In this paper we advocate a new approach to item identification based on physical unclonable features. Being unique characteristics of an item, these features represent a kind of unstructured random codebook that links the identification problem to digital communications via composite hypothesis testing. Despite the obvious similarity, this problem is significantly different in that a security constraint prohibits the disclosure of the entire codebook at the identification stage. Besides this, complexity, memory storage and universality constraints should be taken into account for databases with several hundred millions entries. Therefore, we attempt to find a trade-off between performance, security, memory storage and universality constraints. A practical suboptimal method is considered based on our reference list decoding (RLD) framework. Simulation results are presented to demonstrate and support the theoretical findings.