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Dr Mohiuddin Ahmed

Lecturer

Staff Member Details
Telephone: +61 8 6304 5121
Email: mohiuddin.ahmed@ecu.edu.au
Campus: Joondalup  
Room: JO18.418B  
ORCID iD: https://orcid.org/0000-0002-4559-4768

Overview of role

Dr. Mohiuddin Ahmed is a Lecturer of Computing and Security discipline in the School of Science.

Current Teaching

  • CSI3350 Enterprise Security and Governance
  • CSI2107 Software Reverse Engineering

Background

Mohiuddin Ahmed has made practical and theoretical contributions in cyber security and big data analytics for several application domains. His research has a high impact on data and security analytics, false data injection attacks, and digital health. Mohiuddin has led edited multiple books and contributed articles in The Conversation. He has over 50 publications in reputed venues. Mohiuddin secured the prestigious ECU Early Career Researcher Grant for investigating effectiveness of blockchain for dependable and secure e-health. He also secured several external and internal grants within a very short time frame.

Professional Memberships

  • IEEE Senior Member
  • ACS Certified Professional
  • AISA

Awards and Recognition

National and International Awards

  • 2020 Edith Cowan University Aspire Award Winner
  • UNSW Canberra - High Impact Research Publications Award
  • UNSW Canberra - PhD Thesis Writing Fellowship
  • UNSW Canberra - University International Postgraduate Award
  • UNSW Canberra - Postgraduate Research Support Scheme

University and National Teaching Awards

  • CIT Cyber Teaching Team Nomination for Staff Achievement Award, 2018

National and International Research Positions

  • 2016 - Senior Researcher at MIMOS, Malaysian National R&D.

Research Areas and Interests

  • Cyber Security
  • Data Analytics
  • Machine Learning
  • Big Data
  • Edge Computing
  • Blockchain
  • Healthcare
  • Drones

Qualifications

  • Doctor of Philosophy, The University of New South Wales, 2016.

Research

Recent Research Grants

  • Developing autonomous solutions for building knowledge graphs to support educational outcomes in Virtuoso,  CingleVue Pty Ltd,  Scholarships to Support Industry Engagement PhD Project,  2020 - 2024,  $150,000.
  • Heterogeneous Anomaly Detection from Network Traffic Streams using Data Summarization,  Cyber Security Research Centre Ltd,  Cyber Security Research Centre Masters Scholarship,  2020 - 2022,  $120,000.
  • Securing Internet of Medical Things against False Data Injection Attacks Using Blockchain,  Edith Cowan University,  ECU Early Career Researcher Grant - 2019,  2019 - 2020,  $25,000.

Recent Publications (within the last five years)

Book Chapters

  • Sadik, S., Ahmed, M., (2020), An Overview of Dark Web. Security Analytics for the Internet of Everything , 55-64, Boca Raton, United States of America, CRC Press.
  • Rashid, T., Saeed, M., Ahmed, M., (2020), A New Era of Project Management Using Blockchain Technology. Blockchain in Data Analytics, 102-121, Newcastle upon Tyne, England, Cambridge Scholars Publishing.
  • Bostami, B., Ahmed, M., (2020), Deep Learning Meets Malware Detection: An Investigation. Combating Security Challenges in the Age of Big Data, 137-155, Cham, Switzerland, Springer, DOI: https://doi.org/10.1007/978-3-030-35642-2_7.
  • Seraj, R., Ahmed, M., (2020), Concept Drift for Big Data. Combating Security Challenges in the Age of Big Data, 29-43, Cham, Switzerland, Springer, DOI: https://doi.org/10.1007/978-3-030-35642-2_2.
  • Al Fahdi, H., Ahmed, M., (2020), Cryptographic Attacks, Impacts and Countermeasures. Security Analytics for Internet of Everything , 217-232, Boca Raton, United States of America, CRC Press.
  • Furhad, MH., Sadik, S., Ahmed, M., Barkat, A., (2020), Exploring E-Commerce in Cyber Security Context Through Blockchain Technology. Blockchain in Data Analytics, 216-233, Newcastle upon Tyne, England, Cambridge Scholars Publishing.
  • Sadik, S., Ahmed, M., Hassan, MH., (2020), Blockchain in Healthcare. Blockchain in Data Analytics, 234-253, Newcastle upon Tyne, England, Cambridge Scholars Publishing.
  • Saeed, M., Rashid, T., Ahmed, M., (2020), A Benefits Realization Approach to Cyber Security Projects Implementation in the Public Sector Organizations. Security Analytics for Internet of Everything , 93-114, Boca Raton, United States of America, CRC Press.
  • Chong, K., Ahmed, M., Islam, S., (2020), An Investigation of Performance Analysis of Machine Learning-Based Techniques for Network Anomaly Detection. Security Analytics for Internet of Everything , 117-156, Boca Raton, USA, CRC Press.
  • Bostami, B., Ahmed, M., (2020), Blockchain for Internet of Things. Blockchain in Data Analytics, 24-51, Newcastle upon Tyne, England, Cambridge Scholars Publishing.
  • Bostami, B., Ahmed, M., Choudhury, S., (2019), False Data Injection Attacks in Internet of Things. Performability in Internet of Things, 47-58, Cham, Switzerland, Springer, DOI: 10.1007/978-3-319-93557-7.
  • Ahmed, M., Choudhury, S., Al-Turjman, F., (2019), Big Data Analytics for Intelligent Internet of Things. Artificial Intelligence in IoT, 107-127, Cham, Switzerland, Springer, DOI: 10.1007/978-3-030-04110-6.
  • Saeed, M., Ahmed, M., (2018), Project Management for Effective Data Analytics. Data Analytics Concepts, Techniques, and Applications, 219-234, Boca Raton, USA, CRC Press, DOI: 10.1201/9780429446177.
  • Ahmed, M., Haque, N., (2018), Anomaly Detection and Big Data in IPTV Networks. IPTV Delivery Networks: Next Generation Architectures for Live and Video-on-Demand Services, Hoboken, USA, John Wiley & Sons.
  • Hassan, MM., Ahmed, M., (2018), Blockchain in the Era of Industry 4.0. Data Analytics Concepts, Techniques, and Applications, 235-273, Boca Raton, USA, CRC Press, DOI: 10.1201/9780429446177.
  • Ahmed, M., Barkat, A., (2018), Health Care Security Analytics. Data Analytics Concepts, Techniques, and Applications, 403-416, Boca Raton, USA, CRC Press, DOI: 10.1201/9780429446177.
  • Bostami, B., Ahmed, M., (2018), Intrusion Detection for Big Data. Data Analytics Concepts, Techniques, and Applications, 375-402, Boca Raton, USA, CRC Press, DOI: 10.1201/9780429446177.
  • Ahmed, M., (2017), Infrequent Pattern Identification in SCADA Systems Using Unsupervised Learning. Security Solutions and Applied Cryptography in Smart Grid Communications, 215-225, Hershey, USA, IGI Global , DOI: 10.4018/978-1-5225-1829-7.ch011.

Journal Articles

  • Akhter, AF., Ahmed, M., Shah, AF., Anwar, A., Zengin, A., (2021), A Secured Privacy-Preserving Multi-Level Blockchain Framework for Cluster Based VANET. Sustainability, 13(1), 1-25, Basel, Switzerland, DOI: 10.3390/su13010400.
  • Ahmed, M., Seraj, R., Islam, S., (2020), The k-means Algorithm: A Comprehensive Survey and Performance Evaluation. Electronics, 9(8), article number 1295, DOI: 10.3390/electronics9081295.
  • Ahmed, M., Pathan, AK., (2020), Blockchain: Can It Be Trusted?. Computer, 53(4), 31-35, DOI: 10.1109/MC.2019.2922950.
  • Ahmed, M., Pathan, M., (2020), False Data Injection Attack (FDIA): An Overview and New Metrics for Fair Evaluation of its Countermeasure. Complex Adaptive Systems Modeling, 8(1), Article number 4, DOI: 10.1186/s40294-020-00070-w.
  • Rashid, B., Ahmed, M., Sikos, L., Haskell-Dowland, P., (2020), A Novel Penalty-Based Wrapper Objective Function for Feature Selection in Big Data using Cooperative Co-Evolution. IEEE Access, 8(2020), 150113-150129, DOI: 10.1109/ACCESS.2020.3016679.
  • Rashid, B., Ahmed, M., Sikos, L., Haskell-Dowland, P., (2020), Cooperative co-evolution for feature selection in Big Data with random feature grouping. Journal of Big Data, 7(107), 1-42, USA, DOI: 10.1186/s40537-020-00381-y.
  • Sadik, S., Ahmed, M., Sikos, L., Islam, AN., (2020), Toward a Sustainable Cybersecurity Ecosystem. Computers, 9(3), 1-17, DOI: 10.3390/computers9030074.
  • Ahmed, M., Islam, AK., (2020), Deep Learning: Hope or Hype. Annals of Data Science, 7(2020), 427–432, DOI: 10.1007/s40745-019-00237-0.
  • Yang, J., Hasan Onik, MM., Lee, N., Ahmed, M., Kim, C., (2019), Proof-of-Familiarity: A Privacy-Preserved Blockchain Scheme for Collaborative Medical Decision-Making. Applied Sciences, 9(7), Article no.1370, DOI: 10.3390/app9071370.
  • Aurisch, R., Ahmed, M., Barkat, A., (2019), An outlook at Agile methodologies for the independent games developer. International Journal of Computers and Applications, 2019(Article in press), 1-7, DOI: 10.1080/1206212X.2019.1621463.
  • Ahmed, M., (2019), Data summarization: a survey. Knowledge and Information Systems, 58(2), 249-273, DOI: 10.1007/s10115-018-1183-0.
  • Ahmed, M., (2019), False Image Injection Prevention Using iChain. MDPI Applied Sciences, 9(20), Article number 4328, DOI: 10.3390/app9204328.
  • Ahmed, M., (2019), Intelligent Big Data Summarization for Rare Anomaly Detection. IEEE Access, 7(2019), 68669-68677, DOI: 10.1109/ACCESS.2019.2918364.
  • Ahmed, M., (2018), Reservoir-based network traffic stream summarization for anomaly detection. Pattern Analysis and Applications, 21(2), 579-599, DOI: 10.1007/s10044-017-0659-y.
  • Ahmed, M., Barkat, A., (2018), Infrequent pattern mining in smart healthcare environment using data summarization. Journal of Supercomputing, 74(10), 5041-5059, DOI: 10.1007/s11227-018-2376-8.
  • Ahmed, M., (2018), Collective Anomaly Detection Techniques for Network Traffic Analysis. Annals of Data Science, 5(4), 497-512, Heidelberg, Germany, DOI: 10.1007/s40745-018-0149-0.
  • Ahmed, M., (2017), Thwarting DoS Attacks: A Framework for Detection based on Collective Anomalies and Clustering. Computer, 50(9), 76-82, DOI: 10.1109/MC.2017.3571051.
  • Ahmed, M., (2017), An Unsupervised Approach of Knowledge Discovery from Big Data in Social Network. EAI Endorsed Transactions on Scalable Information Systems, 4(14), article no. e3, Belgium, DOI: 10.4108/eai.25-9-2017.153148.
  • Ahmed, M., Mahmood, A., Islam, MR., (2016), A survey of anomaly detection techniques in financial domain. Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, 55(1 February 2016), 278-288, DOI: 10.1016/j.future.2015.01.001.
  • Ahmed, M., Mahmood, A., Hu, J., (2016), A survey of network anomaly detection techniques. Journal of Network and Computer Applications, 60(1 January 2016), 19-31, DOI: 10.1016/j.jnca.2015.11.016.

Conference Publications

  • Furhad, MH., Ahmed, M., Barkat, A., (2020), A Study on Monitoring Coastal Areas for Having a Better Underwater Surveillance Perspective. Proceedings of International Joint Conference on Computational Intelligence IJCCI 2018, 163-174, Singapore, Springer, DOI: 10.1007/978-981-13-7564-4_14.
  • Ahmed, M., Barkat, A., (2019), Performance Analysis of Hard Clustering Techniques for Big IoT Data Analytics. Proceedings - 2019 Cybersecurity and Cyberforensics Conference, CCC 2019, 62-66, Online, IEEE, DOI: 10.1109/CCC.2019.000-8.
  • Saeed, M., Ahmed, M., (2019), Evaluation Metrics for Big Data Project Management. Smart Grid and Internet of Things Second EAI International Conference, SGIoT 2018, Niagara Falls, ON, Canada, July 11, 2018 Proceedings, 256(July 11-11, 2018), 139-142, Cham, Switzerland, Springer, DOI: 10.1007/978-3-030-05928-6_14.
  • Khandaker, S., Hussain, A., Ahmed, M., (2019), Effectiveness of Hard Clustering Algorithms for Securing Cyber Space. Smart Grid and Internet of Things Second EAI International Conference, SGIoT 2018, Niagara Falls, ON, Canada, July 11, 2018 Proceedings, 256(July 11-11, 2018), 113-120, Cham, Switzerland, Springer, Cham, DOI: 10.1007/978-3-030-05928-6_11.
  • Ahmed, M., Pathan, AK., (2019), Investigating Deep Learning for Collective Anomaly Detection - An Experimental Study. Security in Computing and Communications 6th International Symposium, SSCC 2018, Bangalore, India, September 19–22, 2018, Revised Selected Papers, 969(Sep. 19-22, 2018), 211--219, Singapore, Springer, DOI: 10.1007/978-981-13-5826-5_15.
  • Ahmed, M., Ullah, A., (2018), False Data Injection Attacks in Healthcare. Data Mining. AusDM 2017. Communications in Computer and Information Science, vol 845, 845, , 192-202, Singapore, Springer, DOI: 10.1007/978-981-13-0292-3_12.
  • Ahmed, M., Choudhury, N., Uddin, S., (2017), Anomaly detection on big data in financial markets. ASONAM '17 Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, 998-1001, New York, NY, USA, ACM, DOI: 10.1145/3110025.3119402.
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