collaborators

11 papers

cs.RO2026

When Prompts Control Robots: Prompt Injection Attacks in Multi-Agent Robotic Systems

Neha Nagaraja, Amisha Bagari, Hayretdin Bahsi

Large language models are increasingly integrated into autonomous robotic systems for task planning and control, but this integration exposes them to prompt injection attacks that…

cs.CR2026

From Prompt to Physical Actuation: Holistic Threat Modeling of LLM-Enabled Robotic Systems

Neha Nagaraja, Hayretdin Bahsi, Carlo R. da Cunha

As large language models are integrated into autonomous robotic systems for task planning and control, compromised inputs or unsafe model outputs can propagate through the planning…

cs.CR2026

Incremental Federated Learning for Intrusion Detection in IoT Networks under Evolving Threat Landscape

Muaan Ur Rehman, Hayretdin Bahsi, Rajesh Kalakoti

The expansion of Internet of Things (IoT) devices has increased the attack surface of networks, necessitating a robust and adaptive intrusion detection systems. Machine learning ba…

cs.CR2026

Where Do LLM-based Systems Break? A System-Level Security Framework for Risk Assessment and Treatment

Neha Nagaraja, Hayretdin Bahsi

Large Language Models (LLMs) are increasingly integrated into safety-critical workflows, yet existing security analyses remain fragmented and often isolate model behavior from the…

cs.CR2026

Goal-Driven Risk Assessment for LLM-Powered Systems: A Healthcare Case Study

Neha Nagaraja, Hayretdin Bahsi

While incorporating LLMs into systems offers significant benefits in critical application areas such as healthcare, new security challenges emerge due to the potential cyber kill c…

cs.CR2026

Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning

Xuhui Dou, Hayretdin Bahsi, Alejandro Guerra-Manzanares

Recent work applies Large Language Models (LLMs) to source-code vulnerability detection, but most evaluations still rely on random train-test splits that ignore time and overestima…