Multimodal object authentication with random projections: a worst-case approach

In this paper, we consider a forensic multimodal authentication framework based on binary hypothesis testing in random projections domain. We formulate a generic authentication problem taking into account several possible counterfeiting strategies. The authentication performance analysis is accomplished in the scope of Neyman- Pearson framework as well as for an average probability of error for both direct and random projections domains. Worst-case attack/acquisition channel leading to the worst performance loss in terms of Bhattacharyya distance reduction is presented. The obtained theoretical findings are also confirmed by results of computer simulation