3 citations · 3 across the 2 of their papers we have counts for
4 papers
AEIOU: A Unified Defense Framework against NSFW Prompts in Text-to-Image Models
Yiming Wang, Jiahao Chen, Qingming Li +4
As text-to-image (T2I) models advance and gain widespread adoption, their associated safety concerns are becoming increasingly critical. Malicious users exploit these models to gen…
TextDefense: Adversarial Text Detection based on Word Importance Entropy
Lujia Shen, Xuhong Zhang, Shouling Ji +4
Currently, natural language processing (NLP) models are wildly used in various scenarios. However, NLP models, like all deep models, are vulnerable to adversarially generated text.…
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
Pengyu Qiu, Xuhong Zhang, Shouling Ji +3
Vertical Federated Learning (VFL) is a trending collaborative machine learning model training solution. Existing industrial frameworks employ secure multi-party computation techniq…
Hijack Vertical Federated Learning Models As One Party
Pengyu Qiu, Xuhong Zhang, Shouling Ji +4
Vertical federated learning (VFL) is an emerging paradigm that enables collaborators to build machine learning models together in a distributed fashion. In general, these parties h…