Toward optimal trade-off between identification and secrecy-key binding using linear codes

We consider the trade-off between identification and secret-key binding capacities in biometric systems. We propose the use of linear codes to achieve optimal trade-off for general source and noise models. We relate the problem to classical point to point communication problems, and two system designs based on linear codes are discussed. One design is proven to achieve optimal trade-off by using good linear codes and good decoders. The other design can be proven to achieve slightly suboptimal performance with lower decoder complexity, which is proper for many practical situations. Based on these results, we are also able to extend previous achievable rate region results to general source and noise models that have dependency within and across source and noise elements.