Media Summary: A Linear Reconstruction Approach for Attribute Gradients Look Alike: Sensitivity is Often Overestimated in FaceObfuscator: Defending Deep Learning-based Privacy

Usenix Security 24 Closed Form Bounds For Dp Sgd Against Record Level Inference Attacks - Detailed Analysis & Overview

A Linear Reconstruction Approach for Attribute Gradients Look Alike: Sensitivity is Often Overestimated in FaceObfuscator: Defending Deep Learning-based Privacy SDFuzz: Target States Driven Directed Fuzzing Penghui Li, The Chinese University of Hong Kong and Zhongguancun Laboratory; ... DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training Zihao Wang, Rui Zhu, and ... Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations

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USENIX Security '24 - Closed-Form Bounds for DP-SGD against Record-level Inference Attacks
USENIX Security '24 - A Linear Reconstruction Approach for Attribute Inference Attacks against...
USENIX Security '24 - Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD
USENIX Security '22 - Inference Attacks Against Graph Neural Networks
USENIX Security '22 - Membership Inference Attacks and Defenses in Neural Network Pruning
USENIX Security '22 - Mitigating Membership Inference Attacks by Self-Distillation Through a Novel
USENIX Security '24 - Fast and Private Inference of Deep Neural Networks by Co-designing...
USENIX Security '24 - FaceObfuscator: Defending Deep Learning-based Privacy Attacks with Gradient...
USENIX Security '24 - SAIN: Improving ICS Attack Detection Sensitivity via State-Aware Invariants
USENIX Security '24 - SDFuzz: Target States Driven Directed Fuzzing
USENIX Security '24 - DPAdapter: Improving Differentially Private Deep Learning through Noise...
USENIX Security '24 - Inference of Error Specifications and Bug Detection Using Structural...
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USENIX Security '24 - Closed-Form Bounds for DP-SGD against Record-level Inference Attacks

USENIX Security '24 - Closed-Form Bounds for DP-SGD against Record-level Inference Attacks

Closed

USENIX Security '24 - A Linear Reconstruction Approach for Attribute Inference Attacks against...

USENIX Security '24 - A Linear Reconstruction Approach for Attribute Inference Attacks against...

A Linear Reconstruction Approach for Attribute

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USENIX Security '24 - Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD

USENIX Security '24 - Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD

Gradients Look Alike: Sensitivity is Often Overestimated in

USENIX Security '22 - Inference Attacks Against Graph Neural Networks

USENIX Security '22 - Inference Attacks Against Graph Neural Networks

USENIX Security

USENIX Security '22 - Membership Inference Attacks and Defenses in Neural Network Pruning

USENIX Security '22 - Membership Inference Attacks and Defenses in Neural Network Pruning

USENIX Security

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USENIX Security '22 - Mitigating Membership Inference Attacks by Self-Distillation Through a Novel

USENIX Security '22 - Mitigating Membership Inference Attacks by Self-Distillation Through a Novel

USENIX Security

USENIX Security '24 - Fast and Private Inference of Deep Neural Networks by Co-designing...

USENIX Security '24 - Fast and Private Inference of Deep Neural Networks by Co-designing...

Fast and Private

USENIX Security '24 - FaceObfuscator: Defending Deep Learning-based Privacy Attacks with Gradient...

USENIX Security '24 - FaceObfuscator: Defending Deep Learning-based Privacy Attacks with Gradient...

FaceObfuscator: Defending Deep Learning-based Privacy

USENIX Security '24 - SAIN: Improving ICS Attack Detection Sensitivity via State-Aware Invariants

USENIX Security '24 - SAIN: Improving ICS Attack Detection Sensitivity via State-Aware Invariants

SAIN: Improving ICS

USENIX Security '24 - SDFuzz: Target States Driven Directed Fuzzing

USENIX Security '24 - SDFuzz: Target States Driven Directed Fuzzing

SDFuzz: Target States Driven Directed Fuzzing Penghui Li, The Chinese University of Hong Kong and Zhongguancun Laboratory; ...

USENIX Security '24 - DPAdapter: Improving Differentially Private Deep Learning through Noise...

USENIX Security '24 - DPAdapter: Improving Differentially Private Deep Learning through Noise...

DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training Zihao Wang, Rui Zhu, and ...

USENIX Security '24 - Inference of Error Specifications and Bug Detection Using Structural...

USENIX Security '24 - Inference of Error Specifications and Bug Detection Using Structural...

Inference

USENIX Security '18 - AttriGuard: A Practical Defense Against Attribute Inference Attacks...

USENIX Security '18 - AttriGuard: A Practical Defense Against Attribute Inference Attacks...

AttriGuard: A Practical Defense

USENIX Security '22 - Minefield: A Software-only Protection for SGX Enclaves against DVFS Attacks

USENIX Security '22 - Minefield: A Software-only Protection for SGX Enclaves against DVFS Attacks

USENIX Security

USENIX Security '23 - Generative Intrusion Detection and Prevention on Data Stream

USENIX Security '23 - Generative Intrusion Detection and Prevention on Data Stream

USENIX Security

USENIX Security '18 - AttriGuard: A Practical Defense Against Attribute Inference Attacks...

USENIX Security '18 - AttriGuard: A Practical Defense Against Attribute Inference Attacks...

AttriGuard: A Practical Defense

USENIX Security '22 - Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference

USENIX Security '22 - Cheetah: Lean and Fast Secure Two-Party Deep Neural Network Inference

USENIX Security

USENIX Security '22 - Pool Inference Attacks on Local Differential Privacy...

USENIX Security '22 - Pool Inference Attacks on Local Differential Privacy...

USENIX Security

USENIX Security '22 - Poisoning Attacks to Local Differential Privacy Protocols for Key-Value Data

USENIX Security '22 - Poisoning Attacks to Local Differential Privacy Protocols for Key-Value Data

USENIX Security

USENIX Security '24 - Inf2Guard: An Information-Theoretic Framework for Learning...

USENIX Security '24 - Inf2Guard: An Information-Theoretic Framework for Learning...

Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations