Esteban Rivera

• Master of Science
• PhD Student at Technical University of Munich

Deep learning models for autonomous driving, encompassing perception, planning, and control, depend on vast datasets to achieve their high performance. However, their generalization often suffers due to domain-specific data distributions, making an effective scene-based categorization of samples necessary to improve their reliability across diverse...

Adversarial attacks have recently gained popularity due to their simplicity, impact, and applicability to a wide range of machine learning scenarios. However, knowledge of a particular security scenario can be advantageous for adversaries to craft better attacks. In other words, in some scenarios, attackers may come up naturally with ad hoc black-b...

LiDAR object detection algorithms based on neural networks for autonomous driving require large amounts of data for training, validation, and testing. As real-world data collection and labeling are time-consuming and expensive, simulation-based synthetic data generation is a viable alternative. However, using simulated data for the training of neur...

LiDAR object detection algorithms based on neural networks for autonomous driving require large amounts of data for training, validation, and testing. As real-world data collection and labeling are time-consuming and expensive, simulation-based synthetic data generation is a viable alternative. However, using simulated data for the training of neur...

The rise in popularity of web and mobile applications brings about a need of robust authentication systems. Behavioral Biometrics Authentication has emerged as a complementary risk-based authentication approach which aims at profiling users based on their interaction with computers/smartphones. In this work we propose a novel approach based on Siam...

Although browser fingerprinting has been widely studied from a privacy angle, there is also a case for fingerprinting in the context of risk-based authentication. Given that most browser-context features can be easily spoofed, APIs that potentially depend both on software and hardware have gained interest. HTML5 Canvas has been shown to provide a c...

The popularity of face-authentication systems has also generated interest in the study of malicious authentication attempts, such as face spoofing attacks. In this study we investigate two dynamic face-authentication challenges: the camera close-up, and head-rotation paradigms. For each paradigm we developed an ML-based face-authentication system t...

Providing integrity guarantees for websites rendered on a user’s browser is a crucial security property for web applications. There are several ways to tamper with data being received or rendered on the client side, including browser hijacking, malicious plugins, cross-site scripting attacks and manipulation of data in transit. Detecting such attac...

Distributed (i.e. mobile) enrollment to services such as banking is gaining popularity. In such processes, users are often asked to provide proof of identity by taking a picture of an ID. For this to work securely, it is critical to automatically check basic document features, perform text recognition, among others. Furthermore, challenging context...