92 citations · 211 across the 21 of their papers we have counts for
4 papers · 1 filter
Combining Machine Learning Defenses without Conflicts
Vasisht Duddu, Rui Zhang, N. Asokan
Machine learning (ML) defenses protect against various risks to security, privacy, and fairness. Real-life models need simultaneous protection against multiple different risks whic…
Privacy Bias in Language Models: A Contextual Integrity-based Auditing Metric
Yan Shvartzshnaider, Vasisht Duddu
As large language models (LLMs) are integrated into sociotechnical systems, it is crucial to examine the privacy biases they exhibit. We define privacy bias as the appropriateness…
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations
Vasisht Duddu, Oskari Järvinen, Lachlan J Gunn +1
Regulations increasingly call for various assurances from machine learning (ML) model providers about their training data, training process, and model behavior. For better transpar…
Espresso: Robust Concept Filtering in Text-to-Image Models
Anudeep Das, Vasisht Duddu, Rui Zhang +1
Diffusion based text-to-image models are trained on large datasets scraped from the Internet, potentially containing unacceptable concepts (e.g., copyright-infringing or unsafe). W…