Dr Yi Han

  • Room: Level: 07 Room: 15
  • Building: Doug McDonell Building
  • Campus: Parkville

Recent publications

  1. Han, Y.; Rubinstein, B. Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks. . The AAAI Press. 2018.
  2. Han, Y.; Rubinstein, BIP.; Abraham, T.; Alpcan, T.; De Vel, O.; Erfani, S.; Hubczenko, D.; Leckie, C.; Montague, P. Reinforcement learning for autonomous defence in software-defined networking. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11199 LNCS, pp. 145-165. DOI: 10.1007/978-3-030-01554-1_9
  3. Han, Y.; Chan, J.; Alpcan, T.; Leckie, C. Using Virtual Machine Allocation Policies to Defend against Co-Resident Attacks in Cloud Computing. IEEE Transactions on Dependable and Secure Computing. IEEE COMPUTER SOC. 2017, Vol. 14, Issue 1, pp. 95-108. DOI: 10.1109/TDSC.2015.2429132
  4. Han, Y.; Alpcan, T.; Chan, J.; Leckie, C.; Rubinstein, BIP. A Game Theoretical Approach to Defend Against Co-Resident Attacks in Cloud Computing: Preventing Co-Residence Using Semi-Supervised Learning. IEEE Transactions on Information Forensics and Security. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2016, Vol. 11, Issue 3, pp. 556-570. DOI: 10.1109/TIFS.2015.2505680