Neuromorphic Algorithms for Hardware-Based Anomaly Detection – Phase 2

Project Member(s): Hamilton, T.

Funding or Partner Organisation: Defence Science and Technology Group of the Department of Defence
Defence Science and Technology Group of the Department of Defence

Start year: 2021

Summary: The aim of the proposed research project described in this SOW will be to expand upon the findings of the current research agreement, which is due to conclude in March 2021. At the conclusion of the current agreement it is anticipated that a novel biologically inspired anomaly detection algorithm prototype will be available for further experimentation. Thus the goals of the research project proposed in this SOW will be as follows: • Further development, refinement and characterisation of the anomaly detection algorithm, with key areas to explore: o Detection performance. o Robustness. o Implementation efficiency. • Comparison of the novel algorithms based on Neuromorphic Computing principles to conventional deep learning equivalents. • Development of a prototype FPGA hardware implementation.

FOR Codes: Emerging Defence Technologies, Expanding Knowledge in the Information and Computing Sciences, Neural, Evolutionary and Fuzzy Computation, Pattern Recognition and Data Mining, Evolutionary computation, Data structures and algorithms

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.