| Phishing email detection using improved RCNN model with multilevel vectors and attention mechanism Y Fang, C Zhang, C Huang, L Liu, Y Yang Ieee Access 7, 56329-56340, 2019 | 180 | 2019 |
| DeepXSS: Cross site scripting detection based on deep learning Y Fang, Y Li, L Liu, C Huang Proceedings of the 2018 international conference on computing and artificial …, 2018 | 112 | 2018 |
| Indoor positioning based on Bluetooth low-energy beacons adopting graph optimization Z Zuo, L Liu, L Zhang, Y Fang Sensors 18 (11), 3736, 2018 | 84 | 2018 |
| FastEmbed: Predicting vulnerability exploitation possibility based on ensemble machine learning algorithm Y Fang, Y Liu, C Huang, L Liu Plos one 15 (2), e0228439, 2020 | 82 | 2020 |
| Classification of ultra-high resolution orthophotos combined with DSM using a dual morphological top hat profile Q Zhang, R Qin, X Huang, Y Fang, L Liu Remote Sensing 7 (12), 16422-16440, 2015 | 76 | 2015 |
| Android malware familial classification based on dex file section features Y Fang, Y Gao, FAN Jing, LEI Zhang IEEE Access 8, 10614-10627, 2020 | 70 | 2020 |
| Self multi-head attention-based convolutional neural networks for fake news detection Y Fang, J Gao, C Huang, H Peng, R Wu PloS one 14 (9), e0222713, 2019 | 66 | 2019 |
| Webshell detection based on random forest–gradient boosting decision tree algorithm H Cui, D Huang, Y Fang, L Liu, C Huang 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC …, 2018 | 63 | 2018 |
| Cyberbullying detection in social networks using bi-gru with self-attention mechanism Y Fang, S Yang, B Zhao, C Huang Information 12 (4), 171, 2021 | 62 | 2021 |
| A machine learning based framework for identifying influential nodes in complex networks G Zhao, P Jia, C Huang, A Zhou, Y Fang IEEE Access 8, 65462-65471, 2020 | 61 | 2020 |
| Credit card fraud detection based on machine learning Y Fang, Y Zhang, C Huang Proceedings of the 2024 2nd International Conference on Image, Algorithms …, 2024 | 53 | 2024 |
| DeepDetectNet vs RLAttackNet: An adversarial method to improve deep learning-based static malware detection model Y Fang, Y Zeng, B Li, L Liu, L Zhang Plos one 15 (4), e0231626, 2020 | 48 | 2020 |
| WOVSQLI: Detection of SQL injection behaviors using word vector and LSTM Y Fang, J Peng, L Liu, C Huang Proceedings of the 2nd international conference on cryptography, security …, 2018 | 48 | 2018 |
| Detecting malicious JavaScript code based on semantic analysis Y Fang, C Huang, Y Su, Y Qiu Computers & Security 93, 101764, 2020 | 47 | 2020 |
| Research on malicious JavaScript detection technology based on LSTM Y Fang, C Huang, L Liu, M Xue IEEE Access 6, 59118-59125, 2018 | 46 | 2018 |
| GraphXSS: an efficient XSS payload detection approach based on graph convolutional network Z Liu, Y Fang, C Huang, J Han Computers & Security 114, 102597, 2022 | 45 | 2022 |
| TAP: A static analysis model for PHP vulnerabilities based on token and deep learning technology Y Fang, S Han, C Huang, R Wu PloS one 14 (11), e0225196, 2019 | 43 | 2019 |
| Detecting webshell based on random forest with fasttext Y Fang, Y Qiu, L Liu, C Huang Proceedings of the 2018 International Conference on Computing and Artificial …, 2018 | 42 | 2018 |
| A study on Web security incidents in China by analyzing vulnerability disclosure platforms C Huang, JY Liu, Y Fang, Z Zuo Computers & Security 58, 47-62, 2016 | 41 | 2016 |
| RLXSS: Optimizing XSS detection model to defend against adversarial attacks based on reinforcement learning Y Fang, C Huang, Y Xu, Y Li Future Internet 11 (8), 177, 2019 | 36 | 2019 |
Yijia XuSichuan Universityכתובת אימייל מאומתת בדומיין scu.edu.cn