Prof. Dr. Pascal Schöttle

Head of Josef Ressel Centre for Security Analysis of IoT DevicesIT Security & Machine Learning +43 512 2070 - 4332 pascal.schoettle@mci.edu

Pascal is a professor for IT Security and Machine Learning at the department Digital Business & Software Engineering at MCI - The Entrepreneurial School in Innsbruck.

Professional work experience

06/2022 - present
Professor - MCI - The Entrepreneurial School, Austria
10/2020 - 06/2022
Associate Professor - MCI - The Entrepreneurial School, Austria
10/2018 - 09/2020
Lecturer - MCI - The Entrepreneurial School, Austria
03/2015 - 09/2018
Post-Doc - University of Innsbruck, Austria
09/2014 - 02/2015
Post-Doc - University Münster, Deutschland
02/2013 - 04/2013
Visiting Scholar - Pennsylvania State University, USA
09/2011 - 08/2014
Scientific Staff Member (Doctoral Candidate) - University Münster, Germany
07/2010 - 06/2011
Scientific Student Assistent - Ruhr-University Bochum, Deutschland

Education

10/2011 - 07/2014
Ph. D. (Dr. rer. nat) - University Münster, Germany
Computer Science
04/2008 - 06/2011
Master of Science - Ruhr-University Bochum, Germany
IT Security / Networks and Systems
10/2003 - 02/2008
Bachelor of Science - University of Duisburg-Essen, Germany
Mathematical Engineering

Teaching (faculty internships etc.)

01/2020 - present
MCI - The Entrepreneurial School, Austria
Smart Systems & Machine Learning
01/2020 - present
MCI - The Entrepreneurial School, Austria
IT Security
01/2020 - 12/2022
MCI - The Entrepreneurial School, Austria
Integrated Overall Project
01/2019 - present
MCI - The Entrepreneurial School, Austria
Mathematics for Software Engineering
01/2019 - 12/2022
MCI - The Entrepreneurial School, Austria
Algorithms & Data Structures
01/2019 - present
MCI - The Entrepreneurial School, Austria
Management Information Systems
01/2019 - 12/2021
MCI - The Entrepreneurial School, Austria
Data Science
01/2019 - present
MCI - The Entrepreneurial School, Austria
Security for Smart Technologies
01/2018 - present
MCI - The Entrepreneurial School, Austria
Logic & Computability
01/2017 - 12/2018
University of Innsbruck, Austria
Communication Technology and Computer Networks
01/2016 - 12/2018
University of Innsbruck, Austria
Information Security II
01/2015 - 12/2018
University of Innsbruck, Austria
Introduction to Computer Engineering
01/2015 - 12/2018
University of Innsbruck, Austria
Computer Networks and Internet Technology
01/2012 - 12/2014
University Münster, Germany
Multimedia Security
01/2012 - 12/2014
University Münster, Germany
Advanced Cryptology

Practice related research and developmental project

07/2023 - present
Head of Research Center - CDG - Christian Doppler Forschungsgesellschaft
Josef Ressel Center for Security Analysis of IoT Devices
04/2021 - 12/2023
Principal Investigator (@ MCI) - FFG - The Austrian Research Promotion Agency
SMiLE - Secure Machine Learning Applications with Homomorphically Encrypted Data
01/2019 - 06/2023
Principal Investigator - FWF - Austrian Science Fund
Game Over Eva(sion): Securing Deep Learning with Game Theory Keywords: Deep Learning, Security, Game Theory, Evasion Attacks
01/2017 - 12/2019
Project Leader - Forschungsförderungsmittel der Nachwuchsförderung 2017 (University Innsbruck)
“Forensic Analysis of Scanned Text Documents" (FASTDoc).

Competitive Research Award

11/2012 - 11/2012
IEEE International Workshop on Information Forensics and Security
Best Student Paper Award
09/2008 - 09/2008
CAST - Competence Center for Applied Security Technology
2nd place at CAST Förderpreis in IT security,

Further education & Training

2019 - 2019
MCI - The Entrepreneurial School
Blended Learning 1-2-3
2018 - 2018
MCI - The Entrepreneurial School
Sakai Advanced
2018 - 2018
MCI - The Entrepreneurial School
Adobe Connect Advanced
2018 - 2018
MCI - The Entrepreneurial School
Sakai Basic
2018 - 2018
MCI - The Entrepreneurial School
Adobe Connect Basics

Other

03/2015 - 03/2015
FFG Relocation Grant, for the relocation from Germany to Austria.
03/2013 - 03/2013
ONR Visiting Researcher Grant, funding the research visit at the Pennsylvania State University, US.

Positions in professional/academic societies

01/2018 - 12/2018
Programm Committee Co-Chair - ACM Information Hiding & Multimedia Security 2018
01/2018 - 12/2018
Programm Committee Member - IEEEE International Conference on Acoustics, Speech, and Signal Processing
01/2015 - 12/2020
Program Committee Member - ACM Information Hiding & Multimedia Security
01/2015 - 12/2018
Programm Committee Member - International Workshop on Digital-forensics and Watermarking

Peer reviewed journal article

Merkle, F., Weber, D., Schöttle, P., Schlögl, S., & Nocker, M. (2025). Less is More: The Influence of Pruning on the Explainability of CNNs. IEEE Access, 13, 87909–87927. https://doi.org/10.1109/ACCESS.2025.3569575
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

Presentation of a paper at a conference, workshop or seminar

Schöttle, P. (2025, August 16). CyberSecurity IoT [Invited Talk]. Euregio Days Forum Alpbach, Alpbach, Austria.
Schöttle, P. (2025, May 8). Josef Ressel Centre for Security Analysis of IoT Devices [Conference Presentation]. FFH2025 18. Forschungsforum der österreichischen Fachhochschulen, Vienna, Austria.
Schöttle, P. (2025, February 20). The Cyber Resilience Act and its Meaning for Cybersecurity Vendors [Invited Talk]. AV-Comparatives Security Summit & Awards, Innsbruck, Austria.

Supervised bachelor theses

Kelmer Romed (2025): Anomalie Erkennung in einem LoRaWAN Netzwerk
Buchmann Mira (2025): State-sponsored Actors and Their Implications for Web Application Security
Gritsch Lukas (2025): Persönliches Trainingssystem für Luftgewehrschützen:innen
Windisch Jakob (2025): Comparative Analysis of Self-Supervised Learning Algorithms for Effective Data Labeling and Performance Improvements in Computer Vision Models
Brandacher Daniel (2025): Evaluierung wesentlicher Einflussfaktoren bei der Implementierung eines lokalen Open Source Large Language Models
Ladner Adrian (2025): Reinforcement Learning für die Anomalieerkennung in Netzwerken
Kalupa Aaron Joel (2025): Gamifizierte IT-Sicherheit: Design, Umsetzung und Evaluation einer webbasierten Lernplattform
Jarosch Simon (2024): From Zero to h3r0 Creating a Web Application Security Playbook for Students
Müller Sandra (2024): Analyse der Integration von Securability und deren Einfluss auf die Arbeitsumgebung in österreichischen IT-Unternehmen
Witsch Phillipp (2024): Optimierung der Operationsplanung mit Hilfe von Machine Learning in den Tirol Kliniken
Genctan Pascal (2024): Effiziente Bilderkennung in der Pharmaproduktion durch Supervised Learning
Jauck Nicholas (2024): Screenshot - resistente digitale Wasserzeichen für soziale Netzwerke
Burns-Balog Jana Madison (2024): Towards More Secure Databases : Developing an Adaptive Deep Forest -Based SQL Injection Detection Tool
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

Supervised master theses

Sandmayr Maximilian (2024): Video Analysis in Supermarkets to Prevent Theft
Kaltenstadler Marco (2024): Towards Efficient and Secure Update Management Mechanisms for IoT Devices: An Analysis of the Matter Standard
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