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ORCIDKonstantin Böttinger
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2020 – today
- 2024
[c33]Nicolas M. Müller, Piotr Kawa, Wei Herng Choong, Edresson Casanova, Eren Gölge, Thorsten Müller, Piotr Syga, Philip Sperl, Konstantin Böttinger:
MLAAD: The Multi-Language Audio Anti-Spoofing Dataset. IJCNN 2024: 1-7- [c32]Nicolas M. Müller, Simon Roschmann, Shahbaz Khan, Philip Sperl, Konstantin Böttinger:
Shortcut Detection With Variational Autoencoders. IJCNN 2024: 1-7 - [i30]Nicolas M. Müller, Piotr Kawa, Wei Herng Choong, Edresson Casanova, Eren Gölge, Thorsten Müller, Piotr Syga, Philip Sperl, Konstantin Böttinger:
MLAAD: The Multi-Language Audio Anti-Spoofing Dataset. CoRR abs/2401.09512 (2024) - [i29]Nicolas M. Müller, Piotr Kawa, Shen Hu, Matthias Neu, Jennifer Williams, Philip Sperl, Konstantin Böttinger:
A New Approach to Voice Authenticity. CoRR abs/2402.06304 (2024) - [i28]Daniel Kowatsch, Nicolas M. Müller, Kilian Tscharke, Philip Sperl, Konstantin Böttinger:
Imbalance in Regression Datasets. CoRR abs/2402.11963 (2024) - [i27]Nicolas M. Müller, Nicholas W. D. Evans, Hemlata Tak, Philip Sperl, Konstantin Böttinger:
Harder or Different? Understanding Generalization of Audio Deepfake Detection. CoRR abs/2406.03512 (2024) - 2023
- [c31]Nicolas M. Müller, Maximilian Burgert, Pascal Debus, Jennifer Williams, Philip Sperl, Konstantin Böttinger:
Protecting Publicly Available Data With Machine Learning Shortcuts. BMVC 2023: 685-698 - [c30]Nicolas M. Müller, Jochen Jacobs, Jennifer Williams, Konstantin Böttinger:
Localized Shortcut Removal. CVPR Workshops 2023: 3721-3725 - [c29]Nicolas M. Müller, Philip Sperl, Konstantin Böttinger:
Complex-valued neural networks for voice anti-spoofing. INTERSPEECH 2023: 3814-3818 - [i26]Karla Pizzi, Franziska Boenisch, Ugur Sahin, Konstantin Böttinger:
Introducing Model Inversion Attacks on Automatic Speaker Recognition. CoRR abs/2301.03206 (2023) - [i25]Nicolas M. Müller, Simon Roschmann, Shahbaz Khan, Philip Sperl, Konstantin Böttinger:
Shortcut Detection with Variational Autoencoders. CoRR abs/2302.04246 (2023) - [i24]Nicolas M. Müller, Philip Sperl, Konstantin Böttinger:
Complex-valued neural networks for voice anti-spoofing. CoRR abs/2308.11800 (2023) - [i23]Nicolas M. Müller, Maximilian Burgert, Pascal Debus
, Jennifer Williams, Philip Sperl, Konstantin Böttinger:
Protecting Publicly Available Data With Machine Learning Shortcuts. CoRR abs/2310.19381 (2023) - [i22]Ana Radutoiu, Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
Physical Adversarial Examples for Multi-Camera Systems. CoRR abs/2311.08539 (2023) - 2022
- [c28]Paul Andrei Sava, Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
Assessing the Impact of Transformations on Physical Adversarial Attacks. AISec@CCS 2022: 79-90 - [c27]Ching-Yu Kao, Junhao Chen, Karla Markert, Konstantin Böttinger:
Rectifying adversarial inputs using XAI techniques. EUSIPCO 2022: 573-577 - [c26]Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
Anomaly Detection by Recombining Gated Unsupervised Experts. IJCNN 2022: 1-8 - [c25]Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly Generators. IJCNN 2022: 1-8 - [c24]Nicolas M. Müller, Pavel Czempin, Franziska Dieckmann, Adam Froghyar, Konstantin Böttinger:
Does Audio Deepfake Detection Generalize? INTERSPEECH 2022: 2783-2787 - [c23]Ching-Yu Kao, Hongjia Wan, Karla Markert, Konstantin Böttinger:
Real or Fake? A Practical Method for Detecting Tempered Images. IPAS 2022: 1-6 - [c22]Jan-Philipp Schulze, Philip Sperl, Ana Radutoiu, Carla Sagebiel, Konstantin Böttinger:
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient. ECML/PKDD (1) 2022: 209-224 - [i21]Karla Markert, Donika Mirdita, Konstantin Böttinger:
Language Dependencies in Adversarial Attacks on Speech Recognition Systems. CoRR abs/2202.00399 (2022) - [i20]Karla Markert, Romain Parracone, Mykhailo Kulakov, Philip Sperl, Ching-Yu Kao, Konstantin Böttinger:
Visualizing Automatic Speech Recognition - Means for a Better Understanding? CoRR abs/2202.00673 (2022) - [i19]Nicolas M. Müller, Pavel Czempin, Franziska Dieckmann, Adam Froghyar, Konstantin Böttinger:
Does Audio Deepfake Detection Generalize? CoRR abs/2203.16263 (2022) - [i18]Jan-Philipp Schulze, Philip Sperl, Ana Radutoiu, Carla Sagebiel, Konstantin Böttinger:
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient. CoRR abs/2206.10259 (2022) - [i17]Nicolas M. Müller, Jochen Jacobs, Jennifer Williams, Konstantin Böttinger:
Shortcut Removal for Improved OOD-Generalization. CoRR abs/2211.15510 (2022) - 2021
- [j4]Karla Markert, Konstantin Böttinger:
Robuste Lernverfahren. Datenschutz und Datensicherheit 45(7): 457-461 (2021) - [c21]Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
DA3G: Detecting Adversarial Attacks by Analysing Gradients. ESORICS (1) 2021: 563-583 - [c20]Nicolas M. Müller, Konstantin Böttinger:
Adversarial Vulnerability of Active Transfer Learning. IDA 2021: 116-127 - [i16]Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly Generators. CoRR abs/2101.04645 (2021) - [i15]Nicolas M. Müller, Konstantin Böttinger:
Adversarial Vulnerability of Active Transfer Learning. CoRR abs/2101.10792 (2021) - [i14]Pascal Debus, Nicolas M. Müller, Konstantin Böttinger:
Deep Reinforcement Learning for Backup Strategies against Adversaries. CoRR abs/2102.06632 (2021) - [i13]Nicolas M. Müller, Simon Roschmann, Konstantin Böttinger:
Defending against Adversarial Denial-of-Service Attacks. CoRR abs/2104.06744 (2021) - [i12]Franziska Boenisch, Philip Sperl, Konstantin Böttinger:
Gradient Masking and the Underestimated Robustness Threats of Differential Privacy in Deep Learning. CoRR abs/2105.07985 (2021) - [i11]Nicolas M. Müller, Franziska Dieckmann, Pavel Czempin, Roman Canals, Konstantin Böttinger:
Speech is Silver, Silence is Golden: What do ASVspoof-trained Models Really Learn? CoRR abs/2106.12914 (2021) - [i10]Nicolas M. Müller, Karla Markert, Konstantin Böttinger:
Human Perception of Audio Deepfakes. CoRR abs/2107.09667 (2021) - 2020
- [c19]Philip Sperl, Ching-Yu Kao, Peng Chen, Xiao Lei, Konstantin Böttinger:
DLA: Dense-Layer-Analysis for Adversarial Example Detection. EuroS&P 2020: 198-215 - [c18]Philip Sperl, Jan-Philipp Schulze, Konstantin Böttinger:
Activation Anomaly Analysis. ECML/PKDD (2) 2020: 69-84 - [c17]Nicolas M. Müller, Daniel Kowatsch, Konstantin Böttinger:
Data Poisoning Attacks on Regression Learning and Corresponding Defenses. PRDC 2020: 80-89 - [i9]Philip Sperl, Jan-Philipp Schulze, Konstantin Böttinger:
A3: Activation Anomaly Analysis. CoRR abs/2003.01801 (2020) - [i8]Philip Sperl, Konstantin Böttinger:
Optimizing Information Loss Towards Robust Neural Networks. CoRR abs/2008.03072 (2020) - [i7]Jan-Philipp Schulze, Philip Sperl, Konstantin Böttinger:
Anomaly Detection by Recombining Gated Unsupervised Experts. CoRR abs/2008.13763 (2020) - [i6]Nicolas Michael Müller, Daniel Kowatsch, Konstantin Böttinger:
Data Poisoning Attacks on Regression Learning and Corresponding Defenses. CoRR abs/2009.07008 (2020) - [i5]Tom Dörr, Karla Markert, Nicolas M. Müller, Konstantin Böttinger:
Towards Resistant Audio Adversarial Examples. CoRR abs/2010.07190 (2020)
2010 – 2019
- 2019
- [b1]Konstantin Böttinger:
Fuzzing with Stochastic Feedback Processes. Technical University of Munich, Germany, 2019 - [c16]Philip Sperl, Konstantin Böttinger:
Side-Channel Aware Fuzzing. ESORICS (1) 2019: 259-278 - [c15]Gerhard Hansch, Peter Schneider, Kai Fischer, Konstantin Böttinger:
A Unified Architecture for Industrial IoT Security Requirements in Open Platform Communications. ETFA 2019: 325-332 - [c14]Nicolas M. Müller, Pascal Debus, Daniel Kowatsch, Konstantin Böttinger:
Distributed Anomaly Detection of Single Mote Attacks in RPL Networks. ICETE (2) 2019: 378-385 - [c13]Jan-Philipp Schulze, Artur Mrowca, Elizabeth Ren, Hans-Andrea Loeliger, Konstantin Böttinger:
Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy. KDD 2019: 2059-2068 - [c12]Nicolas M. Müller, Daniel Kowatsch, Pascal Debus, Donika Mirdita, Konstantin Böttinger:
On GDPR Compliance of Companies' Privacy Policies. TSD 2019: 151-159 - [c11]Felix Fischer, Huang Xiao, Ching-yu Kao, Yannick Stachelscheid, Benjamin Johnson, Danial Razar, Paul Fawkesley, Nat Buckley, Konstantin Böttinger, Paul Muntean, Jens Grossklags:
Stack Overflow Considered Helpful! Deep Learning Security Nudges Towards Stronger Cryptography. USENIX Security Symposium 2019: 339-356 - [i4]Philip Sperl, Konstantin Böttinger:
Side-Channel Aware Fuzzing. CoRR abs/1908.05012 (2019) - [i3]Philip Sperl, Ching-yu Kao, Peng Chen, Konstantin Böttinger:
DLA: Dense-Layer-Analysis for Adversarial Example Detection. CoRR abs/1911.01921 (2019) - 2018
- [c10]Peter Schneider, Konstantin Böttinger:
High-Performance Unsupervised Anomaly Detection for Cyber-Physical System Networks. CPS-SPC@CCS 2018: 1-12 - [c9]Konstantin Böttinger, Patrice Godefroid, Rishabh Singh:
Deep Reinforcement Fuzzing. IEEE Symposium on Security and Privacy Workshops 2018: 116-122 - [i2]Konstantin Böttinger, Patrice Godefroid, Rishabh Singh:
Deep Reinforcement Fuzzing. CoRR abs/1801.04589 (2018) - 2017
- [j3]Giuseppe Settanni, Florian Skopik, Yegor Shovgenya, Roman Fiedler, Mark Carolan, Damien Conroy, Konstantin Böttinger, Mark Gall, Gerd Brost, Christophe Ponchel, Mirko Haustein, Helmut Kaufmann, Klaus Theuerkauf, Pia Olli:
A collaborative cyber incident management system for European interconnected critical infrastructures. J. Inf. Secur. Appl. 34: 166-182 (2017) - [c8]Konstantin Böttinger:
Guiding a Colony of Black-Box Fuzzers with Chemotaxis. IEEE Symposium on Security and Privacy Workshops 2017: 11-16 - [c7]Felix Fischer, Konstantin Böttinger, Huang Xiao, Christian Stransky, Yasemin Acar, Michael Backes, Sascha Fahl:
Stack Overflow Considered Harmful? The Impact of Copy&Paste on Android Application Security. IEEE Symposium on Security and Privacy 2017: 121-136 - [i1]Felix Fischer, Konstantin Böttinger, Huang Xiao, Christian Stransky, Yasemin Acar, Michael Backes, Sascha Fahl:
Stack Overflow Considered Harmful? The Impact of Copy&Paste on Android Application Security. CoRR abs/1710.03135 (2017) - 2016
- [j2]Konstantin Böttinger:
Fuzzing binaries with Lévy flight swarms. EURASIP J. Inf. Secur. 2016: 28 (2016) - [j1]Konstantin Böttinger:
Chemotactic Test Case Recombinationfor Large-Scale Fuzzing. J. Cyber Secur. Mobil. 5(4): 269-286 (2016) - [c6]Konstantin Böttinger, Claudia Eckert:
DeepFuzz: Triggering Vulnerabilities Deeply Hidden in Binaries - (Extended Abstract). DIMVA 2016: 25-34 - [c5]Konstantin Böttinger:
Hunting Bugs with Lévy Flight Foraging. IEEE Symposium on Security and Privacy Workshops 2016: 111-117 - 2015
- [c4]Konstantin Böttinger, Dieter Schuster, Claudia Eckert:
Detecting Fingerprinted Data in TLS Traffic. AsiaCCS 2015: 633-638 - [c3]Giuseppe Settanni, Florian Skopik, Helmut Kaufmann, Tobias Gebhardt, Klaus Theuerkauf, Konstantin Böttinger, Mark Carolan, Damien Conroy, Pia Olli:
A Blueprint for a Pan-European Cyber Incident Analysis System. ICS-CSR 2015 - 2014
- [c2]Julian Horsch, Konstantin Böttinger, Michael Weiß, Sascha Wessel, Frederic Stumpf:
TrustID: trustworthy identities for untrusted mobile devices. CODASPY 2014: 281-288 - 2012
- [c1]Daniel Angermeier, Konstantin Böttinger, Andreas Ibing, Dieter Schuster, Frederic Stumpf, Dirk Wacker:
A Secure Architecture for Smart Meter Systems. CSS 2012: 108-122
Coauthor Index
aka: Nicolas Michael Müller
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