3 citations · 3 across the 2 of their papers we have counts for
4 papers
Model-Reuse Attacks on Deep Learning Systems
Yujie Ji, Xinyang Zhang, Shouling Ji +2
Many of today's machine learning (ML) systems are built by reusing an array of, often pre-trained, primitive models, each fulfilling distinct functionality (e.g., feature extractio…
EagleEye: Attack-Agnostic Defense against Adversarial Inputs (Technical Report)
Yujie Ji, Xinyang Zhang, Ting Wang
Deep neural networks (DNNs) are inherently vulnerable to adversarial inputs: such maliciously crafted samples trigger DNNs to misbehave, leading to detrimental consequences for DNN…
Where Classification Fails, Interpretation Rises
Chanh Nguyen, Georgi Georgiev, Yujie Ji +1
An intriguing property of deep neural networks is their inherent vulnerability to adversarial inputs, which significantly hinders their application in security-critical domains. Mo…
Modular Learning Component Attacks: Today's Reality, Tomorrow's Challenge
Xinyang Zhang, Yujie Ji, Ting Wang
Many of today's machine learning (ML) systems are not built from scratch, but are compositions of an array of {\em modular learning components} (MLCs). The increasing use of MLCs s…