| Early-stage malware prediction using recurrent neural networks M Rhode, P Burnap, K Jones computers & security 77, 578-594, 2018 | 326 | 2018 |
| Adversarial attacks on machine learning cybersecurity defences in industrial control systems E Anthi, L Williams, M Rhode, P Burnap, A Wedgbury Journal of Information Security and Applications 58, 102717, 2021 | 199 | 2021 |
| Lab to soc: robust features for dynamic malware detection M Rhode, L Tuson, P Burnap, K Jones 2019 49th annual IEEE/IFIP international conference on dependable systems …, 2019 | 28 | 2019 |
| Real‐Time Malware Process Detection and Automated Process Killing M Rhode, P Burnap, A Wedgbury Security and Communication Networks 2021 (1), 8933681, 2021 | 18 | 2021 |
| Vulnerability Forecasting: theory and practice É Leverett, M Rhode, A Wedgbury Digital Threats: Research and Practice 3 (4), 1-27, 2022 | 10 | 2022 |
| Waste not: using diverse neural networks from hyperparameter search for improved malware detection P Marques, M Rhode, I Gashi Computers & Security 108, 102339, 2021 | 10 | 2021 |
| Racing demons: Malware detection in early execution M Rhode Cardiff University, 2021 | 2 | 2021 |
| Dual-task agent for run-time classification and killing of malicious processes. M Rhode, P Burnap, K Jones CoRR, 2019 | | 2019 |
| Data Capture & Analysis to Assess Impact of Carbon Credit Schemes M Rhode, O Rana, T Edwards arXiv preprint arXiv:1711.07574, 2017 | | 2017 |
| AI for Security Topic Guide Issue.. M Rhode | | |
| Yang, Wei 1 Yasa, Giridhar Appaji Nag 25 Zeng, Qinsong 1 Zhang, Changrong W Zheng, P Burnap, HB Chen, J Chromik, P Coulthard, Y Deng, S Fu, ... | | |
