5 citations · 10 across the 4 of their papers we have counts for
5 papers
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better
Bojia Zi, Shihao Zhao, Xingjun Ma +1
Adversarial training is one effective approach for training robust deep neural networks against adversarial attacks. While being able to bring reliable robustness, adversarial trai…
Sub-trajectory Similarity Join with Obfuscation
Yanchuan Chang, Jianzhong Qi, Egemen Tanin +2
User trajectory data is becoming increasingly accessible due to the prevalence of GPS-equipped devices such as smartphones. Many existing studies focus on querying trajectories tha…
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting
Ang Li, Qiuhong Ke, Xingjun Ma +4
Deep image inpainting aims to restore damaged or missing regions in an image with realistic contents. While having a wide range of applications such as object removal and image rec…
Dual Head Adversarial Training
Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani +1
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples/attacks, raising concerns about their reliability in safety-critical applications. A number of defens…
Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data
R G Gayathri, Atul Sajjanhar, Yong Xiang +1
Insider threats are the cyber attacks from within the trusted entities of an organization. Lack of real-world data and issue of data imbalance leave insider threat analysis an unde…