World's Best Scientists 2026 revealed!
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Rising Stars
2025

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Rising Stars

D-Index
49
Citations
12904
World Ranking
338
National Ranking
20

Computer Science

D-Index
55
Citations
16361
World Ranking
4220
National Ranking
124

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Nour Moustafa is affiliated with the University of New South Wales in Australia and specializes in computer science, with a focus on artificial intelligence, computer networks and communications, and information systems. Their research encompasses a range of subfields including signal processing and control and systems engineering.

The scientist's work emphasizes topics such as network security and intrusion detection, anomaly detection techniques and applications, advanced malware detection techniques, privacy-preserving technologies in data, smart grid security and resilience, IoT and edge/fog computing, and blockchain technology applications and security.

Notable recent publications include:

  • "TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems," 2020, IEEE Access
  • "A new distributed architecture for evaluating AI-based security systems at the edge: Network TON_IoT datasets," 2021, Sustainable Cities and Society
  • "A Deep Blockchain Framework-Enabled Collaborative Intrusion Detection for Protecting IoT and Cloud Networks," 2020, IEEE Internet of Things Journal
  • "A Review of Intrusion Detection Systems Using Machine and Deep Learning in Internet of Things: Challenges, Solutions and Future Directions," 2020, Electronics
  • "ToN_IoT: The Role of Heterogeneity and the Need for Standardization of Features and Attack Types in IoT Network Intrusion Data Sets," 2021, IEEE Internet of Things Journal

Frequent co-authors in their research include Benjamin Turnbull, Mohamed Abdel-Basset, Hossam Hawash, Nickolaos Koroniotis, and Zahir Tari, reflecting collaboration across multiple projects.

Moustafa has contributed extensively to publication venues such as arXiv (Cornell University), IEEE Transactions on Intelligent Transportation Systems, IEEE Access, IEEE Internet of Things Journal, and IEEE Transactions on Industrial Informatics.

In addition to journal articles, Nour Moustafa has published books through Springer Nature, including Explainable Artificial Intelligence for Cyber Security (2022) and Deep Learning Techniques for IoT Security and Privacy (2021).

Best Publications

  • UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)

    Nour Moustafa;Jill Slay

  • Towards the development of realistic botnet dataset in the Internet of Things for network forensic analytics: Bot-IoT dataset

    Nickolaos Koroniotis;Nour Moustafa;Elena Sitnikova;Benjamin P. Turnbull

  • The evaluation of Network Anomaly Detection Systems: Statistical analysis of the UNSW-NB15 data set and the comparison with the KDD99 data set

    Nour Moustafa;Jill Slay

  • TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems

    Abdullah Alsaedi;Nour Moustafa;Zahir Tari;Abdun Naser Mahmood

  • An Ensemble Intrusion Detection Technique Based on Proposed Statistical Flow Features for Protecting Network Traffic of Internet of Things

    Nour Moustafa;Benjamin Turnbull;Kim-Kwang Raymond Choo

  • A new distributed architecture for evaluating AI-based security systems at the edge: Network TON_IoT datasets

    Nour Moustafa

  • A Deep Blockchain Framework-Enabled Collaborative Intrusion Detection for Protecting IoT and Cloud Networks

    Osama Alkadi;Nour Moustafa;Benjamin Turnbull;Kim-Kwang Raymond Choo

  • ToN_IoT: The Role of Heterogeneity and the Need for Standardization of Features and Attack Types in IoT Network Intrusion Datasets

    Tim M. Booij;Irina Chiscop;Erik Meeuwissen;Nour Moustafa

  • Identification of malicious activities in industrial internet of things based on deep learning models

    Muna AL-Hawawreh;Nour Moustafa;Elena Sitnikova

  • NetFlow Datasets for Machine Learning-based Network Intrusion Detection Systems

    Mohanad Sarhan;Siamak Layeghy;Nour Moustafa;Marius Portmann

  • Blockchain-Based Federated Learning for Securing Internet of Things: A Comprehensive Survey

    Unknown

  • A Review of Intrusion Detection Systems Using Machine and Deep Learning in Internet of Things: Challenges, Solutions and Future Directions

    Javed Asharf;Nour Moustafa;Hasnat Khurshid;Essam Debie

  • Novel Geometric Area Analysis Technique for Anomaly Detection Using Trapezoidal Area Estimation on Large-Scale Networks

    Nour Moustafa;Jill Slay;Gideon Creech

  • A holistic review of Network Anomaly Detection Systems: A comprehensive survey

    Nour Moustafa;Jiankun Hu;Jill Slay

  • Novel Deep Learning-Enabled LSTM Autoencoder Architecture for Discovering Anomalous Events From Intelligent Transportation Systems

    Javed Ashraf;Asim D. Bakhshi;Nour Moustafa;Hasnat Khurshid

  • The Significant Features of the UNSW-NB15 and the KDD99 Data Sets for Network Intrusion Detection Systems

    Nour Moustafa;Jill Slay

  • A new network forensic framework based on deep learning for Internet of Things networks: A particle deep framework

    Nickolaos Koroniotis;Nour Moustafa;Elena Sitnikova

  • Big Data Analytics for Intrusion Detection System: Statistical Decision-Making Using Finite Dirichlet Mixture Models

    Nour Moustafa;Gideon Creech;Jill Slay

  • Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions

    Unknown

  • NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems

    Mohanad Sarhan;Siamak Layeghy;Nour Moustafa;Marius Portmann

  • An explainable deep learning-enabled intrusion detection framework in IoT networks

    Unknown

  • A Privacy-Preserving-Framework-Based Blockchain and Deep Learning for Protecting Smart Power Networks

    Marwa Keshk;Benjamin Turnbull;Nour Moustafa;Dinusha Vatsalan

  • Towards Developing Network Forensic Mechanism for Botnet Activities in the IoT Based on Machine Learning Techniques

    Nickolaos Koroniotis;Nour Moustafa;Elena Sitnikova;Jill Slay

  • A New Threat Intelligence Scheme for Safeguarding Industry 4.0 Systems

    Nour Moustafa;Erwin Adi;Benjamin Turnbull;Jiankun Hu

Frequent Co-Authors

Kim-Kwang Raymond Choo
Kim-Kwang Raymond Choo The University of Texas at San Antonio
Jiankun Hu
Jiankun Hu University of New South Wales
Ibrahim Khalil
Ibrahim Khalil RMIT University
Alireza Jolfaei
Alireza Jolfaei Flinders University
Ali Kashif Bashir
Ali Kashif Bashir Manchester Metropolitan University
Seyit Camtepe
Seyit Camtepe Commonwealth Scientific and Industrial Research Organisation
Zahir Tari
Zahir Tari RMIT University
Monica T. Whitty
Monica T. Whitty Monash University
Shahid Mumtaz
Shahid Mumtaz Nottingham Trent University
Sahil Garg
Sahil Garg Canadian University Dubai

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