19 citations · 50 across the 12 of their papers we have counts for
14 papers
Natural Code Transformation Confuses Agents in Vulnerability Analysis
Jie Zhu, Ronik Bhaskar, Heather Zheng +2
Having demonstrated a strong potential for automating vulnerability discovery, AI agents can also be used to attack software systems at scale. Today's software systems need mechani…
Mitigating Private Data Leakage in LLMs with Whiteout
Anna Yoo Jeong Ha, Ronik Bhaskar, Haitao Zheng +1
Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible website and user inputs. As a result…
An Empirical Analysis of AI Slop in Music Streaming
Stanley Wu, Josephine Passananti, Viresh Mittal +3
Generative AI models lower the bar for content creation, making it easy for any user to create professional-looking images, text and music with minimal effort. This has enabled a n…
On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling
Stanley Wu, Ronik Bhaskar, Anna Yoo Jeong Ha +3
Today's text-to-image generative models are trained on millions of images sourced from the Internet, each paired with a detailed caption produced by Vision-Language Models (VLMs).…
Somesite I Used To Crawl: Awareness, Agency and Efficacy in Protecting Content Creators From AI Crawlers
Enze Liu, Elisa Luo, Shawn Shan +3
The success of generative AI relies heavily on training on data scraped through extensive crawling of the Internet, a practice that has raised significant copyright, privacy, and e…
Understanding Implosion in Text-to-Image Generative Models
Wenxin Ding, Cathy Y. Li, Shawn Shan +2
Recent works show that text-to-image generative models are surprisingly vulnerable to a variety of poisoning attacks. Empirical results find that these models can be corrupted by a…
Disrupting Style Mimicry Attacks on Video Imagery
Josephine Passananti, Stanley Wu, Shawn Shan +2
Generative AI models are often used to perform mimicry attacks, where a pretrained model is fine-tuned on a small sample of images to learn to mimic a specific artist of interest.…
Inception Attacks: Immersive Hijacking in Virtual Reality Systems
Zhuolin Yang, Cathy Yuanchen Li, Arman Bhalla +2
Today's virtual reality (VR) systems provide immersive interactions that seamlessly connect users with online services and one another. However, these immersive interfaces also int…
Organic or Diffused: Can We Distinguish Human Art from AI-generated Images?
Anna Yoo Jeong Ha, Josephine Passananti, Ronik Bhaskar +4
The advent of generative AI images has completely disrupted the art world. Distinguishing AI generated images from human art is a challenging problem whose impact is growing over t…
Towards Scalable and Robust Model Versioning
Wenxin Ding, Arjun Nitin Bhagoji, Ben Y. Zhao +1
As the deployment of deep learning models continues to expand across industries, the threat of malicious incursions aimed at gaining access to these deployed models is on the rise.…
A Response to Glaze Purification via IMPRESS
Shawn Shan, Stanley Wu, Haitao Zheng +1
Recent work proposed a new mechanism to remove protective perturbation added by Glaze in order to again enable mimicry of art styles from images protected by Glaze. Despite promisi…
Can Virtual Reality Protect Users from Keystroke Inference Attacks?
Zhuolin Yang, Zain Sarwar, Iris Hwang +3
Virtual Reality (VR) has gained popularity by providing immersive and interactive experiences without geographical limitations. It also provides a sense of personal privacy through…
Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models
Shawn Shan, Wenxin Ding, Josephine Passananti +3
Data poisoning attacks manipulate training data to introduce unexpected behaviors into machine learning models at training time. For text-to-image generative models with massive tr…
Defending against Sybil Devices in Crowdsourced Mapping Services
Gang Wang, Bolun Wang, Tianyi Wang +3
Real-time crowdsourced maps such as Waze provide timely updates on traffic, congestion, accidents and points of interest. In this paper, we demonstrate how lack of strong location…