RDA – Artificial Immune System (AIS) for Anomaly Detection

January 2, 2016June 5, 2020 by Pete Scully PhD (UK), posted in code/science

The Receptor Density Algorithm (RDA) is an Artificial Immune System (AIS) anomaly detection algorithm modelled upon how T-cell receptors respond to antigen, originally modelled by Owens et al in 2009. A recent small project has been to investigate its applicability as an AIS anomaly classifier for our CARDINAL-Vanilla AIS self-healing architecture.

Github repo | Version 0.1 implementation of RDA in python 2.7.

Published by Pete Scully PhD (UK)

Find my work on Research, Technology & Science... Past highlights include @PyCon, Data Science @Lexr.AI, Agri-Tech @MSU-TH, 3D Reconstruction Light Stages for Plants (Phenotypic/Genomic Mappings) @AU @NPPC-UK, Cybernetics, Social Science + Behavioural Research + Grant Writing @MU-TH, Model Explainability, IoT Apps for Zombies, Self-Healing AI + Cyber Security @Airbus, COVID-19 Thailand's Provincial Public Data Analysis, PlayfulCoding.EU, Training SW Engineers @MorganStanley, Commercial Projects + Start-ups. To discuss or work together, I'm on email: pmdscully-at-gmail-com. View all posts by Pete Scully PhD (UK)