Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination Detection

Abstract

This paper presents a new technique called Statistical Contamination Analyzer (SCAn) to detect backdoors in DNN models by performing a statistical analysis on the global information of the model's representations, which can effectively detect data contamination attacks, including the new targeted contamination attack (TaCT) discovered in the study.