11 papers
ExplainGuard: A Zero Trust Framework for Post-Hoc Explanation Integrity Guarantees in Blackbox XAI Models
Maraz Mia, Shovan Roy, Mir Mehedi A. Pritom +1
As machine learning (ML) models are increasingly deployed in high-stakes environments, explainable AI (XAI) methods like SHAP and LIME have become essential for regulatory complian…
PANOPTICON: A PII-Based Assemblage of Naturalistic Output Tokens for Investigating Privacy Leakage Within LLM Context Window
Ryan Thornton, Mir Mehedi Ahsan Pritom, Maanak Gupta
Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment. While this automation provi…
VEXAIoT: Autonomous IoT Vulnerability EXploitation using AI Agents
Katherine Swinea, Kshitiz Aryal, Lopamudra Praharaj +1
Internet of Things (IoT) systems are inherently vulnerable due to constrained hardware, outdated firmware, and insecure default configurations, creating a need for scalable and ada…
Privacy Enhanced PEFT: Tensor Train Decomposition Improves Privacy Utility Tradeoffs under DP-SGD
Pradip Kunwar, Minh Vu, Maanak Gupta +1
Fine-tuning large language models on sensitive data poses significant privacy risks, as membership inference attacks can reveal whether individual records were used during training…
A Survey of Agentic AI and Cybersecurity: Challenges, Opportunities and Use-case Prototypes
Sahaya Jestus Lazer, Kshitiz Aryal, Maanak Gupta +1
Agentic AI marks an important transition from single-step generative models to systems capable of reasoning, planning, acting, and adapting over long-lasting tasks. By integrating…
RAG-targeted Adversarial Attack on LLM-based Threat Detection and Mitigation Framework
Seif Ikbarieh, Kshitiz Aryal, Maanak Gupta
The rapid expansion of the Internet of Things (IoT) is reshaping communication and operational practices across industries, but it also broadens the attack surface and increases su…