20 citations · 32 across the 9 of their papers we have counts for
10 papers · 1 filter
Practical Type Inference: High-Throughput Recovery of Real-World Structures and Function Signatures
Lukas Seidel, Sam Thomas, Konrad Rieck
The recovery of types from stripped binaries is a key to exact decompilation, yet its practical realization suffers. For composite structures in particular, both layout and semanti…
Evil from Within: Machine Learning Backdoors through Hardware Trojans
Alexander Warnecke, Julian Speith, Jan-Niklas Möller +2
Backdoors pose a serious threat to machine learning, as they can compromise the integrity of security-critical systems, such as self-driving cars. While different defenses have bee…
No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning
Thorsten Eisenhofer, Erwin Quiring, Jonas Möller +3
The number of papers submitted to academic conferences is steadily rising in many scientific disciplines. To handle this growth, systems for automatic paper-reviewer assignments ar…
LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems
Niclas Kühnapfel, Stefan Preußler, Maximilian Noppel +3
Physical isolation, so called air-gapping, is an effective method for protecting security-critical computers and networks. While it might be possible to introduce malicious code th…
Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification
Erwin Quiring, Lukas Pirch, Michael Reimsbach +2
Machine learning-based systems for malware detection operate in a hostile environment. Consequently, adversaries will also target the learning system and use evasion attacks to byp…
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks
Erwin Quiring, Konrad Rieck
Backdoors and poisoning attacks are a major threat to the security of machine-learning and vision systems. Often, however, these attacks leave visible artifacts in the images that…