20 citations · 47 across the 11 of their papers we have counts for
12 papers
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…
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…
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…
Visually Analyze SHAP Plots to Diagnose Misclassifications in ML-based Intrusion Detection
Maraz Mia, Mir Mehedi A. Pritom, Tariqul Islam +1
Intrusion detection has been a commonly adopted detective security measures to safeguard systems and networks from various threats. A robust intrusion detection system (IDS) can es…
AbuseGPT: Abuse of Generative AI ChatBots to Create Smishing Campaigns
Ashfak Md Shibli, Mir Mehedi A. Pritom, Maanak Gupta
SMS phishing, also known as "smishing", is a growing threat that tricks users into disclosing private information or clicking into URLs with malicious content through fraudulent mo…
ConChain: A Scheme for Contention-free and Attack Resilient BlockChain
Faisal Haque Bappy, Tariqul Islam, Tarannum Shaila Zaman +2
Although blockchains have become widely popular for their use in cryptocurrencies, they are now becoming pervasive as more traditional applications adopt blockchain to ensure data…
Case Study on Detecting COVID-19 Health-Related Misinformation in Social Media
Mir Mehedi A. Pritom, Rosana Montanez Rodriguez, Asad Ali Khan +4
COVID-19 pandemic has generated what public health officials called an infodemic of misinformation. As social distancing and stay-at-home orders came into effect, many turned to so…
Data-Driven Characterization and Detection of COVID-19 Themed Malicious Websites
Mir Mehedi Ahsan Pritom, Kristin M. Schweitzer, Raymond M. Bateman +2
COVID-19 has hit hard on the global community, and organizations are working diligently to cope with the new norm of "work from home". However, the volume of remote work is unprece…
Characterizing the Landscape of COVID-19 Themed Cyberattacks and Defenses
Mir Mehedi Ahsan Pritom, Kristin M. Schweitzer, Raymond M. Bateman +2
COVID-19 (Coronavirus) hit the global society and economy with a big surprise. In particular, work-from-home has become a new norm for employees. Despite the fact that COVID-19 can…