Biometric template protection schemes in particular, biometric cryptosystems bind secret keys to biometric data, i.e. complex key retrieval processes are performed at each authentication attempt. Focusing on biometric identification exhaustive 1: N comparisons are required for identifying a biometric probe. As a consequence comparison time frequently dominates the overall computational workload, preventing biometric cryptosystems from being operated in identification mode. In this paper we propose a computational efficient two-stage identification system for fingerprint-biometric cryptosystems. Employing the concept of adaptive Bloom filter-based cancelable biometrics, pseudonymous binary prescreeners are extracted based on which top-candidates are returned from a database. Thereby the number of required key-retrieval processes is reduced to a fraction of the total. Experimental evaluations confirm that, by employing the proposed technique, biometric cryptosystems, e.g. fuzzy vault scheme, can be enhanced in order to enable a real-time privacy preserving identification, while at the same time biometric performance is maintained.