7 papers
Chameleon: Recovering Cyber-Physical Systems from Memory Corruption Attacks via ML Surrogates
Mohsen Salehi, Karthik Pattabiraman
Cyber-physical systems (CPSs) are increasingly deployed in every aspect of our lives and can be compromised through memory corruption vulnerabilities, allowing attackers to hijack…
Framework for Discovering GPS Spoofing Attacks in Drone Swarms
Yingao Elaine Yao, Pritam Dash, Karthik Pattabiraman
Swarm robotics, particularly drone swarms, are used in various safety-critical tasks. While a lot of attention has been given to improving swarm control algorithms for improved int…
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices
Mohammadreza Hallajiyan, Xueren Ge, Athish Pranav Dharmalingam +4
The growing integration of artificial intelligence (AI) and machine learning (ML) in medical systems requires effective measures to address emerging security risks. One such risk i…
ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks
Mohammed Elnawawy, Gargi Mitra, Shahrear Iqbal +1
Safety-critical domains like healthcare rely on deep neural networks (DNNs) for prediction, yet DNNs remain vulnerable to evasion attacks. Anomaly detectors (ADs) are widely used t…
ARMOR: Robust Reinforcement Learning-based Control for UAVs under Physical Attacks
Pritam Dash, Ethan Chan, Nathan P. Lawrence +1
Unmanned Aerial Vehicles (UAVs) depend on onboard sensors for perception, navigation, and control. However, these sensors are susceptible to physical attacks, such as GPS spoofing,…
Systems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices
Gargi Mitra, Mohammadreza Hallajiyan, Inji Kim +5
The integration of AI/ML into medical devices is rapidly transforming healthcare by enhancing diagnostic and treatment facilities. However, this advancement also introduces serious…