| Software vulnerability detection using deep neural networks: a survey G Lin, S Wen, QL Han, J Zhang, Y Xiang Proceedings of the IEEE 108 (10), 1825-1848, 2020 | 413 | 2020 |
| Cross-project transfer representation learning for vulnerable function discovery G Lin, J Zhang, W Luo, L Pan, Y Xiang, O De Vel, P Montague IEEE Transactions on Industrial Informatics 14 (7), 3289-3297, 2018 | 221 | 2018 |
| POSTER: Vulnerability discovery with function representation learning from unlabeled projects G Lin, J Zhang, W Luo, L Pan, Y Xiang Proceedings of the 2017 ACM SIGSAC conference on computer and communications …, 2017 | 159 | 2017 |
| DeepBalance: Deep-learning and fuzzy oversampling for vulnerability detection S Liu, G Lin, QL Han, S Wen, J Zhang, Y Xiang IEEE Transactions on Fuzzy Systems 28 (7), 1329-1343, 2019 | 111 | 2019 |
| Software vulnerability discovery via learning multi-domain knowledge bases G Lin, J Zhang, W Luo, L Pan, O De Vel, P Montague, Y Xiang IEEE Transactions on Dependable and Secure Computing 18 (5), 2469-2485, 2019 | 107 | 2019 |
| Cyber resilience in healthcare digital twin on lung cancer J Zhang, L Li, G Lin, D Fang, Y Tai, J Huang IEEE access 8, 201900-201913, 2020 | 102 | 2020 |
| Deep learning-based vulnerable function detection: A benchmark G Lin, W Xiao, J Zhang, Y Xiang Information and Communications Security: 21st International Conference …, 2020 | 85 | 2020 |
| CD-VulD: Cross-domain vulnerability discovery based on deep domain adaptation S Liu, G Lin, L Qu, J Zhang, O De Vel, P Montague, Y Xiang IEEE Transactions on Dependable and Secure Computing 19 (1), 438-451, 2020 | 73 | 2020 |
| Software vulnerability analysis and discovery using deep learning techniques: A survey P Zeng, G Lin, L Pan, Y Tai, J Zhang IEEE Access 8, 197158-197172, 2020 | 67 | 2020 |
| Near real-time twitter spam detection with machine learning techniques N Sun, G Lin, J Qiu, P Rimba International Journal of Computers and Applications 44 (4), 338-348, 2022 | 66 | 2022 |
| Statistical twitter spam detection demystified: performance, stability and scalability G Lin, N Sun, S Nepal, J Zhang, Y Xiang, H Hassan IEEE access 5, 11142-11154, 2017 | 52 | 2017 |
| Deep neural embedding for software vulnerability discovery: Comparison and optimization X Yuan, G Lin, Y Tai, J Zhang Security and Communication Networks 2022 (1), 5203217, 2022 | 33 | 2022 |
| Deep neural-based vulnerability discovery demystified: data, model and performance G Lin, W Xiao, LY Zhang, S Gao, Y Tai, J Zhang Neural Computing and Applications 33 (20), 13287-13300, 2021 | 18 | 2021 |
| Detecting vulnerabilities in IoT software: New hybrid model and comprehensive data analysis H Mei, G Lin, D Fang, J Zhang Journal of Information Security and Applications 74, 103467, 2023 | 11 | 2023 |
| The application of neural network for software vulnerability detection: a review Y Zhu, G Lin, L Song, J Zhang Neural Computing and Applications 35 (2), 1279-1301, 2023 | 9 | 2023 |
| A context-aware neural embedding for function-level vulnerability detection H Wei, G Lin, L Li, H Jia Algorithms 14 (11), 335, 2021 | 9 | 2021 |
| Senior Member, Houcine Hassan,“Statistical Twitter Spam Detection Demystified: Performance, Stability and Scalability” G Lin, SN Sun, J Zhang, Y Xiang IEEE TRANSACTIONS–2017, 2017 | 8 | 2017 |
| Neural model stealing attack to smart mobile device on intelligent medical platform L Zhang, G Lin, B Gao, Z Qin, Y Tai, J Zhang Wireless Communications and Mobile Computing 2020 (1), 8859489, 2020 | 7 | 2020 |
| Intelligent detection of vulnerable functions in software through neural embedding‐based code analysis P Zeng, G Lin, J Zhang, Y Zhang International Journal of Network Management 33 (3), e2198, 2023 | 4 | 2023 |
| Boosting aquila optimizer by marine predators algorithm for combinatorial optimization S Wang, H Jia, AG Hussien, L Abualigah, G Lin, H Wei, Z Lin, KG Dhal Journal of Computational Design and Engineering 11 (2), 37-69, 2024 | 3 | 2024 |
Jun ZhangProfessor, Swinburne University of TechnologyZweryfikowany adres z swin.edu.au
