| A taxonomy and survey of attacks against machine learning N Pitropakis, E Panaousis, T Giannetsos, E Anastasiadis, G Loukas Computer Science Review 34, 100199, 2019 | 317 | 2019 |
| Hiding in plain sight: A longitudinal study of combosquatting abuse P Kintis, N Miramirkhani, C Lever, Y Chen, R Romero-Gómez, ... Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017 | 186 | 2017 |
| A privacy-preserving healthcare framework using hyperledger fabric C Stamatellis, P Papadopoulos, N Pitropakis, S Katsikas, WJ Buchanan Sensors 20 (22), 6587, 2020 | 132 | 2020 |
| A deep learning-based intrusion detection system for MQTT enabled IoT MA Khan, MA Khan, SU Jan, J Ahmad, SS Jamal, AA Shah, N Pitropakis, ... Sensors 21 (21), 7016, 2021 | 122 | 2021 |
| HDL-IDS: a hybrid deep learning architecture for intrusion detection in the Internet of Vehicles S Ullah, MA Khan, J Ahmad, SS Jamal, Z e Huma, MT Hassan, ... Sensors 22 (4), 1340, 2022 | 93 | 2022 |
| Cloud computing security: foundations and challenges JR Vacca CRC press, 2016 | 84 | 2016 |
| A new intrusion detection system for the internet of things via deep convolutional neural network and feature engineering S Ullah, J Ahmad, MA Khan, EH Alkhammash, M Hadjouni, YY Ghadi, ... Sensors 22 (10), 3607, 2022 | 68 | 2022 |
| Towards lightweight url-based phishing detection A Butnaru, A Mylonas, N Pitropakis Future internet 13 (6), 154, 2021 | 64 | 2021 |
| A comparative analysis of honeypots on different cloud platforms C Kelly, N Pitropakis, A Mylonas, S McKeown, WJ Buchanan Sensors 21 (7), 2433, 2021 | 63 | 2021 |
| Launching adversarial attacks against network intrusion detection systems for iot P Papadopoulos, O Thornewill von Essen, N Pitropakis, C Chrysoulas, ... Journal of Cybersecurity and Privacy 1 (2), 252-273, 2021 | 56 | 2021 |
| Explainable AI-based DDOS attack identification method for IoT networks CS Kalutharage, X Liu, C Chrysoulas, N Pitropakis, P Papadopoulos Computers 12 (2), 32, 2023 | 52 | 2023 |
| Privacy and trust redefined in federated machine learning P Papadopoulos, W Abramson, AJ Hall, N Pitropakis, WJ Buchanan Machine Learning and Knowledge Extraction 3 (2), 333-356, 2021 | 50 | 2021 |
| DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things J Ahmad, SA Shah, S Latif, F Ahmed, Z Zou, N Pitropakis Journal of King Saud University-Computer and Information Sciences 34 (10 …, 2022 | 48 | 2022 |
| Testing and hardening IOT devices against the Mirai botnet C Kelly, N Pitropakis, S McKeown, C Lambrinoudakis 2020 international conference on cyber security and protection of digital …, 2020 | 41 | 2020 |
| An enhanced cyber attack attribution framework N Pitropakis, E Panaousis, A Giannakoulias, G Kalpakis, RD Rodriguez, ... Trust, Privacy and Security in Digital Business: 15th International …, 2018 | 37 | 2018 |
| Ransomware: Analysing the impact on Windows active directory domain services G McDonald, P Papadopoulos, N Pitropakis, J Ahmad, WJ Buchanan Sensors 22 (3), 953, 2022 | 36 | 2022 |
| Predicting malicious insider threat scenarios using organizational data and a heterogeneous stack-classifier AJ Hall, N Pitropakis, WJ Buchanan, N Moradpoor 2018 IEEE International Conference on Big Data (Big Data), 5034-5039, 2018 | 35 | 2018 |
| A distributed trust framework for privacy-preserving machine learning W Abramson, AJ Hall, P Papadopoulos, N Pitropakis, WJ Buchanan Trust, Privacy and Security in Digital Business: 17th International …, 2020 | 33 | 2020 |
| Using social media & sentiment analysis to make investment decisions B Hasselgren, C Chrysoulas, N Pitropakis, WJ Buchanan Future Internet 15 (1), 5, 2022 | 31 | 2022 |
| Monitoring users’ behavior: anti-immigration speech detection on twitter N Pitropakis, K Kokot, D Gkatzia, R Ludwiniak, A Mylonas, M Kandias Machine Learning and Knowledge Extraction 2 (3), 11, 2020 | 30 | 2020 |
Bill BuchananEdinburgh Napier UniversityAdresse e-mail validée de napier.ac.uk
