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20152026
most citedDefending against Sybil Devices in Crowdsourced Mapping Services

19 citations · 50 across the 12 of their papers we have counts for

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Showing cs.CRShow all

9 papers · 1 filter

cs.CR2026

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…

cs.CR2026

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…

cs.CR2026

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…

cs.CR2025★ 1 cited

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).…

cs.CR2024★ 4 cited

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…

cs.CR2024★ 1 cited

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…

cs.CR2023

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…

cs.CR2023★ 3 cited

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…

cs.CR2023★ 13 cited

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…