Dr Naeem Syed



Lecturer, Cyber Security


Faculty of Sci Eng & Built Env


School of Info Technology


Geelong Waurn Ponds Campus


Doctor of Philosophy, Edith Cowan University, 2020
Master of Science (Network Systems), King Fahd University, 2011


+61 3 924 68539

Research interests

  • Cyber threat modeling and detection
  • Design of machine learning-based intrusion detection systems
  • Security protocol analysis for the IoT
  • Cyber security risk assessments for the supply chain industry
  • Zero trust architectures
  • Secure coding practices including static and dynamic application security testing.
  • Reinforcement learning for cyber security.

Teaching interests

  • Secure programming/coding practices
  • Advanced network forensics
  • Computer forensics
  • Identity and access management
  • Network security


Filter by


Securing Industrial Control Systems (ICS) Through Attack Modelling and Rule-Based Learning

M Mehmood, Z Baig, N Syed

(2024), pp. 598-602, COMSNETS 2024 : Proceedings of the 16th International Conference on COMmunication Systems and NETworkS, Bengaluru, India, E1


Fog-cloud based intrusion detection system using Recurrent Neural Networks and feature selection for IoT networks

Naeem Syed, Mengmeng Ge, Zubair Baig

(2023), Vol. 225, pp. 1-14, Computer Networks, Amsterdam, The Netherlands, C1

journal article

DoS Attacks, Human Factors, and Evidence Extraction for the Industrial Internet of Things (IIoT) Paradigm

S Mekala, Z Baig, A Anwar, N Syed

(2023), pp. 32-39, Proceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2023, LUXEMBOURG, Echternach, E1


Traceability in Supply Chains: A Cyber Security Analysis

Naeem Syed, Syed Shah, Rolando Trujillo Rasua, Robin Doss

(2022), Vol. 112, Computers and Security, C1

journal article

Zero Trust Architecture (ZTA): A Comprehensive Survey

N Syed, S Shah, A Shaghaghi, A Anwar, Z Baig, R Doss

(2022), Vol. 10, pp. 57143-57179, IEEE Access, Piscataway, N.J., C1

journal article

Securing the Smart City Airspace: Drone Cyber Attack Detection through Machine Learning

Z Baig, N Syed, N Mohammad

(2022), Vol. 14, pp. 1-19, Future Internet, Basel, Switzerland, C1

journal article

Unsupervised Machine Learning for Drone Forensics through Flight Path Analysis

N Syed, M Khan, N Mohammad, G Brahim, Z Baig

(2022), ISDFS 2022 : International Symposium on Digital Forensics and Security 2022, Istanbul, Turkey, E1


Securing contemporary eHealth architectures: Techniques and methods

N Syed, Z Baig, A Anwar

(2021), pp. 207-234, Security and Privacy in the Internet of Things: Architectures, Techniques, and Applications, London, Eng., B1

book chapter

Towards a deep learning-driven intrusion detection approach for Internet of Things

M Ge, N Syed, X Fu, Z Baig, A Robles-Kelly

(2021), Vol. 186, Computer Networks, C1

journal article

LCDA: Lightweight Continuous Device-to-Device Authentication for a Zero Trust Architecture (ZTA)

S Shah, N Syed, A Shaghaghi, A Anwar, Z Baig, R Doss

(2021), Vol. 108, Computers and Security, C1

journal article

Averaged dependence estimators for DoS attack detection in IoT networks

Z Baig, S Sanguanpong, S Firdous, V Vo, T Nguyen, C So-In

(2020), Vol. 102, pp. 198-209, Future Generation Computer Systems, C1

journal article

Denial of service attack detection through machine learning for the IoT

Naeem Syed, Zubair Baig, Ahmed Ibrahim, Craig Valli

(2020), Vol. 4, pp. 482-503, Journal of information and telecommunication, Abingdon, Eng., C1

journal article

Towards a lightweight continuous authentication protocol for device-to-device communication

S Shah, N Syed, A Shaghaghi, A Anwar, Z Baig, R Doss

(2020), pp. 1119-1126, Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020, Guangzhou, China, E1


Bio-inspired cyber-security for the smart grid

Naeem Syed, Ahmed Ibrahim, Z Baig, Craig Valli

(2019), pp. 373-392, Nature-inspired cyber security and resiliency: fundamentals, techniques and applications, Stevenage, Eng., B1

book chapter

Deep learning-based intrusion detection for IoT networks

Mengmeng Ge, Xiping Fu, Naeem Syed, Zubair Baig, Gideon Teo, Antonio Robles-Kelly

(2019), pp. 256-265, PRDC 2019 : Proceedings of the 2019 IEEE 24th Pacific Rim International Symposium on Dependable Computing, Kyoto, Japan, E1



M Malik, I McAteer, P Hannay, S Firdous, Z Baig

(2018), pp. 62-73, ISM 2018 : Proceedings of the 16th Australian Information Security Management Conference, AISMC 2018, Perth, Western Australia, E1-1


Future challenges for smart cities: cyber-security and digital forensics

Z Baig, P Szewczyk, C Valli, P Rabadia, P Hannay, M Chernyshev, M Johnstone, P Kerai, A Ibrahim, K Sansurooah, N Syed, M Peacock

(2017), Vol. 22, pp. 3-13, Digital investigation, Amsterdam, The Netherlands, C1-1

journal article

Modelling and Evaluation of Malicious Attacks against the IoT MQTT Protocol

Syed Firdous, Zubair Baig, Craig Valli, Ahmed Ibrahim

(2017), pp. 748-755, Internet of Things-Green Computing-Cyber, Physical and Social Computing-SmartData 2017 : proceedings : 2017 Institute of Electrical and Electronics Engineers International Conference on Internet of Things, Institute of Electrical and Electronics Engineers Green Computing and Communications, Institute of Electrical and Electronics Engineers Cyber, Physical and Social Computing, Institute of Electrical and Electronics Engineers Smart Data : 21-23 June 2017, Exeter, United Kingdom, Exeter, England, E1-1


Classifying malicious activities in Honeynets using entropy and volume-based thresholds

M Sqalli, S Firdous, K Salah, M Abu-Amara

(2013), Vol. 6, pp. 567-583, Security and Communication Networks, C1-1

journal article

An entropy and volume-based approach for identifying malicious activities in honeynet traffic

M Sqalli, S Firdous, Z Baig, F Azzedin

(2011), pp. 23-30, Proceedings - 2011 International Conference on Cyberworlds, Cyberworlds 2011, Banff, CANADA, E1-1


A reliable peer-to-peer protocol for mobile ad-hoc wireless networks

M Al-Mouhamed, I Khan, S Firdous

(2011), pp. 32-37, Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, E1-1


Identifying network traffic features suitable for honeynet data analysis

M Sqalli, N Syed, K Salah, M Abu-Amara

(2011), pp. 001044-001048, Canadian Conference on Electrical and Computer Engineering, Niagara Falls, ON, Canada, E1-1


Funded Projects at Deakin

Industry and Other Funding


Dr Zubair Baig, Dr Muna Al-Hawawreh, Dr Jesse Laeuchli, Dr Naeem Syed, Dr Anh Dinh

Victorian Chamber of Commerce and Industry

  • 2023: $66,000

Other Funding Sources

Socrates: Software Security with a focus on critical technologies.

A/Prof Lei Pan, Dr Syed Wajid Ali Shah, Prof Robin Ram Mohan Doss, Dr Zubair Baig, Prof Jemal Abawajy, Prof Shiri Krebs, Dr Jayson Lamchek, Dr Shamsul Huda, Dr Muna Al-Hawawreh, Dr Naeem Syed, Dr Jack Li, Dr Ye Zhu, Dr Frank Jiang, A/Prof William Yeoh, Prof Chang-Tsun Li, A/Prof Lennon Chang, Prof Patrick Emerton, Dr Hourieh Khalajzadeh, Dr Van-Hau Trieu, Dr Yanjun Zhang, Dr Leo Zhang

Cyber Security Research Centre Limited

  • 2024: $30,244
  • 2023: $120,976


No completed student supervisions to report