6 citations · 8 across the 7 of their papers we have counts for
7 papers
From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents
Pritam Dash, Tongyu Ge, Aditi Jain +2
Memory is a core component of AI agents, enabling them to accumulate knowledge across interactions and improve performance. However, persistent memory introduces the risk of memory…
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…
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,…
SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attacks
Pritam Dash, Ethan Chan, Karthik Pattabiraman
Robotic Autonomous Vehicles (RAVs) rely on their sensors for perception, and follow strict mission specifications (e.g., altitude, speed, and geofence constraints) for safe and tim…
ICS-Sniper: A Targeted Blackhole Attack on Encrypted ICS Traffic
Gargi Mitra, Chanyuan Liu, Pritam Dash +4
Modern industrial control systems (ICS) increasingly host their Supervisory Control and Data Acquisition (SCADA) services in the cloud to reduce the costs of large-scale automation…
Diagnosis-guided Attack Recovery for Securing Robotic Vehicles from Sensor Deception Attacks
Pritam Dash, Guanpeng Li, Mehdi Karimibiuki +1
Sensors are crucial for perception and autonomous operation in robotic vehicles (RV). Unfortunately, RV sensors can be compromised by physical attacks such as sensor tampering or s…
Jujutsu: A Two-stage Defense against Adversarial Patch Attacks on Deep Neural Networks
Zitao Chen, Pritam Dash, Karthik Pattabiraman
Adversarial patch attacks create adversarial examples by injecting arbitrary distortions within a bounded region of the input to fool deep neural networks (DNNs). These attacks are…