| Dlfuzz: Differential fuzzing testing of deep learning systems J Guo, Y Jiang, Y Zhao, Q Chen, J Sun Proceedings of the 2018 26th ACM Joint Meeting on European Software …, 2018 | 306 | 2018 |
| Leopard: Identifying vulnerable code for vulnerability assessment through program metrics X Du, B Chen, Y Li, J Guo, Y Zhou, Y Liu, Y Jiang 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 121 | 2019 |
| AdvDoor: Adversarial Backdoor Attack of Deep Learning System Q Zhang, Y Ding, Y Tian, J Guo, M Yuan, Y Jiang The ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2021 | 64 | 2021 |
| RNN-Test: Towards Adversarial Testing for Recurrent Neural Network Systems J Guo, Q Zhang, Y Zhao, H Shi, Y Jiang, J Sun IEEE Transactions of Software Engineering, 2021 | 34* | 2021 |
| Coverage guided differential adversarial testing of deep learning systems J Guo, Y Zhao, H Song, Y Jiang IEEE Transactions on Network Science and Engineering 8 (2), 933-942, 2020 | 29 | 2020 |
| Hdtest: Differential fuzz testing of brain-inspired hyperdimensional computing D Ma, J Guo, Y Jiang, X Jiao The 58th Design Automation Conference (DAC), 2021 | 27 | 2021 |
| Cube-evo: A query-efficient black-box attack on video classification system Y Zhan, Y Fu, L Huang, J Guo, H Shi, H Song, C Hu IEEE Transactions on Reliability, 2023 | 2 | 2023 |
