| Multi-level anomaly detection in industrial control systems via package signatures and LSTM networks C Feng, T Li, D Chana 47th Annual IEEE/IFIP International Conference on Dependable Systems and …, 2017 | 232 | 2017 |
| A Systematic Framework to Generate Invariants for Anomaly Detection in Industrial Control Systems C Feng, VR Palleti, A Mathur, D Chana 26th Annual Network and Distributed System Security Symposium (NDSS 2019), 2019 | 112 | 2019 |
| Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering C Feng, P Tian Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 56 | 2021 |
| PALOMA: A process algebra for located markovian agents C Feng, J Hillston International Conference on Quantitative Evaluation of Systems, 265-280, 2014 | 56 | 2014 |
| A deep learning-based framework for conducting stealthy attacks in industrial control systems C Feng, T Li, Z Zhu, D Chana arXiv preprint arXiv:1709.06397, 2017 | 46 | 2017 |
| Automatic moment-closure approximation of spatially distributed collective adaptive systems C Feng, J Hillston, V Galpin ACM Transactions on Modeling and Computer Simulation (TOMACS) 26 (4), 1-22, 2016 | 25 | 2016 |
| A preliminary investigation of capturing spatial information for CAS V Galpin, L Bortolussi, V Ciancia, A Clark, R De Nicola, C Feng, S Gilmore, ... QUANTICOL Deliverable D 2 (1), 110, 2014 | 25* | 2014 |
| Availability Modeling of Generalized -Out-of- :G Warm Standby Systems With PEPA X Wu, J Hillston, C Feng IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (12), 3177-3188, 2016 | 21 | 2016 |
| Moment-based availability prediction for bike-sharing systems C Feng, J Hillston, D Reijsbergen Performance Evaluation 117, 58-74, 2017 | 19 | 2017 |
| Moment-based probabilistic prediction of bike availability for bike-sharing systems C Feng, J Hillston, D Reijsbergen International Conference on Quantitative Evaluation of Systems, 139-155, 2016 | 18 | 2016 |
| StackVAE-G: An efficient and interpretable model for time series anomaly detection W Li, W Hu, T Chen, N Chen, C Feng AI Open 3, 101-110, 2022 | 13 | 2022 |
| Scalable Approach to Enhancing ICS Resilience by Network Diversity T Li, C Feng, C Hankin 50th Annual IEEE/IFIP International Conference on Dependable Systems and …, 2020 | 12* | 2020 |
| Patch-based hybrid modelling of spatially distributed systems by using stochastic HYPE-ZebraNet as an example C Feng Proceedings of the 14th Workshop on Quantitative Aspects of Programming …, 2014 | 11 | 2014 |
| Accelerating simulation of Population Continuous Time Markov Chains via automatic model reduction C Feng, J Hillston Performance Evaluation 120, 20-35, 2018 | 7* | 2018 |
| Modelling Opportunistic Netowrks with HYPE C Feng University of Edinburgh, 2012 | 6 | 2012 |
| Performance analysis of collective adaptive behaviour in time and space C Feng, M Gribaudo, J Hillston Electronic Notes in Theoretical Computer Science 318, 53-68, 2015 | 5 | 2015 |
| Review of time-based techniques for modelling space V Galpin, C Feng, J Hillston, M Massink, M Tribastone, M Tschaikowski QUANTICOL, Tech. Rep. TR-QC-05–2014, 2014 | 5* | 2014 |
| Nonlinear Hawkes processes in time-varying system F Zhou, Q Kong, Y Zhang, C Feng, J Zhu arXiv preprint arXiv:2106.04844, 2021 | 4 | 2021 |
| RelSen: An Optimization-based Framework for Simultaneous Sensor Reliability Monitoring and Data Cleaning C Feng, X Liang, D Schneegass, PW Tian Proceedings of the 29th ACM International Conference on Information and …, 2020 | 4 | 2020 |
| Efficient inference for dynamic flexible interactions of neural populations F Zhou, Q Kong, Z Deng, J Kan, Y Zhang, C Feng, J Zhu Journal of Machine Learning Research, 2022 | 3 | 2022 |
Jane HillstonProfessor of Quantitative Modelling, University of EdinburghVerified email at ed.ac.uk
