no code implementations • 13 Jun 2023 • Bowen Li, Hanlin Gu, Ruoxin Chen, Jie Li, Chentao Wu, Na Ruan, Xueming Si, Lixin Fan
We investigate a Temporal Gradient Inversion Attack with a Robust Optimization framework, called TGIAs-RO, which recovers private data without any prior knowledge by leveraging multiple temporal gradients.
no code implementations • 27 Mar 2022 • Jikun Chen, Feng Qiang, Na Ruan
Then we present ARS, a collaborative learning framework wherein users share representations of data to train models, and add imperceptible adversarial noise to data representations against reconstruction or attribute extraction attacks.
1 code implementation • CVPR 2021 • Zekun Sun, Yujie Han, Zeyu Hua, Na Ruan, Weijia Jia
Moreover, our method has shown robustness in detecting highly compressed or noise corrupted videos.
no code implementations • 17 Sep 2020 • Chaohao Fu, Hongbin Chen, Na Ruan, Weijia Jia
We find that training model with label smoothing can easily achieve striking accuracy under most gradient-based attacks.
no code implementations • 5 Sep 2019 • Ruoyu Deng, Na Ruan
Based on the new paradigm, we design a novel fraud detection model, FraudJudger, to analyze users behaviors on digital payment platforms and detect fraud users with fewer labeled data in training.
no code implementations • 3 May 2019 • Wenmian Yang, Kun Wang, Na Ruan, Wenyuan Gao, Weijia Jia, Wei Zhao, Nan Liu, Yunyong Zhang
Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF).