Prof. Dali Kaafar​

Level 2, 4 Research Park Drive, Macquarie University
Phone: 0435 747249
dali.kaafar@mq.edu.au

 

  • Privacy Enhancing Technologies, Data and Information Security
  • Distributed networked systems and Mobile Security
  • Robustness and Security of Machine Learning
  • Information Theory and Applied Data Mining
  • Human identification and Next Generation Authentication systems

I am a full Professor in the Faculty of Science and Engineering and the Executive Director of the Macquarie University Cyber Security Hub. I am on the editorial board of IEEE Transactions on Information Forensics & Security (IEEE T-IFS) and IEEE Transactions on Dependable and Secure Computing (IEEE TDSC) and serve on the board of the Proceedings of Privacy Enhancing Technologies and the Privacy Enhancing Technologies Symposium as senior member. I am also the founder of the Information Security and Privacy group at CSIRO Data61 and member of the CORE Ranking Advisory Board.

My research expertise includes provably private and secure technologies with a focus on privacy preserving data sharing and secure and trustworthy AI, privacy preserving distributed systems, applied cryptography, networked systems security, human-centric security and next generation authentication and identification systems. I am interested in modelling, developing and deploying mathematically rigorous information-theory based techniques to 1- measure information leakage and security vulnerabilities of existing systems, 2- theorise and construct mathematical definitions of privacy and security and validate theoretical attacks on real-life use cases and data and 3- develop algorithms and protocols with strong guarantees of privacy/security and optimal efficiency and utility. 

  • Privacy Enhancing Technologies, Data and Information Security
  • Distributed networked systems and Mobile Security
  • Robustness and Security of Machine Learning
  • Information Theory and Applied Data Mining
  • Human identification and Next Generation Authentication systems
  • An Automated System for Rapid, Accurate Malware Analysis and Effective Triage
  • AUSMURI: Cohesive and Robust Human-Bot Cybersecurity Teams
  • Combatting Global Phone Scams
  • DPAIP: Private Machine Learning As a Service
  • Mathematical foundations for Privacy-preserving techniques and Obfuscation in Text Analytics
  • Differential Privacy Algorithms for Data sharing

Recent publications:

  1. Vatsalan, M.A. Kaafar, R. Bhaskar, “Local Differentially Private Fuzzy Counting in Stream Data using Probabilistic Data Structures”, in IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), August 2022.
  2. Wu, D. Vatsalan, S. Verma, M. A. Kaafar, “Fairness and Cost Constrained Privacy-Aware Record Linkage”, Published in IEEE Transactions on Information Forensics and Security (IEEE T-IFS) , July 2022, [DOI: 10.1109/TIFS.2022.3191492]
  3. Kepkowski, L. Hanzlik, I. Wood, M. A. Kaafar, “How Not to Handle Keys: Timing Attacks on FIDO Authenticator Privacy”, In Privacy Preserving Technologies Symposium (PETS 2022), Sydney, 2022.
  4. Lu, H. J. Asghar, M. A. Kaafar, D. Webb, P. Dickinson, “A Differentially Private Framework for Deep Learning with Convexified Loss Functions”, in IEEE Transactions on Information Forensics and Security (IEEE T-IFS), April 2022, Page(s): 2151 – 2165, DOI: 10.1109/TIFS.2022.3169911.
  5. Masood, S. Berkovsky, M. A. Kaafar, “Tracking and Personalization”, Book Chapter in “Modern Socio-Technical Perspectives on Privacy”, Publisher Springer, Cham, pp. 171-202, 2022.

Full publication list available at: https://scholar.google.com/citations?hl=en&user=9DR87DQAAAAJ&view_op=list_works&sortby=pubdate