7 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…
Explainable but Vulnerable: Adversarial Attacks on XAI Explanation in Cybersecurity Applications
Maraz Mia, Mir Mehedi A. Pritom
Explainable Artificial Intelligence (XAI) has aided machine learning (ML) researchers with the power of scrutinizing the decisions of the black-box models. XAI methods enable looki…
Characterizing Event-themed Malicious Web Campaigns: A Case Study on War-themed Websites
Maraz Mia, Mir Mehedi A. Pritom, Tariqul Islam +1
Cybercrimes such as online scams and fraud have become prevalent. Cybercriminals often abuse various global or regional events as themes of their fraudulent activities to breach us…
Securing Proof of Stake Blockchains: Leveraging Multi-Agent Reinforcement Learning for Detecting and Mitigating Malicious Nodes
Faisal Haque Bappy, Tariqul Islam, Kamrul Hasan +2
Proof of Stake (PoS) blockchains offer promising alternatives to traditional Proof of Work (PoW) systems, providing scalability and energy efficiency. However, blockchains operate…
Can Features for Phishing URL Detection Be Trusted Across Diverse Datasets? A Case Study with Explainable AI
Maraz Mia, Darius Derakhshan, Mir Mehedi A. Pritom
Phishing has been a prevalent cyber threat that manipulates users into revealing sensitive private information through deceptive tactics, designed to masquerade as trustworthy enti…