| Towards the development of realistic botnet dataset in the internet of things for network forensic analytics: Bot-iot dataset N Koroniotis, N Moustafa, E Sitnikova, B Turnbull Future Generation Computer Systems 100, 779-796, 2019 | 1634 | 2019 |
| An ensemble intrusion detection technique based on proposed statistical flow features for protecting network traffic of internet of things N Moustafa, B Turnbull, KKR Choo IEEE Internet of Things Journal 6 (3), 4815-4830, 2018 | 580 | 2018 |
| A deep blockchain framework-enabled collaborative intrusion detection for protecting IoT and cloud networks O Alkadi, N Moustafa, B Turnbull, KKR Choo IEEE Internet of Things Journal 8 (12), 9463-9472, 2020 | 410 | 2020 |
| Generating realistic intrusion detection system dataset based on fuzzy qualitative modeling W Haider, J Hu, J Slay, BP Turnbull, Y Xie Journal of Network and Computer Applications 87, 185-192, 2017 | 231 | 2017 |
| Blockchain-based federated learning for securing internet of things: A comprehensive survey W Issa, N Moustafa, B Turnbull, N Sohrabi, Z Tari ACM Computing Surveys 55 (9), 1-43, 2023 | 215 | 2023 |
| Supply chain 4.0: A survey of cyber security challenges, solutions and future directions T Sobb, B Turnbull, N Moustafa Electronics 9 (11), 1864, 2020 | 205 | 2020 |
| A new threat intelligence scheme for safeguarding industry 4.0 systems N Moustafa, E Adi, B Turnbull, J Hu IEEE Access 6, 32910-32924, 2018 | 184 | 2018 |
| A privacy-preserving-framework-based blockchain and deep learning for protecting smart power networks M Keshk, B Turnbull, N Moustafa, D Vatsalan, KKR Choo IEEE Transactions on Industrial Informatics 16 (8), 5110-5118, 2019 | 179 | 2019 |
| A review of intrusion detection and blockchain applications in the cloud: approaches, challenges and solutions O Alkadi, N Moustafa, B Turnbull IEEE Access 8, 104893-104917, 2020 | 101 | 2020 |
| An explainable deep learning-enabled intrusion detection framework in IoT networks M Keshk, N Koroniotis, N Pham, N Moustafa, B Turnbull, AY Zomaya Information Sciences 639, 119000, 2023 | 96 | 2023 |
| Robustness evaluations of sustainable machine learning models against data poisoning attacks in the internet of things C Dunn, N Moustafa, B Turnbull Sustainability 12 (16), 6434, 2020 | 66 | 2020 |
| Digital evidence on mobile devices E Casey, B Turnbull Digital Evidence and Computer Crime 3, 1-44, 2011 | 65 | 2011 |
| Automated event and social network extraction from digital evidence sources with ontological mapping B Turnbull, S Randhawa Digital Investigation 13, 94-106, 2015 | 59 | 2015 |
| Privacy-preserving big data analytics for cyber-physical systems M Keshk, N Moustafa, E Sitnikova, B Turnbull Wireless Networks 28 (3), 1241-1249, 2022 | 56 | 2022 |
| A survey on privacy-preserving blockchain systems (PPBS) and a novel PPBS-based framework for smart agriculture QN Tran, BP Turnbull, HT Wu, AJS De Silva, K Kormusheva, J Hu IEEE Open Journal of the Computer Society 2, 72-84, 2021 | 50 | 2021 |
| A blockchain-enabled explainable federated learning for securing internet-of-things-based social media 3.0 networks S Salim, B Turnbull, N Moustafa IEEE Transactions on Computational Social Systems, 2021 | 48 | 2021 |
| Privacy-preserving schemes for safeguarding heterogeneous data sources in cyber-physical systems M Keshk, B Turnbull, E Sitnikova, D Vatsalan, N Moustafa IEEE Access 9, 55077-55097, 2021 | 46 | 2021 |
| OQFL: An optimized quantum-based federated learning framework for defending against adversarial attacks in intelligent transportation systems W Yamany, N Moustafa, B Turnbull IEEE Transactions on Intelligent Transportation Systems 24 (1), 893-903, 2021 | 45 | 2021 |
| Biometrics and privacy-preservation: How do they evolve? QN Tran, BP Turnbull, J Hu IEEE Open Journal of the Computer Society 2, 179-191, 2021 | 41 | 2021 |
| The cyber conceptual framework for developing military doctrine D Ormrod, B Turnbull Defence Studies 16 (3), 270-298, 2016 | 37 | 2016 |
Dr Nour MoustafaUniversity of New South Wales (UNSW Canberra)Verified email at ieee.org