SoK: Comparing Different Membership Inference Attacks with a Comprehensive Benchmark

1 code implementation • 12 Jul 2023 • Jun Niu, Xiaoyan Zhu, Moxuan Zeng, Ge Zhang, Qingyang Zhao, Chunhui Huang, Yangming Zhang, Suyu An, Yangzhong Wang, Xinghui Yue, Zhipeng He, Weihao Guo, Kuo Shen, Peng Liu, Yulong Shen, Xiaohong Jiang, Jianfeng Ma, Yuqing Zhang

We have identified three principles for the proposed "comparing different MI attacks" methodology, and we have designed and implemented the MIBench benchmark with 84 evaluation scenarios for each dataset.

BeamAttack: Generating High-quality Textual Adversarial Examples through Beam Search and Mixed Semantic Spaces

no code implementations • 9 Mar 2023 • Hai Zhu, Qingyang Zhao, Yuren Wu

These adversarial examples are imperceptible to human readers but can mislead models to make the wrong predictions.

Multimodal and Contrastive Learning for Click Fraud Detection

no code implementations • 8 May 2021 • Weibin Li, Qiwei Zhong, Qingyang Zhao, Hongchun Zhang, Xiaonan Meng

In this paper, we propose a Multimodal and Contrastive learning network for Click Fraud detection (MCCF).

Contrastive Learning Fraud Detection