FH-Prof. Dr. Pascal Schöttle

2022 - heute
Professor (FH) - Management Center Innsbruck, Österreich

2020 - 2022
Assoziierter Professor (FH) - Management Center Innsbruck, Österreich

2018 - 2020
Hochschullektor - Management Center Innsbruck, Österreich

2015 - 2018
Post-Doc - Universität Innsbruck, Österreich

2014 - 2015
Post-Doc - Westfälische Wilhelms-Universität Münster, Deutschland

2013
Austauschforscher - Pennsylvania State University, USA

2011 - 2014
Wissenschaftlicher Mitarbeiter (Doktorand) - Westfälische Wilhelms-Universität Münster, Deutschland

2010 - 2011
Wissenschaftliche Hilfskraft - Ruhr-Universität Bochum, Deutschland

2011 - 2014
Informatik - Westfälische Wilhelms-Universität Münster, Deutschland (Dr. rer. nat)

2008 - 2011
IT-Sicherheit / Netze und Systeme - Ruhr-Universität Bochum, Deutschland (Master of Science)

2003 - 2008
Mathematical Engineering - Universität Duisburg-Essen, Deutschland (Bachelor of Science)

Blended Learning 1-2-3 - MCI - Die Unternehmerische Hochschule

Sakai Advanced - MCI - Die Unternehmerische Hochschule

Adobe Connect Advanced - MCI - Die Unternehmerische Hochschule

Sakai Basic - MCI - Die Unternehmerische Hochschule

Adobe Connect Basics - MCI - Die Unternehmerische Hochschule

Multimedia-Sicherheit - Westfälische Wilhelms-Universität Münster, Deutschland

Advanced Cryptology - Westfälische Wilhelms-Universität Münster, Deutschland

Einführung in die Technische Informatik - Universität Innsbruck, Österreich

Rechnernetze und Internettechnik - Universität Innsbruck, Österreich

Information Security II - Universität Innsbruck, Österreich

Kommunikationstechnik und Rechnernetzwerke - Universität Innsbruck, Österreich

Logik & Berechenbarkeit - Management Center Innsbruck, Österreich

Mathematik & Statistik - Management Center Innsbruck, Österreich

Algorithmen & Datenstrukturen - Management Center Innsbruck, Österreich

Management Information Systems - Management Center Innsbruck, Österreich

Data Science - Management Center Innsbruck, Österreich

Security for Smart Technologies - MCI - Die Unternehmerische Hochschule, Österreich

Smart Systems & Machine Learning - MCI - Die Unternehmerische Hochschule, Österreich

IT Security - MCI - Die Unternehmerische Hochschule, Österreich

Integratives Gesamtprojekt - MCI - Die Unternehmerische Hochschule, Österreich

2012
IEEE International Workshop on Information Forensics and Security
Best Student Paper Award

2008
CAST - Competence Center for Applied Security Technology
2. Platz beim CAST Förderpreis IT-Sicherheit

• Merkle, F., Samsinger, M., Schöttle, P., & Pevny, T. (2024). On the Economics of Adversarial Machine Learning. IEEE Transactions on Information Forensics and Security, 1-1. https://doi.org/10.1109/TIFS.2024.3379829
• Brinkschulte, L., Schlögl, S., Monz, A., Schöttle, P., & Janetschek, M. (2022). Perspectives on Socially Intelligent Conversational Agents. Multimodal Technologies and Interaction, 6(8). https://doi.org/10.3390/mti6080062
• Baumhauer, T., Schöttle, P., & Zeppelzauer, M. (2022). Machine unlearning: linear filtration for logit-based classifiers. Machine Learning. https://doi.org/10.1007/s10994-022-06178-9
• Thalhammer, F., Schöttle, P., Janetschek, M., & Ploder, C. (2022). Blockchain Use Cases Against Climate Destruction. Cloud Computing and Data Science, 3(2), 22-38. https://doi.org/10.37256/ccds.3220221277
• Pascal Schöttle and Rainer Böhme. "Game Theory and Adaptive Steganography". In: IEEE Transactions on Information Forensics and Security 11.4 (2016), pp. 760-773
• Benjamin Johnson, Pascal Schöttle, Aron Laszka, Jens Grossklags, and Rainer Böhme. "Adaptive Steganography and Steganalysis with Fixed-Size Embedding". In: Transactions on Data Hiding and Multimedia Security 10 (2015), pp. 69-91
• Aron Laszka, Benjamin Johnson, Pascal Schöttle, Jens Grossklags, and Rainer Böhme. "Secure Team Composition to Thwart Insider Threats and Cyberespionage". In: ACM Transactions on Internet Technology 14.2-3 (2014), 19:1-22

• Pascal Schöttle and Rainer Böhme. "Die totale Transparenz. Facebook, Cookies, RFID etc." In: Ethische Herausforderungen im Web 2.0. Ed. by Martin Dabrowski, Judith Wolf, and Karlies Abmeier. Paderborn: Schöningh, 2014, pp. 11-31

• Russold, M., Nocker, M., & Schöttle, P. (2024). Incremental Whole Plate ALPR Under Data Availability Constraints. Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM, 131-140. https://doi.org/10.5220/0012566400003654
• Merkle, F., Sirbu, M. R., Nocker, M., & Schöttle, P. (2024). Generating Invariance-Based Adversarial Examples: Bringing Humans Back into the Loop. In G. L. Foresti, A. Fusiello, & E. Hancock (Hrsg.), Image Analysis and Processing—ICIAP 2023 Workshops (S. 15-27). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-51023-6_2
• Martin, Nocker, David, Drexel, Michael Rader, Alessio Montuoro, and Pascal Schöttle. "HE-MAN - Homomorphically Encrypted MAchine learning with oNnx models", In The 8th International Conference on Machine Learning Technologies (ICMLT), 2023. https://doi.org/10.1145/3589883.3589889
• Roland Rauter, Martin Nocker, Florian Merkle, and Pascal Schöttle. "On the Effect of Adversarial Training Against Invariance-based Adversarial Examples", In The 8th International Conference on Machine Learning Technologies (ICMLT), 2023. https://doi.org/10.1145/3589883.3589891
• Widmann, T., Merkle, F., Nocker, M., & Schöttle, P. (2023). Pruning for Power: Optimizing Energy Efficiency in IoT with Neural Network Pruning. In L. Iliadis, I. Maglogiannis, S. Alonso, C. Jayne, & E. Pimenidis (Hrsg.), Engineering Applications of Neural Networks (S. 251-263). Springer Nature Switzerland. doi: 10.1007/978-3-031-34204-2_22
• Florian Merkle, Maximilian Samsinger, and Pascal Schöttle. "Pruning in the Face of Adversaries", In The 21st International Conference on Image Analysis and Processing (ICIAP), 2022
• Daniel Aumayr and Pascal Schöttle. "U Can't (re)Touch This - A Deep Learning Approach for Detecting Image Retouching", In The 21st International Conference on Image Analysis and Processing (ICIAP), 2022
• Maximilian Samsinger, Florian Merkle, Pascal Schöttle, and Tomas Pevny. "When Should You Defend Your Classifier? - A Game-theoretical Analysis of Countermeasures against Adversarial Examples", In The 12th Conference on Decision and Game Theory for Security (GameSec), 2021
• Nora Hofer, Pascal Schöttle, Alexander Riezler, and Sebastian Stabinger. "Adversarial Examples Against a BERT ABSA Model -Fooling Bert With L33T, Misspellign, and Punctuation," In International Conference on Availability, Reliability and Security (ARES), 2021
• Dilger, T., Ploder, C., Haas, W., Schöttle, P., & Bernsteiner, R. (2020). Continuous Planning and Forecasting Framework(CPFF) for Agile Project Management: Overcoming the "Agilefall"-BudgetingTrap. 21st Annual Conference on Information Technology Education (SIGITE '20), October 7-9, 2020, Virtual Event, USA.ACM, Omaha, NB, USA, https://doi.org/10.1145/3368308.3415398
• Christian Ploder, Thomas Dilger, and Schöttle Pascal. "Agile Project Budgeting - Teaching the Combination of Agile Project Management and Beyond Budgeting Basics". In: Proceedings of the 12th International Conference on Education and New Learning Technologies (EDULEARN). 2020
• Thomas Baumhauer, Pascal Schöttle, and Matthias Zeppelzauer. "Machine Unlearning: Linear Filtration for Logit-based Classifiers". In: https://arxiv.org/abs/2002.02730
• Pascal Schöttle, Alexander Schlögl, Cecilia Pasquini, and Rainer Böhme. "Detecting Adversarial Examples - A Lesson from Multimedia Security" In: 26th European Signal Processing Conference (EUSIPCO), 2018.
• Cecilia Pasquini, Pascal Schöttle, and Rainer Böhme. "Decoy Password Vaults: At Least As Hard As Steganography?" In: Proceedings of 32nd International Conference on ICT Systems Security and Privacy Protection (IFIP SEC). 2017, pp. 327-340
• Svetlana Abramova, Pascal Schöttle, and Rainer Böhme. "Mixing Coins of Different Quality: A Game-Theoretic Approach". In: 4th Workshop on Bitcoin and Blockchain Research, in assocation with Financial Cryptography and Data Security 2017. Malta, 2017
• Cecilia Pasquini, Pascal Schöttle, Rainer Böhme, Giulia Boato, and Fernando Pèrez- Gonzàlez. "Forensics of High Quality and Nearly Identical JPEG Image Recompression". In: ACM Information Hiding and Multimedia Security Workshop. Vigo, Galicia, Spain, 2016, pp. 11-21
• Matthias Carnein, Pascal Schöttle, and Rainer Böhme. "Telltale Watermarks for Counting JPEG Compressions". In: Proceedings of IS&T Electronic Imaging: Media Watermarking, Security, and Forensics 2016. San Francisco, CA, 2016
• Matthias Carnein, Pascal Schöttle, and Rainer Böhme. "Forensics of High-Quality JPEG Images with Color Subsampling". In: IEEE International Workshop on Information Forensics and Security (IEEE WIFS). Rome, Italy, 2015
• Matthias Kirchner, Pascal Schöttle, and Christian Riess. "Thinking beyond the block: block matching for copy-move forgery detection revisited." Media Watermarking, Security, and Forensics 2015. Vol. 9409. International Society for Optics and Photonics, 2015.
• Matthias Carnein, Pascal Schöttle, and Rainer Böhme. "Predictable Rain? Steganalysis of Public-Key Steganography using Wet Paper Codes". In: ACM Information Hiding and Multimedia Security Workshop. Salzburg, Austria, 2014, pp. 97-108
• Erwin Quiring and Pascal Schöttle. "On the Combination of Randomized Thresholds and Non-Parametric Boundaries to Protect Digital Watermarks against Sensitivity Attacks". In: ACM Information Hiding and Multimedia Security Workshop. Salzburg, Austria, 2014, pp. 41-48
• Aron Laszka, Benjamin Johnson, Pascal Schöttle, and Rainer Böhme. "Managing the Weakest Link: A Game-Theoretic Approach for the Mitigation of Insider Threats". In: Computer Security (ESORICS). Ed. by Jason Crampton, Sushil Jajodia, and Keith Mayes. Vol. 8134. Lecture Notes in Computer Science. Berlin Heidelberg: Springer, 2013, pp. 273- 290
• Pascal Schöttle, Aron Laszka, Benjamin Johnson, Jens Grossklags, and Rainer Böhme. "A Game-Theoretic Analysis of Content-adaptive Steganography with Independent Embed- ding". In: 21st European Signal Processing Conference (EUSIPCO). Marrakech, Morocco: IEEE, 2013, pp. 1-5
• Pascal Schöttle, Stefan Korff, and Rainer Böhme. "Weighted Stego-Image Steganalysis for Naive Content-Adaptive Embedding". In: IEEE International Workshop on Information Forensics and Security (IEEE WIFS). Best paper award. Tenerife, Spain, 2012, pp. 193- 198
• Pascal Schöttle and Rainer Böhme. "A Game-Theoretic Approach to Content-Adaptive Steganography". In: Information Hiding (14th International Conference). Ed. by Matthias Kirchner and Dipak Ghosal. Vol. 7692. Lecture Notes in Computer Science. Berlin Heidel- berg: Springer, 2012, pp. 125-141
• Benjamin Johnson, Pascal Schöttle, and Rainer Böhme. "Where to Hide the Bits?" In: Decision and Game Theory for Security. Ed. by Jens Grossklags and Jean Walrand. Vol. 7638. Lecture Notes in Computer Science. Berlin Heidelberg: Springer, 2012, pp. 1-17

Schöttle, P. (2024, February 24). Incremental Whole Plate ALPR Under Data Availability Constraints [Conference presentation]. ICPRAM, Rome (online), Italy.

Schöttle., P. (2023, October 10). Einblicke in KI Initiativen und Projekte bei INNIO [Invited talk]. Industriellen Vereinigung Tirol - KI in der Tiroler Industrie, Innsbruck, Austria.

2021 - 2023
Projektleiter (@ MCI) - SMiLE - Secure Machine Learning Applications with Homomorphically Encrypted Data - FFG - Die Österreichische Forschungsförderungsgesellschaft

2019 - 2023
Projektleiter - Game Over Eva(sion): Sicheres Deep Learning mit Spieltheorie Keywords: Deep Learning, Security, Game Theory, Evasion Attacks - FWF - Der Wissenschaftsfonds

2017 - 2019
Projektleitung - "Forensic Analysis of Scanned Text Documents" (FASTDoc). - Forschungsförderungsmittel der Nachwuchsförderung 2017 (Universität Innsbruck)

2015
FFG Relocation Förderung -

2013
ONR Visiting Researcher Förderung -

2018
Programm Committee Co-Chair - ACM Information Hiding & Multimedia Security 2018

2018
Programmkomitteemitglied - IEEE International Conference on Acoustics, Speech, and Signal Processing

2015 - 2020
Programmkomitteemitglied - ACM Information Hiding & Multimedia Security

2015 - 2018
Programmkomitteemitglied - International Workshop on Digital-forensics and Watermarking

Gerges Youssef (2023): Web Application Security Education

Schweitzer Stefan (2023): Container Orchestrierungen: Eine qualitative Erhebung zu aktuellen Sicherheitsmaßnahmen und Best Practices

Stöbich Roman (2023): Machine Learning als Methode zur Anomaliedetektion in drahtlosen Lichtsteuersystemen

Payr Patrik (2023): Cyber-Sicherheit für Smartphones: Angriffsvektoren und Container-Anwendungen im Android Betriebssystem als Schutzmaßnahme

Russold Markus (2023): On The Usage Of Deep Learning To Improve License Plate Recognition Quality In Post-Processing Based On A Continual Learning Approach

Gangl Katharina (2023): Ultimateberechnung von Hagelschäden in Österreich mithilfe von Machine Learning

Suntinger Fabian (2023): Abschätzung der Arbeitszeit für zusätzliche Ingenieurleistungen für Balance-of-Plant-/Anlagenbau- und Sonderaufträge bei INNIO Jenbacher

Rauter Roland (2022): Trainieren eines CNN mithilfe von Invariance-Based Adversarial Examples

Stockinger Rene (2022): Universal Adversarial Perturbations als Angriff gegen Gesichtserkennung

Mösl Michael (2022): On-Device Modell Optimierung von Machine-Learning Algorithmen auf mobilen Geräten

Hüttl Mathis (2022): Welche Anforderungen hat eine Software zur Bekämpfung von Fake News im Internet und wie kann diese umgesetzt werden?

Köll Julian (2022): Cybersecurity in Computerspielen - Sicherheitsaspekte von Offline- und Online-Games

Griesser Daniel (2022): State-of-the-art Algorithmen zur Generierung von Adversarial Examples - ein Vergleich

Gugler Anton (2022): Material demand forecasting : Ein Vergleich statistischer, Machine Learning und Deep Learning Methoden.

Temizkan Abdulkadir (2022): Evaluierung von Social Engineering Methoden

Mirocha Tobias (2021): PKI-basierte E-Mail-Verschlüsselung und -Signatur

Eichhorn Philipp (2021): Few-Shot Learning am Beispiel automatisierter Rechnungsklassifikation

Thurner Maximilian (2021): Entwicklung eines Konzepts zur Steigerung der Passwortsicherheit und dessen Anwendung in einer Sicherheitsanalyse

Divković Marijan (2021): Making Machine Learning Accessible for SMEs: Framework Requirements and Clustering Prototype

Klingenschmid Lukas (2021): Detektion von Laser-Range Finder Messpulsen unter Verwendung von Machine Learning Algorithmen

Lerch Judith (2021): Machine Learning zur Vorhersage von Zeitaufwand im Kontext von INNIO Jenbacher

Aumayr Daniel (2021): Automatische Erkennung von Bildmanipulationen durch mobile Applikationen mit einem CNN

Moog Patrick (2022): Fooling Neural Networks for Age-/Gender- and Emotion-Prediction with Adversarial Patches

Sirbu Mihaela Roxana (2021): Humans vs. CNNs: susceptibility to invariance and sensitivity based adversarial examples

Weber David (2021): How much pruning is too much? The effects of neural network pruning on machine learning explainability

Hofer Nora (2020): On the Robustness of a BERT Model for ABSA against Input Level Adversarial Examples

Merkle Florian (2020): The Impact of Network Pruning on the Adversarial Robustness of Deep Neural Networks

Bleckmann Carl (2020): What‘s next for IoT Forensics? A Proposal for Integration of Multimedia Forensic Methods to IoT Forensic Concepts

Muhr Valentin (2019): Data Deletion in Deep Learning Networks