6 citations · 20 across the 22 of their papers we have counts for
7 papers · 1 filter
NinjaDoH: A Censorship-Resistant Moving Target DoH Server Using Hyperscalers and IPNS
Scott Seidenberger, Marc Beret, Raveen Wijewickrama +2
We introduce NinjaDoH, a novel DNS over HTTPS (DoH) protocol that leverages the InterPlanetary Name System (IPNS), along with public cloud infrastructure, to create a censorship-re…
Promptly Yours? A Human Subject Study on Prompt Inference in AI-Generated Art
Khoi Trinh, Joseph Spracklen, Raveen Wijewickrama +3
The emerging field of AI-generated art has witnessed the rise of prompt marketplaces, where creators can purchase, sell, or share prompts for generating unique artworks. These mark…
Why You've Got Mail: Evaluating Inbox Privacy Implications of Email Marketing Practices in Online Apps and Services
Scott Seidenberger, Oluwasijibomi Ajisegiri, Noah Pursell +2
This study explores the widespread perception that personal data, such as email addresses, may be shared or sold without informed user consent, investigating whether these concerns…
Spiking Neural Networks in Vertical Federated Learning: Performance Trade-offs
Maryam Abbasihafshejani, Anindya Maiti, Murtuza Jadliwala
Federated machine learning enables model training across multiple clients while maintaining data privacy. Vertical Federated Learning (VFL) specifically deals with instances where…
We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs
Joseph Spracklen, Raveen Wijewickrama, A H M Nazmus Sakib +3
The reliance of popular programming languages such as Python and JavaScript on centralized package repositories and open-source software, combined with the emergence of code-genera…
Generating Print-Ready Personalized AI Art Products from Minimal User Inputs
Noah Pursell, Anindya Maiti
We present a novel framework to advance generative artificial intelligence (AI) applications in the realm of printed art products, specifically addressing large-format products tha…
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
Kavita Kumari, Murtuza Jadliwala, Sumit Kumar Jha +1
Model explanations improve the transparency of black-box machine learning (ML) models and their decisions; however, they can also be exploited to carry out privacy threats such as…