400 citations · 613 across the 6 of their papers we have counts for
6 papers
A Solution toward Transparent and Practical AI Regulation: Privacy Nutrition Labels for Open-source Generative AI-based Applications
Meixue Si, Shidong Pan, Dianshu Liao +4
The rapid development and widespread adoption of Generative Artificial Intelligence-based (GAI) applications have greatly enriched our daily lives, benefiting people by enhancing c…
Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches
Jianan Feng, Jiachun Li, Changqing Miao +4
Object detection has found extensive applications in various tasks, but it is also susceptible to adversarial patch attacks. The ideal defense should be effective, efficient, easy…
BDTS: Blockchain-based Data Trading System
Erya Jiang, Bo Qin, Qin Wang +5
Trading data through blockchain platforms is hard to achieve \textit{fair exchange}. Reasons come from two folds: Firstly, guaranteeing fairness between sellers and consumers is a…
SEPAL: Towards a Large-scale Analysis of SEAndroid Policy Customization
Dongsong Yu, Guangliang Yang, Guozhu Meng +9
To investigate the status quo of SEAndroid policy customization, we propose SEPAL, a universal tool to automatically retrieve and examine the customized policy rules. SEPAL applies…
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction
Bin Liang, Hongcheng Li, Miaoqiang Su +3
Recently, many studies have demonstrated deep neural network (DNN) classifiers can be fooled by the adversarial example, which is crafted via introducing some perturbations into an…
Deep Text Classification Can be Fooled
Bin Liang, Hongcheng Li, Miaoqiang Su +3
In this paper, we present an effective method to craft text adversarial samples, revealing one important yet underestimated fact that DNN-based text classifiers are also prone to a…