger, Stefan and M{\"u}ller, Klaus-Robert}, title = {Incremental support vector learning: analysis, implementation and applications}, series = {Journal of machine learning research}, volume = {7}, journal = {Journal of machine learning research}, publisher = {MIT Press}, address = {Cambridge, Mass.}, issn = {1532-4435}, pages = {1909 -- 1936}, year = {2006}, abstract = {Incremental Support Vector Machines (SVM) are instrumental in practical applications of online learning. This work focuses on the design and analysis of efficient incremental SVM learning, with the aim of providing a fast, numerically stable and robust implementation. A detailed analysis of convergence and of algorithmic complexity of incremental SVM learning is carried out. Based on this analysis, a new design of storage and numerical operations is proposed, which speeds up the training of an incremental SVM by a factor of 5 to 20. The performance of the new algorithm is demonstrated in two scenarios: learning with limited resources and active learning. Various applications of the algorithm, such as in drug discovery, online monitoring of industrial devices and and surveillance of network traffic, can be foreseen.}, language = {en} } @article{SteuerHumburgSelbig2006, author = {Steuer, Ralf and Humburg, Peter and Selbig, Joachim}, title = {Validation and functional annotation of expression-based clusters based on gene ontology}, series = {BMC bioinformatics}, volume = {7}, journal = {BMC bioinformatics}, number = {380}, publisher = {BioMed Central}, address = {London}, issn = {1471-2105}, doi = {10.1186/1471-2105-7-380}, pages = {12}, year = {2006}, abstract = {Background: The biological interpretation of large-scale gene expression data is one of the paramount challenges in current bioinformatics. In particular, placing the results in the context of other available functional genomics data, such as existing bio-ontologies, has already provided substantial improvement for detecting and categorizing genes of interest. One common approach is to look for functional annotations that are significantly enriched within a group or cluster of genes, as compared to a reference group. Results: In this work, we suggest the information-theoretic concept of mutual information to investigate the relationship between groups of genes, as given by data-driven clustering, and their respective functional categories. Drawing upon related approaches (Gibbons and Roth, Genome Research 12: 1574-1581, 2002), we seek to quantify to what extent individual attributes are sufficient to characterize a given group or cluster of genes. Conclusion: We show that the mutual information provides a systematic framework to assess the relationship between groups or clusters of genes and their functional annotations in a quantitative way. Within this framework, the mutual information allows us to address and incorporate several important issues, such as the interdependence of functional annotations and combinatorial combinations of attributes. It thus supplements and extends the conventional search for overrepresented attributes within a group or cluster of genes. In particular taking combinations of attributes into account, the mutual information opens the way to uncover specific functional descriptions of a group of genes or clustering result. All datasets and functional annotations used in this study are publicly available. All scripts used in the analysis are provided as additional files.}, language = {en} } @incollection{KiyHaferSchumannetal.2016, author = {Kiy, Alexander and Hafer, J{\"o}rg and Schumann, Marlen and Enke, Uta}, title = {Digitale Teilnehmerzertifikate und Open Badges verbinden}, series = {DeLFI 2016 - Die 14. E-Learning Fachtagung Informatik 11.-14. September 2016 Potsdam}, booktitle = {DeLFI 2016 - Die 14. E-Learning Fachtagung Informatik 11.-14. September 2016 Potsdam}, number = {P-262}, editor = {Lucke, Ulrike and Schwill, Andreas and Zender, Raphael}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, isbn = {978-3-88579-656-5}, publisher = {Universit{\"a}t Potsdam}, pages = {285 -- 287}, year = {2016}, abstract = {W{\"a}hrend Qualifikationen und Kompetenzen, die auf informellem Wege erworben werden, immer mehr Beachtung finden, stellt sowohl deren Darstellung als auch die Anerkennung ein meist un{\"u}berwindbares Hindernis f{\"u}r Ausstellende und Erwerbende dar. Vermehrt wird unterdessen von klassisch papiergebundenen auf digitale Teilnahmezertifikate umgestellt, um den Nachweis von Kompetenz- und Qualifikationserwerb zu vereinfachen. In diesem Zusammenhang kann die Verbindung von digitalen Teilnahmezertifikaten und Open Badges einen Mehrwert f{\"u}r die {\"o}ffentliche Darstellung und Verifikation bieten.}, language = {de} } @article{LinkeTompitsWoltran2004, author = {Linke, Thomas and Tompits, Hans and Woltran, Stefan}, title = {On Acyclic and head-cycle free nested logic programs}, isbn = {3-540-22671-01}, year = {2004}, language = {en} } @article{LinkeTompitsWoltran2004, author = {Linke, Thomas and Tompits, Hans and Woltran, Stefan}, title = {On acyclic and head-cycle free nested logic programs}, year = {2004}, language = {en} } @incollection{HaferKostaedtLucke2021, author = {Hafer, J{\"o}rg and Kost{\"a}dt, Peter and Lucke, Ulrike}, title = {Das Corona-Virus als Treiber der Digitalisierung}, series = {Das Corona-Virus als Treiber der Digitalisierung}, booktitle = {Das Corona-Virus als Treiber der Digitalisierung}, publisher = {Springer}, address = {Wiesbaden}, isbn = {978-3-658-32608-1}, doi = {10.1007/978-3-658-32609-8_15}, pages = {219 -- 242}, year = {2021}, abstract = {Mit der Covid-19-Pandemie hat die Digitalisierung an Hochschulen weitere Bedeutung erlangt. Insbesondere dem Einsatz digitaler Medien in Lehre und Studium galt großes Augenmerk. Das legt die Hoffnung nahe, dass die Digitalisierung durch das Virus einen Schub erfahren und die Hochschulen dauerhaft ver{\"a}ndert hat. Der Beitrag geht am Beispiel der Universit{\"a}t Potsdam der Frage nach, welcher Natur diese Ver{\"a}nderungen waren - ausgehend sowohl von den unternommenen Maßnahmen als auch von den erzielten Resultaten - und inwiefern sie von Dauer sind. Dabei werden f{\"o}rderliche und hemmende Faktoren identifiziert, die in Empfehlungen f{\"u}r weitere Digitalisierungsvorhaben {\"u}bersetzt werden.}, language = {de} } @article{BordihnFernauHolzeretal.2006, author = {Bordihn, Henning and Fernau, Henning and Holzer, Markus and Manca, Vincenzo and Martin-Vide, Carlos}, title = {Iterated sequential transducers as language generating devices}, series = {Theoretical computer science}, volume = {369}, journal = {Theoretical computer science}, number = {1}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0304-3975}, doi = {10.1016/j.tcs.2006.07.059}, pages = {67 -- 81}, year = {2006}, abstract = {Iterated finite state sequential transducers are considered as language generating devices. The hierarchy induced by the size of the state alphabet is proved to collapse to the fourth level. The corresponding language families are related to the families of languages generated by Lindenmayer systems and Chomsky grammars. Finally, some results on deterministic and extended iterated finite state transducers are established.}, language = {en} } @article{StoffelKunzGerber1997, author = {Stoffel, Dominik and Kunz, Wolfgang and Gerber, Stefan}, title = {And/Or reasoning graphs for determining prime implicants in multi-level combinational networks}, year = {1997}, language = {en} }