Lecturer / Assistant Professor
School of Computer Science
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.
Year Citation 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, 36 pages.
2022 Ullah, F., & Babar, M. A. (2022). On the scalability of Big Data Cyber Security Analytics systems. Journal of Network and Computer Applications, 198, 23 pages.
DOI Scopus2 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, 27 pages.
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 Scopus4 WoS1
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 Scopus41 WoS31
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 Scopus45 WoS37
Year Citation 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.
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 Scopus5 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. (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.
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
- 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)
- 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)
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 2022 Co-Supervisor Developing a Framework of Secure Microservice Architecture in Cyber Physical Systems Doctor of Philosophy Doctorate Full Time Mr Yasir Abdullah J Althobaiti 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
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