Bruce Gu (IEEE M’17) is currently a Teaching Focused Academic with the Discipline of Information Technology, College of Engineering and Science, Victoria University.

He received his PhD in Computer Science from Deakin University, Australia in 2020. In 2009 and 2011, he received his BInfoTech and MIT degrees from Deakin University, respectively. He has over 10 years of industry engagement experience in Australia. His research interests include artificial intelligence, cybersecurity, privacy preserving, blockchain, Internet of Things and Edge AI.

He has served as the TPC co-chair, publicity co-chair, organisation chair and TPC member for many international conferences.

He is a member of:

  • Institute of Electrical and Electronics Engineers (IEEE)
  • Australian Computer Society (ACS).

Portfolios

Information Technology Discipline, College of Engineering and Science

Areas of expertise

  • Artificial intelligence
  • Cybersecurity
  • Privacy preserving
  • Blockchain
  • Internet of Things

Contact details

Refereed journal articles

Gao, L., Luan, T.H., Gu, B., Qu, Y. and Xiang, Y., 2021. Context-Aware Privacy Preserving in Edge Computing. In Privacy-Preserving in Edge Computing (pp. 35-63). Springer, Singapore.

Gao, L., Luan, T.H., Gu, B., Qu, Y. and Xiang, Y., 2021. Blockchain Based Decentralized Privacy Preserving in Edge Computing. In Privacy-Preserving in Edge Computing (pp. 83-109). Springer, Singapore.

Gao, L., Luan, T.H., Gu, B., Qu, Y. and Xiang, Y., 2021. An Introduction to Edge Computing. In Privacy-Preserving in Edge Computing (pp. 1-14). Springer, Singapore.

Gao, L., Luan, T.H., Gu, B., Qu, Y. and Xiang, Y., 2021. Privacy Issues in Edge Computing. In Privacy-Preserving in Edge Computing (pp. 15-34). Springer, Singapore.

Liu, Y., Qu, Y., Xu, C., Hao, Z. and Gu, B., 2021. Blockchain-Enabled Asynchronous Federated Learning in Edge Computing. Sensors, 21(10), p.3335.

Ho, S., Qu, Y., Gu, B., Gao, L., Li, J. and Xiang, Y., 2021. DP-GAN: Differentially private consecutive data publishing using generative adversarial nets. Journal of Network and Computer Applications, 185, p.103066.

Liu, F., Gu, B., Qin, S., Zhang, K., Cui, L. and Xie, G., 2021. Power grid partition with improved biogeography-based optimization algorithm. Sustainable Energy Technologies and Assessments, 46, p.101267.

Wang, X., Gu, B., Qu, Y., Ren, Y., Xiang, Y. and Gao, L., 2020, November. A privacy preserving aggregation scheme for fog-based recommender system. In International Conference on Network and System Security (pp. 408-418). Springer, Cham.

Gu, B., Wang, X., Qu, Y., Jin, J., Xiang, Y. and Gao, L., 2020, October. Location-aware privacy preserving scheme in SDN-enabled fog computing. In International Conference on Security and Privacy in Digital Economy (pp. 176-190). Springer, Singapore.

Wang, X., Gu, B., Qu, Y., Ren, Y., Xiang, Y. and Gao, L., 2020, June. Reliable customized privacy-preserving in fog computing. In ICC 2020-2020 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.

Gu, B., Wang, X., Qu, Y., Jin, J., Xiang, Y. and Gao, L., 2019, May. Context-aware privacy preservation in a hierarchical Fog computing system. In ICC 2019-2019 IEEE International Conference on Communications (ICC) (pp. 1-6). IEEE.

Gu, B.S., Gao, L., Wang, X., Qu, Y., Jin, J. and Yu, S., 2019. Privacy on the edge: Customizable privacy-preserving context sharing in hierarchical edge computing. IEEE Transactions on Network Science and Engineering.

Wang, X., Gu, B., Ren, Y., Ye, W., Yu, S., Xiang, Y. and Gao, L., 2019. A fog-based recommender system. IEEE Internet of Things Journal, 7(2), pp.1048-1060.