Stacey Truex | DeepAI

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∙ 07/16/2020

Data Poisoning Attacks Against Federated Learning Systems

Federated learning (FL) is an emerging paradigm for distributed training...

0 Vale Tolpegin, et al. ∙

∙ 07/11/2020

Understanding Object Detection Through An Adversarial Lens

Deep neural networks based object detection models have revolutionized c...

12 Ka-Ho Chow, et al. ∙

∙ 06/05/2020

LDP-Fed: Federated Learning with Local Differential Privacy

This paper presents LDP-Fed, a novel federated learning system with a fo...

12 Stacey Truex, et al. ∙

∙ 04/22/2020

A Framework for Evaluating Gradient Leakage Attacks in Federated Learning

Federated learning (FL) is an emerging distributed machine learning fram...

5 Wenqi Wei, et al. ∙

∙ 04/09/2020

TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems

The rapid growth of real-time huge data capturing has pushed the deep le...

3 Ka-Ho Chow, et al. ∙

∙ 01/25/2020

TiFL: A Tier-based Federated Learning System

Federated Learning (FL) enables learning a shared model across many clie...

0 Zheng Chai, et al. ∙

∙ 11/21/2019

Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability

Membership inference attacks seek to infer the membership of individual ...

2 Stacey Truex, et al. ∙

∙ 10/01/2019

Cross-Layer Strategic Ensemble Defense Against Adversarial Examples

Deep neural network (DNN) has demonstrated its success in multiple domai...

9 Wenqi Wei, et al. ∙

∙ 08/29/2019

Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness

Ensemble learning is a methodology that integrates multiple DNN learners...

0 Ling Liu, et al. ∙

∙ 05/15/2019

Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy

Local Differential Privacy (LDP) is popularly used in practice for priva...

0 Mehmet Emre Gursoy, et al. ∙

∙ 04/03/2019

Differentially Private Model Publishing for Deep Learning

Deep learning techniques based on neural networks have shown significant...

0 Lei Yu, et al. ∙

∙ 12/07/2018

A Hybrid Approach to Privacy-Preserving Federated Learning

Training machine learning models often requires data from multiple parti...

0 Stacey Truex, et al. ∙

∙ 06/29/2018

Adversarial Examples in Deep Learning: Characterization and Divergence

The burgeoning success of deep learning has raised the security and priv...

0 Wenqi Wei, et al. ∙

∙ 06/28/2018

Towards Demystifying Membership Inference Attacks

Membership inference attacks seek to infer membership of individual trai...

0 Stacey Truex, et al. ∙

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