43 citations · 46 across the 15 of their papers we have counts for
14 papers · 1 filter
Privacy Conductor: An Architectural Enforcement of Contextual Integrity in LLM-Based Document Retrieval
Ryan Thornton, Mir Mehedi A. Pritom, Maanak Gupta +1
Large language model (LLM) that retrieve internal documents within an organization must decide who may receive them. Existing approaches based on Contextual Integrity ask the model…
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…
Malformer: A Multi-Modal Malware Detector Using Transformers
Samuel Howard, Kshitiz Aryal, Mahmoud Abdelsalam +3
Traditional malware detection systems that rely on a single representation of malware often fail to identify novel threats. These representations of malware binaries, also known as…
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Internet of Things (IoT) systems are inherently vulnerable due to constrained hardware, outdated firmware, and insecure default configurations, creating a need for scalable and ada…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…
LLM-based Multi-class Attack Analysis and Mitigation Framework in IoT/IIoT Networks
Seif Ikbarieh, Maanak Gupta, Elmahedi Mahalal
The Internet of Things has expanded rapidly, transforming communication and operations across industries but also increasing the attack surface and security breaches. Artificial In…
Safety and Security Analysis of Large Language Models: Benchmarking Risk Profile and Harm Potential
Charankumar Akiri, Harrison Simpson, Kshitiz Aryal +2
While the widespread deployment of Large Language Models (LLMs) holds great potential for society, their vulnerabilities to adversarial manipulation and exploitation can pose serio…
Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges
Harikha Manthena, Shaghayegh Shajarian, Jeffrey Kimmell +3
Machine learning (ML) has rapidly advanced in recent years, revolutionizing fields such as finance, medicine, and cybersecurity. In malware detection, ML-based approaches have demo…
Explainability-Informed Targeted Malware Misclassification
Quincy Card, Kshitiz Aryal, Maanak Gupta
In recent years, there has been a surge in malware attacks across critical infrastructures, requiring further research and development of appropriate response and remediation strat…
Explainability Guided Adversarial Evasion Attacks on Malware Detectors
Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam +1
As the focus on security of Artificial Intelligence (AI) is becoming paramount, research on crafting and inserting optimal adversarial perturbations has become increasingly critica…
SoK: Leveraging Transformers for Malware Analysis
Pradip Kunwar, Kshitiz Aryal, Maanak Gupta +2
The introduction of transformers has been an important breakthrough for AI research and application as transformers are the foundation behind Generative AI. A promising application…
Explainable Deep Learning Models for Dynamic and Online Malware Classification
Quincy Card, Daniel Simpson, Kshitiz Aryal +2
In recent years, there has been a significant surge in malware attacks, necessitating more advanced preventive measures and remedial strategies. While several successful AI-based m…