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Institut für Visualisierung und Interaktive Systeme
Team
Becker, Franziska

Franziska Becker

Frau M. Sc.

Wiss. Mitarbeiterin (VIS)
Institut für Visualisierung und Interaktive Systeme (VIS)
Abteilung Grafisch-Interaktive Systeme

Kontakt

+49 711 685 88429
E-Mail

Universitätsstraße 38
70569 Stuttgart
Deutschland
Raum: 1.464

Sprechstunde

Bei Bedarf gerne immer per Mail anschreiben.

Fachgebiet

Visual Analytics, Information Visualization
Externalization and Annotations
Sensemaking and Decision Making
Analytical Provenance and Interaction Logs

Publikationen

Publikationen:

2024
1. F. Becker and T. Blascheck, “TimeSeriesMaker: Interactive Time Series Composition in No Time,” in 2024 IEEE 17th Pacific Visualization Symposium (PacificVis), IEEE Computer Society, 2024. doi: 10.1109/PacificVis60374.2024.00042.
  - BibTeX
  BibTeX
  @inproceedings{becker2024timeseriesmaker, abstract = {TimeSeriesMaker is an open-source application to visually compose time series data in an intuitive and shareable manner. Visualization researchers often use time series data in studies about perceptual or cognitive phenomena and many other contexts. However, finding or generating time series data that fits a given scenario is not always easy. Using a component-based architecture, TimeSeriesMaker allows analysts to compose time series data with complex patterns by combining different components, such as noise, a linear trend or a seasonal pattern. An interactive compositor tree of these components lets analysts explore their combinations using different operators. We support reproducibility and transparency by including functionalities that allow analysts to export and share their configuration, which others can use to reload and modify the same time series. In a qualitative online study with visualization researchers, we found that our approach enables them to create a time series based on an example image or their own requirements. However, system usability could be further improved when interacting with the compositor tree. TimeSeriesMaker can be found here: https://unistuttgart-visus.github.io/time-series-maker/.}, author = {Becker, Franziska and Blascheck, Tanja}, booktitle = {2024 IEEE 17th Pacific Visualization Symposium (PacificVis)}, doi = {10.1109/PacificVis60374.2024.00042}, language = {en}, publisher = {IEEE Computer Society}, title = {TimeSeriesMaker: Interactive Time Series Composition in No Time}, year = 2024 }
2. F. Becker, C. Müller, D. Karpuk, and T. Ertl, “AlertSets: Supporting Exploratory Analysis of Cybersecurity Alerts through Sets,” in 1st Japan Visualization Symposium (JapanVis 2024), 2024.
  - BibTeX
  BibTeX
  @conference{becker2024alertsets, abstract = {Security providers typically deal with large numbers of alerts based on heterogeneous data from many endpoint sensors. While the number of alerts is generally much smaller than the volume of raw data, most alerts are false positives that do not reflect genuinely malicious activity. All types of experts work on such alerts, be it to determine whether they are indeed false positives, to build machine learning models to support their analysis or to keep an eye on the current threat landscape. We conducted a design study to support a diverse group of experts whose working environments are connected to the same alert data. Based on an ongoing industry project that clusters vectorized alerts, we designed and evaluated a visual analytics system enabling exploration via powerful, easy-to-understand filtering mechanisms framed through set operations. In this article, we describe our system, give a detailed breakdown of the design process and the lessons we learned. Lastly, we discuss the results from expert interviews, which showed the set-based framing to align with experts’ intuitive approach to data analysis and helped users uncover improvement opportunities for the clustering pipeline.}, author = {Becker, Franziska and Müller, Christoph and Karpuk, David and Ertl, Thomas}, booktitle = {1st Japan Visualization Symposium (JapanVis 2024)}, language = {en}, title = {AlertSets: Supporting Exploratory Analysis of Cybersecurity Alerts through Sets}, year = 2024 }
3. R. Warnking, J. Scheer, F. Becker, F. Siegel, F. Trinkmann, and T. Nagel, “Designing interactive visualizations for analyzing chronic lung diseases in a user-centered approach,” Journal of the American Medical Informatics Association, 2024, doi: 10.1093/jamia/ocae113.
  - BibTeX
  - Link
  BibTeX
  @article{warnking2024designing, author = {Warnking, René and Scheer, Jan and Becker, Franziska and Siegel, Fabian and Trinkmann, Frederik and Nagel, Till}, doi = {10.1093/jamia/ocae113}, journal = {Journal of the American Medical Informatics Association}, title = {Designing interactive visualizations for analyzing chronic lung diseases in a user-centered approach}, url = {https://doi.org/10.1093/jamia/ocae113}, year = 2024 }
  Link
  https://doi.org/10.1093/jamia/ocae113
2023
1. F. Becker and T. Ertl, “Putting Annotations to the Test,” in EuroVis 2023 - Posters, C. Gillmann, M. Krone, and S. Lenti, Eds., The Eurographics Association, 2023. doi: 10.2312/EVP.20231068.
  - BibTeX
  - Link
  BibTeX
  @inproceedings{https://doi.org/10.2312/evp.20231068, author = {Becker, Franziska and Ertl, Thomas}, booktitle = {EuroVis 2023 - Posters}, copyright = {Creative Commons Attribution 4.0 International}, doi = {10.2312/EVP.20231068}, editor = {Gillmann, Christina and Krone, Michael and Lenti, Simone}, isbn = {978-3-03868-220-2}, language = {en}, publisher = {The Eurographics Association}, title = {Putting Annotations to the Test}, url = {https://diglib.eg.org/handle/10.2312/evp20231068}, year = 2023 }
  Link
  https://diglib.eg.org/handle/10.2312/evp20231068
2022
1. T. Tremel et al., “VITALflow : Visual Interactive Traffic Analysis with NetFlow,” in NOMS 2022 : 2022 IEEE/IFIP Network Operations and Management Symposium, IEEE, 2022. doi: 10.1109/NOMS54207.2022.9789776.
  - BibTeX
  BibTeX
  @inproceedings{tremel2022vitalflow, address = {Piscataway}, affiliation = {Tremel, T (Corresponding Author), IsarNet Software Solut GmbH, Munich, Germany. Tremel, Tina; Koegel, Jochen; Jauernig, Florian; Meier, Sebastian, IsarNet Software Solut GmbH, Munich, Germany. Thom, Dennis; Becker, Franziska; Mueller, Christoph; Koch, Steffen, Univ Stuttgart, Stuttgart, Germany.}, author = {Tremel, Tina and Kögel, Jochen and Jauernig, Florian and Meier, Sebastian and Thom, Dennis and Becker, Franziska and Müller, Christoph and Koch, Steffen}, booktitle = {NOMS 2022 : 2022 IEEE/IFIP Network Operations and Management Symposium}, doi = {10.1109/NOMS54207.2022.9789776}, eventdate = {2022-04-25/2022-04-29}, eventtitle = {NOMS 2022 : 2022 IEEE/IFIP Network Operations and Management Symposium}, isbn = {978-1-6654-0601-7}, language = {eng}, publisher = {IEEE}, title = {VITALflow : Visual Interactive Traffic Analysis with NetFlow}, unique-id = {WOS:000851572700032}, venue = {Budapest, Hungary}, year = 2022 }
2021
1. R.-C. Rapp, C. Müller, F. Becker, P. Palumbo, and T. Ertl, “Interactive Process Tree Analysis: Exploring the Behaviour of Processes with Visual Analytics for Security Operators,” in IEEE Symposium on Visualization for Cyber Security (VizSec), IEEE, 2021.
  - BibTeX
  BibTeX
  @conference{rapp2021interactive, abstract = {Despite constant efforts to improve automation for IT security incidents, analysts are often confronted with numerous alerts and have to make sure that they do not miss the most critical of them. The analysts need to quickly decide based on a plethora of yet incomplete information. This information often includes a tree of parent and child processes in real-world scenarios. We present an augmented visualisation of such a process tree, which not only shows the static hierarchy as previous ones do, but also conveys the temporal relation between processes, thus allowing for investigating the hierarchy and time perspective of the process tree at the same time. Furthermore, it makes additional process-related events collected by endpoint sensors accessible for a more complete view on process behaviour.}, author = {Rapp, Robert-Carl and Müller, Christoph and Becker, Franziska and Palumbo, Paolo and Ertl, Thomas}, booktitle = {IEEE Symposium on Visualization for Cyber Security (VizSec)}, language = {en}, publisher = {IEEE}, title = {Interactive Process Tree Analysis: Exploring the Behaviour of Processes with Visual Analytics for Security Operators}, year = 2021 }
2020
1. F. Becker, A. Drichel, C. Müller, and T. Ertl, “Interpretable Visualizations of Deep Neural Networks for Domain Generation Algorithm Detection,” in 2020 IEEE Symposium on Visualization for Cyber Security (VizSec), IEEE, Oct. 2020, pp. 25–29. doi: 10.1109/VizSec51108.2020.00010.
  - BibTeX
  - Link
  BibTeX
  @inproceedings{9347410, abstract = {Due to their success in many application areas, deep learning models have found wide adoption for many problems. However, their black-box nature makes it hard to trust their decisions and to evaluate their line of reasoning. In the field of cybersecurity, this lack of trust and understanding poses a significant challenge for the utilization of deep learning models. Thus, we present a visual analytics system that provides designers of deep learning models for the classification of domain generation algorithms with understandable interpretations of their model. We cluster the activations of the model's nodes and leverage decision trees to explain these clusters. In combination with a 2D projection, the user can explore how the model views the data at different layers. In a preliminary evaluation of our system, we show how it can be employed to better understand misclassifications, identify potential biases and reason about the role different layers in a model may play.}, author = {Becker, Franziska and Drichel, Arthur and Müller, Christoph and Ertl, Thomas}, booktitle = {2020 IEEE Symposium on Visualization for Cyber Security (VizSec)}, doi = {10.1109/VizSec51108.2020.00010}, issn = {2639-4332}, language = {en}, month = {10}, pages = {25-29}, publisher = {IEEE}, title = {Interpretable Visualizations of Deep Neural Networks for Domain Generation Algorithm Detection}, url = {https://ieeexplore.ieee.org/document/9347410}, year = 2020 }
  Link
  https://ieeexplore.ieee.org/document/9347410

Lehre

Universität Stuttgart
- Practical Course Visual Computing
- Practical Course Information Visualization
- Visualization and Machine Learning Seminar
- Introduction to Information Visualization and Visual Analytics
Universität Osnabrück
- Algorithmen und Datenstrukturen (2x)
- Einführung in die Software-Entwicklung
- Computergrafik Praktikum (2x)
- Geometry Processing

Lebenslauf

2020-jetzt Universität Stuttgart, Institut für Visualisierung und Interaktive Systeme
2017-2020 Universität Osnabrück, M. Sc. Informatik
2014-2015 Universität Helsinki, Auslandssemester (Psychologie)
2012-2017 Universität Osnabrück, B. Sc. Cognitive Science

Franziska Becker

Kontakt

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Publikationen

2024

BibTeX

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Link

2023

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2022

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2021

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2020

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Franziska Becker

Kontakt

Sprechstunde

Fachgebiet

Publikationen

2024

BibTeX

BibTeX

BibTeX

Link

2023

BibTeX

Link

2022

BibTeX

2021

BibTeX

2020

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Link

Lehre

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