Faheem Ullah

Dr Faheem Ullah

Lecturer / Assistant Professor

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.


I am a lecturer in the School of Computer Science at the University of Adelaide. I am also a member of the Centre for Research on Engineering Software Technologies (CREST) where I lead the R&D on big data analytics and cloud computing. 

My research interests include cyber security, big data analytics, software engineering, cloud computing, and machine learning. I have applied my research expertise in various application domains such as healthcare, oil & gas, defense, and green computing. 

  • Journals

    Year Citation
    2024 Wajahat, A., He, J., Zhu, N., Mahmood, T., Nazir, A., Ullah, F., . . . Osman, M. (2024). An effective deep learning scheme for android malware detection leveraging performance metrics and computational resources. Intelligent Decision Technologies, 18(1), 33-55.
    DOI
    2024 Wajahat, A., He, J., Zhu, N., Mahmood, T., Nazir, A., Ullah, F., . . . Dev, S. (2024). Securing Android IoT devices with GuardDroid transparent and lightweight malware detection. Ain Shams Engineering Journal, 15(5), 102642.
    DOI
    2024 Nazir, A., He, J., Zhu, N., Wajahat, A., Ullah, F., Qureshi, S., . . . Pathan, M. S. (2024). Collaborative threat intelligence: Enhancing IoT security through blockchain and machine learning integration. Journal of King Saud University - Computer and Information Sciences, 36(2), 101939.
    DOI
    2024 Ullah, F., Dhingra, S., Xia, X., & Babar, M. A. (2024). Evaluation of distributed data processing frameworks in hybrid clouds. Journal of Network and Computer Applications, 224, 14 pages.
    DOI
    2023 Nazir, A., He, J., Zhu, N., Wajahat, A., Ma, X., Ullah, F., . . . Pathan, M. S. (2023). Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets. Journal of King Saud University - Computer and Information Sciences, 35(10), 101820.
    DOI Scopus4
    2023 Wajahat, A., He, J., Zhu, N., Mahmood, T., Nazir, A., Pathan, M. S., . . . Ullah, F. (2023). An adaptive semi-supervised deep learning-based framework for the detection of Android malware. Journal of Intelligent and Fuzzy Systems, 45(3), 5141-5157.
    DOI Scopus2
    2023 Phu, A. T., Li, B., Ullah, F., Ul Huque, T., Naha, R., Babar, M. A., & Nguyen, H. (2023). Defending SDN against packet injection attacks using deep learning. Computer Networks, 234, 16 pages.
    DOI
    2023 Mansouri, Y., Ullah, F., Dhingra, S., & Babar, M. A. (2023). Design and Implementation of Fragmented Clouds for Evaluation of Distributed Databases. IEEE Transactions on Cloud Computing, 1-14.
    DOI
    2023 Mansouri, Y., Prokhorenko, V., Ullah, F., & Babar, M. A. (2023). Resource Utilization of Distributed Databases in Edge-Cloud Environment. IEEE Internet of Things Journal, 10(11), 9423-9437.
    DOI Scopus2
    2022 Ahmad, H., Dharmadasa, I., Ullah, F., & Babar, M. A. (2022). A Review on C3I Systems' Security: Vulnerabilities, Attacks, and Countermeasures.. ACM Computing Surveys, abs/2104.11906(9), 36 pages.
    DOI Scopus1 WoS1
    2022 Ullah, F., & Babar, M. A. (2022). On the scalability of Big Data Cyber Security Analytics systems. Journal of Network and Computer Applications, 198, 1-23.
    DOI Scopus7 WoS1
    2022 Ullah, F., Ali Babar, M., & Aleti, A. (2022). Design and evaluation of adaptive system for big data cyber security analytics. Expert Systems with Applications, 207, 1-27.
    DOI Scopus1 WoS1
    2021 Sabir, B., Ullah, F., Babar, M. A., & Gaire, R. (2021). Machine Learning for Detecting Data Exfiltration. ACM Computing Surveys, 54(3), 1-47.
    DOI Scopus20 WoS8
    2021 Qureshi, S., Tunio, S., Akhtar, F., Wajahat, A., Nazir, A., & Ullah, F. (2021). Network Forensics: A Comprehensive Review of Tools and Techniques. International Journal of Advanced Computer Science and Applications, 12(5), 879-887.
    DOI Scopus8
    2021 Qureshi, S., He, J., Tunio, S., Zhu, N., Akhtar, F., Ullah, F., . . . Wajahat, A. (2021). A Hybrid DL-Based Detection Mechanism for Cyber Threats in Secure Networks. IEEE Access, 9, 73938-73947.
    DOI Scopus10
    2019 Qureshi, S., Das, G., Tunio, S., Ullah, F., Nazir, A., & Wajahat, A. (2019). Performance analysis of open source solution "ntop" for active and passive packet analysis relating to application and transport layer. International Journal of Advanced Computer Science and Applications, 10(3), 20-27.
    DOI Scopus3
    2019 Ullah, F., & Babar, M. (2019). Architectural Tactics for Big Data Cybersecurity Analytics Systems: A Review. Journal of Systems and Software, 151, 81-118.
    DOI Scopus55 WoS35
    2018 Ullah, F., Edwards, M., Ramdhany, R., Chitchyan, R., Babar, M., & Rashid, A. (2018). Data exfiltration: a review of external attack vectors and countermeasures. Journal of Network and Computer Applications, 101, 18-54.
    DOI Scopus79 WoS53
  • Conference Papers

    Year Citation
    2023 Aurangzaib, R., Iqbal, W., Abdullah, M., Bukhari, F., Ullah, F., & Erradi, A. (2023). Scalable Containerized Pipeline for Real-time Big Data Analytics. In Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom Vol. 2022-December (pp. 25-32). Online: IEEE.
    DOI
    2023 Akhtar, F., Shakeel, A., Nazir, A., Wajahat, A., Ullah, F., & Qureshi, S. (2023). A Study and Application Development on Monitoring Cardio-Vascular Attack using Internet of Thing (IoT). In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies: Idea to Innovation for Building the Knowledge Economy, iCoMET 2020. Online: IEEE.
    DOI
    2023 Ullah, F., & Babar, M. A. (2023). Guidance Models for Designing Big Data Cyber Security Analytics Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14212 LNCS (pp. 70-80). Springer Nature Switzerland.
    DOI
    2023 Dharmadasa, I., & Ullah, F. (2023). Co-Tuning of Cloud Infrastructure and Distributed Data Processing Platforms. In 2023 IEEE International Conference on Big Data (BigData) Vol. abs/2309.00269 (pp. 207-214). Online: IEEE.
    DOI
    2023 Tyllis, N., Ullah, F., & Uzair, M. (2023). An Exploratory Study of Vulnerabilities in Big Data Systems. In Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023 (pp. 1360-1367). IEEE.
    DOI
    2022 Duan, X., Ge, M., Le, T. H., Ullah, F., Gao, S., Lu, X., & Babar, M. A. (2022). Automated Security Assessment for the Internet of Things. In Proceedings of IEEE Pacific Rim International Symposium on Dependable Computing, PRDC Vol. 2021-December (pp. 47-56). online: IEEE.
    DOI Scopus9 WoS7
    2020 Nazir, A., Wajahat, A., Akhtar, F., Ullah, F., Qureshi, S., Malik, S. A., & Shakeel, A. (2020). Evaluating Energy Efficiency of Buildings using Artificial Neural Networks and K-means Clustering Techniques. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies: Idea to Innovation for Building the Knowledge Economy, iCoMET 2020 (pp. 7 pages). Online: IEEE.
    DOI Scopus2
    2020 Wajahat, A., Nazir, A., Akhtar, F., Qureshi, S., Ullah, F., Razaque, F., & Shakeel, A. (2020). Interactively Visualize and Analyze Social Network Gephi. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies: Idea to Innovation for Building the Knowledge Economy, iCoMET 2020 (pp. 9 pages). Online: IEEE.
    DOI Scopus10
    2020 Memon, S. A., Akhtar, F., Nazir, A., Wajahat, A., Qureshi, S., Ullah, F., & Shakeel, A. (2020). Discretization of the Crime Rate from Numerical into Categorical. In 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies: Idea to Innovation for Building the Knowledge Economy, iCoMET 2020 (pp. 7 pages). Online: IEEE.
    DOI Scopus1
    2019 Ullah, F., & Babar, M. (2019). An architecture-driven adaptation approach for big data cyber security analytics. In Proceedings - 2019 IEEE International Conference on Software Architecture, ICSA 2019 (pp. 41-50). online: IEEE.
    DOI Scopus8 WoS4
    2019 Ullah, F., & Babar, M. (2019). QuickAdapt: Scalable adaptation for big data cyber security analytics. In Proceedings of the IEEE International Conference on Engineering of Complex Computer Systems, ICECCS Vol. 2019-November (pp. 81-86). online: IEEE.
    DOI Scopus5 WoS3
    2019 Ullah, F., & Babar, M. A. (2019). Quantifying the impact of design strategies for big data cyber security analytics: An empirical investigation. In Proceedings - 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019 (pp. 146-153). online: IEEE.
    DOI Scopus2
    2017 Ullah, F., Raft, A. J., Shahin, M., Zahedi, M., & Babar, M. A. (2017). Security support in continuous deployment pipeline. In ENASE 2017 - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering (pp. 57-68). Portugal: SCITEPRESS.
    DOI Scopus5 WoS2

Teaching 

  • Concepts in Cyber Security (2022 Trimester 1)
  • Software Engineering Workshop 1 (2017 Semester 1)
  • Software Architecture (2017 Semester 2)
  • Software Engineering Workshop 1 (2018 Semester 1)
  • Software Engineering Workshop 2 (2018 Semester 2)
  • Software Engineering Workshop 1 (2019 Semester 1)
  • Software Architecture (2019 Semester 2)

Course Coordinator

  • Cyber Security Research Project Part A (2022 Trimester 1)
  • Cyber Security Industry Project Part A (2022 Trimester 1)
  • Cyber Security Research Project Part B (2022 Semester 1)
  • Cyber Security Industry Project Part B (2022 Semester 1)

Teaching Philosophy

My teaching philosophy is primarily driven by the following four features.

  • Industry relevance - I keep an eye on industry needs and aim to align my teaching in a way that best relates the content to the industry needs. This helps to enable the students to develop knowledge and learn skills that are directly used in the industry. 
  • Feedback-driven - I am always keen to learn from students how best the course can be taught to convey the maximum value to the students. Also, I observe the students' responses throughout and adjust the path of teaching continuously. 
  • Organized and well-defined - I believe that each aspect (e.g., lecture, assignments, evaluation rubrics, etc.) of teaching should be entirely organized and clear. This helps students to plan and follow the course clearly and neatly right from the beginning. 
  • Up-to-date - Computer science is a field that involves quite rapidly. I aim to keep the content of the course as much up to date as possible. This helps students to not stick to content that is no longer used in the field. Rather, the students learn content that they can directly use in the field. 
  • Current Higher Degree by Research Supervision (University of Adelaide)

    Date Role Research Topic Program Degree Type Student Load Student Name
    2020 Co-Supervisor Open Source Software Security Doctor of Philosophy Doctorate Full Time Mr Yongzheng Xie
  • Other Supervision Activities

    Date Role Research Topic Location Program Supervision Type Student Load Student Name
    2021 - ongoing Principal Supervisor Energy-aware Task-offloading for Big Data Platforms in Edge-Cloud Enviornment The University of Adelaide - Master Full Time Imaduddin Mohammed
    2021 - 2022 Principal Supervisor A Testbed for Assessing the Security of Command and Control Systems The University of Adelaide - Master Full Time Prithviraj Janardhan Kurapothula
    2021 - 2022 Principal Supervisor The Impact of Node Failure and Node Addition on the Performance of Big Data Platforms The University of Adelaide - Master Full Time The Trung Le
  • Position: Lecturer / Assistant Professor
  • Phone: 83130251
  • Email: faheem.ullah@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor Level Five
  • Room: 5.40
  • Org Unit: Computer Science

Connect With Me
External Profiles