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Senior Research Associate

Dr Nickolaos Koroniotis

UNSW Canberra
School of Engineering & IT
E-mail
n.koroniotis@unsw.edu.au
  • Journal articles | 2023
    2023, 'An explainable deep learning-enabled intrusion detection framework in IoT networks', Information Sciences, 639, pp. 119000 - 119000, http://dx.doi.org/10.1016/j.ins.2023.119000
    Journal articles | 2023
    2023, 'The SAir-IIoT Cyber Testbed as a Service: A Novel Cybertwins Architecture in IIoT-Based Smart Airports', IEEE Transactions on Intelligent Transportation Systems, 24, pp. 2368 - 2381, http://dx.doi.org/10.1109/TITS.2021.3106378
    Journal articles | 2022
    2022, 'A new Intelligent Satellite Deep Learning Network Forensic framework for smart satellite networks', Computers and Electrical Engineering, 99, pp. 107745 - 107745, http://dx.doi.org/10.1016/j.compeleceng.2022.107745
    Journal articles | 2020
    2020, 'A Holistic Review of Cybersecurity and Reliability Perspectives in Smart Airports', IEEE Access
    Journal articles | 2020
    2020, 'A New Network Forensic Framework based on Deep Learning for Internet of Things Networks: A Particle Deep Framework', Future Generation Computers Systems
    Journal articles | 2019
    2019, 'Forensics and Deep Learning Mechanisms for Botnets in Internet of Things: A Survey of Challenges and Solutions', IEEE Access, 7, pp. 61764 - 61785, http://dx.doi.org/10.1109/ACCESS.2019.2916717
    Journal articles | 2019
    2019, 'Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset', Future Generation Computer Systems
  • Conference Papers | 2023
    2023, 'Digital Forensics based on Federated Learning in IoT Environment', in ACM International Conference Proceeding Series, ACM, pp. 92 - 101, presented at ACSW 2023: 2023 Australasian Computer Science Week, http://dx.doi.org/10.1145/3579375.3579387
    Conference Papers | 2021
    2021, 'A Deep Learning-based Penetration Testing Framework for Vulnerability Identification in Internet of Things Environments', in Proceedings - 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2021, IEEE, pp. 887 - 894, presented at 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 20 October 2021 - 22 October 2021, http://dx.doi.org/10.1109/TrustCom53373.2021.00125
    Preprints | 2021
    2021, A Deep Learning-based Penetration Testing Framework for Vulnerability Identification in Internet of Things Environments, , http://dx.doi.org/10.48550/arxiv.2109.09259
    Conference Papers | 2020
    2020, 'Enhancing Network Forensics with Particle Swarm and Deep Learning: The Particle Deep Framework', Sydney, Australia, presented at 7th International Conference on Security and its Applications (CNSA 2020), Sydney, Australia, 28 March 2020 - 29 March 2020
    Preprints | 2020
    2020, Enhancing network forensics with particle swarm and deep learning: The particle deep framework, , http://dx.doi.org/10.48550/arxiv.2005.00722
    Preprints | 2018
    2018, Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset, , http://dx.doi.org/10.48550/arxiv.1811.00701
    Conference Papers | 2017
    Koroniotis N; Moustafa N; Sitnikova E; Slay J, 2017, 'Towards Developing Network forensic mechanism for Botnet Activities in the IoT based on Machine Learning Techniques', in Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer International Publishing, Melbourne, Australia, pp. 30 - 44, presented at 9th International Conference, MONAMI 2017, Melbourne, Australia, 13 December 2017 - 15 December 2017, http://dx.doi.org/10.1007/978-3-319-90775-8_3
    Preprints | 2017
    2017, Towards Developing Network forensic mechanism for Botnet Activities in the IoT based on Machine Learning Techniques, , http://dx.doi.org/10.48550/arxiv.1711.02825