Anomaly detection and classification for streaming data using partial differential equations
Nondominated sorting, or Pareto Depth Analysis (PDA) is widely used in multi objective optimization and has recently found important applications in multi criteria anomaly detection. We propose in this paper a fast real time streaming version of the PDA algorithm for anomaly detection and classification that exploits the computational advantages of partial differential equation (PDE) continuum limits. We prove convergence rates for the continuum approximations and present the results of numerical experiments.
ArXiv