Papers Neural Network Security
“Neural Network Security” 태그가 달린 논문 8편 · 필터 해제
Keyed Chaotic Dynamics for Privacy-Preserving Neural Inference
Neural network inference typically operates on raw input data, increasing the risk of exposure during preprocessing and inference. Moreover, neural architectures lack efficient built-in mechanisms for directly authentica…
Graph SamplingNeural Network SecurityPrivacy PreservingVerification of Bit-Flip Attacks against Quantized Neural Networks
In the rapidly evolving landscape of neural network security, the resilience of neural networks against bit-flip attacks (i.e., an attacker maliciously flips an extremely small amount of bits within its parameter storage…
Neural Network SecurityQuantizationAdversarial Infrared Curves: An Attack on Infrared Pedestrian Detectors in the Physical World
Deep neural network security is a persistent concern, with considerable research on visible light physical attacks but limited exploration in the infrared domain. Existing approaches, like white-box infrared attacks usin…
Adversarial DefenseNeural Network SecurityVPN: Verification of Poisoning in Neural Networks
Neural networks are successfully used in a variety of applications, many of them having safety and security concerns. As a result researchers have proposed formal verification techniques for verifying neural network prop…
Data Poisoningimage-classificationImage ClassificationNeural Network SecuritySemi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis
Model poisoning attacks on federated learning (FL) intrude in the entire system via compromising an edge model, resulting in malfunctioning of machine learning models. Such compromised models are tampered with to perform…
Backdoor AttackFederated Learningimage-classificationImage Classification+2Just Noticeable Difference for Deep Machine Vision
As an important perceptual characteristic of the Human Visual System (HVS), the Just Noticeable Difference (JND) has been studied for decades with image and video processing (e.g., perceptual visual signal compression). …
image-classificationImage ClassificationNeural Network SecurityVideo CompressionHacking Neural Networks: A Short Introduction
A large chunk of research on the security issues of neural networks is focused on adversarial attacks. However, there exists a vast sea of simpler attacks one can perform both against and with neural networks. In this ar…
Deep LearningGPUNeural Network SecurityHardware Trojan Attacks on Neural Networks
With the rising popularity of machine learning and the ever increasing demand for computational power, there is a growing need for hardware optimized implementations of neural networks and other machine learning models. …
BIG-bench Machine LearningNeural Network Security