Georg Chalupar

University of Applied Sciences Upper Austria

Papers

Total Citations

H-Index

About

Georg Chalupar is a researcher whose work sits at the intersection of hardware security, reverse engineering, and automated analysis. He is best known for his pioneering 2014 study, "Automated reverse engineering using lego," which demonstrated that state machine learning—a technique that systematically fuzzes input sequences—can be effectively applied to reverse engineer complex systems. In a particularly creative and impactful demonstration, Chalupar used a Lego robot to automate the reverse engineering of hand-held smartcard readers used for Internet banking. This work, which has accumulated 34 citations, showcased how low-cost, off-the-shelf components could be repurposed to uncover the inner workings of security-critical devices. By bridging the gap between theoretical learning algorithms and practical hardware security, Chalupar’s research has influenced subsequent work in automated vulnerability discovery and embedded system analysis. His contributions highlight the power of interdisciplinary thinking, combining robotics, machine learning, and cybersecurity to challenge assumptions about the security of everyday financial technologies.