Dr Faheem Ullah

• Journals

  Year	Citation
  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
  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
  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 Scopus4 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. 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 Scopus11 WoS5
  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 Scopus46 WoS32
  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 Scopus57 WoS40

• Conference Papers

  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. DOI Scopus5 WoS3
  2022	Aurangzaib, R., Iqbal, W., Abdullah, M., Bukhari, F., Ullah, F., & Erradi, A. (2022). 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). Bangkok, THAILAND: IEEE. DOI
  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. 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