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20242026
most citedExplainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges

43 citations · 46 across the 15 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.CR2026

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…

cs.CR2026

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…

cs.CR2026

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…

cs.AI2026

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…

cs.CR2026

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Internet of Things (IoT) systems are inherently vulnerable due to constrained hardware, outdated firmware, and insecure default configurations, creating a need for scalable and ada…

cs.CR2026

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…

cs.CR2026

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…