no code implementations • 27 Dec 2022 • Xiaojun Xu, Yue Yu, Hanzhang Wang, Alok Lal, Carl A. Gunter, Bo Li
In this paper, we propose a general adversarial edge detection pipeline EDoG without requiring knowledge of the attack strategies based on graph generation.
1 code implementation • 8 Oct 2019 • Xiaojun Xu, Qi. Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, Bo Li
To train the meta-model without knowledge of the attack strategy, we introduce a technique called jumbo learning that samples a set of Trojaned models following a general distribution.
no code implementations • 25 Sep 2019 • Yunhui Long, Suxin Lin, Zhuolin Yang, Carl A. Gunter, Han Liu, Bo Li
We present a novel approach named G-PATE for training differentially private data generator.
2 code implementations • NeurIPS 2021 • Yunhui Long, Boxin Wang, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li
In particular, we train a student data generator with an ensemble of teacher discriminators and propose a novel private gradient aggregation mechanism to ensure differential privacy on all information that flows from teacher discriminators to the student generator.
1 code implementation • 13 Feb 2018 • Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiao-Feng Wang, Haixu Tang, Carl A. Gunter, Kai Chen
Membership Inference Attack (MIA) determines the presence of a record in a machine learning model's training data by querying the model.
no code implementations • 24 Jan 2018 • Xuejing Yuan, Yuxuan Chen, Yue Zhao, Yunhui Long, Xiaokang Liu, Kai Chen, Shengzhi Zhang, Heqing Huang, Xiao-Feng Wang, Carl A. Gunter
For this purpose, we developed novel techniques that address a key technical challenge: integrating the commands into a song in a way that can be effectively recognized by ASR through the air, in the presence of background noise, while not being detected by a human listener.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 26 Aug 2017 • Vincent Bindschaedler, Reza Shokri, Carl A. Gunter
We demonstrate the efficiency of this generative technique on a large dataset; it is shown to preserve the utility of original data with respect to various statistical analysis and machine learning measures.
no code implementations • 28 Mar 2017 • Nan Zhang, Soteris Demetriou, Xianghang Mi, Wenrui Diao, Kan Yuan, Peiyuan Zong, Feng Qian, Xiao-Feng Wang, Kai Chen, Yuan Tian, Carl A. Gunter, Kehuan Zhang, Patrick Tague, Yue-Hsun Lin
We systemize this process, by proposing a taxonomy for the IoT ecosystem and organizing IoT security into five problem areas.
Cryptography and Security