Dinusha Vatsalan

Room 370, 4 Research Park Drive, Macquarie University, NSW 2109, Australia
Phone: +61 2 9850 9541
dinusha.vatsalan@mq.edu.au

  • Privacy-preserving record linkage
  • Privacy-preserving data sharing and analytics
  • Privacy-preserving machine learning
  • Privacy attacks and defenses
  • Privacy risk quantification

I am a Senior Lecturer in the School of Computing and a Researcher in the Macquarie University Cyber Security Hub. I’m interested in designing and developing privacy-enhancing algorithms for record linkage, data mining, machine learning, data sharing, and data analytics, evaluating and developing privacy attacks and defences, and privacy risk quantification.

My research focuses on both evaluating and quantifying the privacy risk and vulnerability of Machine Learning models and data towards different types of cyber-attacks and developing responsible and equitable algorithms for different Cyber Security and privacy-preserving applications, including private data matching, private set intersection, and private data sharing and analytics. I apply my background in probabilistic encoding, probabilistic data structures, differential privacy, and machine learning to solve challenging and emerging research problems in Cyber Security.

  • Privacy-preserving record linkage
  • Privacy-preserving data sharing and analytics
  • Privacy-preserving machine learning
  • Privacy attacks and defenses
  • Privacy risk quantification
  • Privacy-preserving record linkage for rare disease studies
  • Privacy-preserving online advertising
  • Defenses against adversarial attacks on Machine Learning models
  1. Nan Wu, Dinusha Vatsalan, Sunny Verma, Mohamed AliKaafar, “Fairness and Cost Constrained Privacy-Aware Record Linkage”, IEEE Transactions on Information Forensics and Security, Vol. 17, pp. 2644 – 2656, July 2022.
  2. Dinusha Vatsalan, Thierry Rakotoarivelo, Raghav Bhaskar, Paul Tyler, and DjaziaLadjal, “Privacy risk quantification in education data using Markov model”, British Journal of Education Technology, Vol. 53, No. 4, pp. 804-821, April 2022.
  3. Dinusha Vatsalan, Raghav Bhaskar, Aris Gkoulalas-Divanis, and DimitriosKarapiperis, “Privacy Preserving Text Data Encoding and Topic Modelling”, IEEE International Conference on Big Data, pp. 1308-1316, January 2022.
  4. Aris Gkoulalas-Divanis, Dinusha Vatsalan, DimitriosKarapiperis, and Murat Kantarcioglu, “Modern privacy-preserving record linkage techniques: An overview”, IEEE Transactions on Information Forensics and Security, 16, pp. 4966-4987, September 2021.
  5. Tatyana Stojnic,Dinusha Vatsalan,Nalin A. G. Arachchilage, “Phishing email strategies: Understanding cybercriminals’ strategies of crafting phishing emails”, Security and Privacy, Vol. 4, No. 5, Wiley, May 2021.
  6. MarwaKeshk, Benjamin Turnbull,Elena Sitnikova, Dinusha Vatsalan, Nour Moustafa, “Privacy-Preserving Schemes for Safeguarding Heterogeneous Data Sources in Cyber-Physical Systems”, IEEE Access, Vol. 9, pp. 55077 – 55097, March 2021.
  7. Qing Yang, Yiran Shen, Dinusha Vatsalan, Jianpei Zhang, Mohamed Ali Kaafar, Wen Hu,“P4mobi: A probabilistic privacy-preserving framework for publishing mobility datasets”, IEEE Transactions on Vehicular Technology, Vol. 69, No. 7, pp. 6987 – 6999, May 2020

Full publication list available at: https://researchers.mq.edu.au/en/persons/dinusha-vatsalan