Cooperative Artificial Immune System And Recurrent Neural Network Error Correction Scheme For Generating Robust Hardware Key
In this paper, a Computational Intelligent (CI) error detection\correction scheme is proposed that is based on cooperation between Artificial Immune System (AIS) and Recurrent Neural Network (RNN). The key idea is to incorporate the search capability, detection, and classification of the AIS algorithms for error characterization for Physically Unclonable Function (PUF) error characterization. AIS also manage the supervised learning of RNNs. The parallel structure of Bidirectional Associated Memory (BAM) neural networks is used to correct the PUF occurred errors. The results demonstrate effectiveness of the proposed structure as an intelligent error correction scheme to have a trusted hardware.
Keywords- Artificial Immune System, Error Detection/Correction, PUF Key Generation, Recurrent Neural Network.