Search Results for author: Yunhui Long

Found 11 papers, 4 papers with code

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks

no code implementations8 Sep 2022 Chulin Xie, Yunhui Long, Pin-Yu Chen, Qinbin Li, Arash Nourian, Sanmi Koyejo, Bo Li

We then provide two robustness certification criteria: certified prediction and certified attack inefficacy for DPFL on both user and instance levels.

Federated Learning

Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions

no code implementations8 Sep 2022 Chulin Xie, Zhong Cao, Yunhui Long, Diange Yang, Ding Zhao, Bo Li

However, training AVs usually requires a large amount of training data collected from different driving environments (e. g., cities) as well as different types of personal information (e. g., working hours and routes).

Autonomous Vehicles

SecretGen: Privacy Recovery on Pre-Trained Models via Distribution Discrimination

1 code implementation25 Jul 2022 Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao, Bo Li

We first explore different statistical information which can discriminate the private training distribution from other distributions.

Model Selection Transfer Learning

Certified Robustness for Free in Differentially Private Federated Learning

no code implementations29 Sep 2021 Chulin Xie, Yunhui Long, Pin-Yu Chen, Krishnaram Kenthapadi, Bo Li

Federated learning (FL) provides an efficient training paradigm to jointly train a global model leveraging data from distributed users.

Federated Learning

LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis

no code implementations14 Aug 2021 Fan Wu, Yunhui Long, Ce Zhang, Bo Li

We show that these DP GCN mechanisms are not always resilient against LinkTeller empirically under mild privacy guarantees ($\varepsilon>5$).

Privacy Preserving Recommendation Systems +1

DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation

2 code implementations20 Mar 2021 Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li

In this paper, we aim to explore the power of generative models and gradient sparsity, and propose a scalable privacy-preserving generative model DATALENS.

Dimensionality Reduction Navigate +1

G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators

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.

BIG-bench Machine Learning Privacy Preserving

Understanding Membership Inferences on Well-Generalized Learning Models

1 code implementation13 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.

BIG-bench Machine Learning Inference Attack +1

CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition

no code implementations24 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

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