5 papers
"Sorry for bugging you so much." Exploring Developers' Behavior Towards Privacy-Compliant Implementation
Stefan Albert Horstmann, Sandy Hong, David Klein +5
While protecting user data is essential, software developers often fail to fulfill privacy requirements. However, the reasons why they struggle with privacy-compliant implementatio…
On the Effectiveness of Adversarial Training on Malware Classifiers
Hamid Bostani, Jacopo Cortellazzi, Daniel Arp +3
Adversarial Training (AT) is a key defense against Machine Learning evasion attacks, but its effectiveness for real-world malware detection remains poorly understood. This uncertai…
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection
Hamid Bostani, Zhengyu Zhao, Zhuoran Liu +1
Machine Learning (ML) promises to enhance the efficacy of Android Malware Detection (AMD); however, ML models are vulnerable to realistic evasion attacks--crafting realizable Adver…
Spatial-Domain Wireless Jamming with Reconfigurable Intelligent Surfaces
Philipp Mackensen, Paul Staat, Stefan Roth +3
Wireless communication infrastructure is a cornerstone of modern digital society, yet it remains vulnerable to the persistent threat of wireless jamming. Attackers can easily creat…
Vulnerability, Where Art Thou? An Investigation of Vulnerability Management in Android Smartphone Chipsets
Daniel Klischies, Philipp Mackensen, Veelasha Moonsamy
Vulnerabilities in Android smartphone chipsets have severe consequences, as recent real-world attacks have demonstrated that adversaries can leverage vulnerabilities to execute arb…