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In this paper, we propose a secure and revocable biometric bit-string generation technique for template protection. The proposed method consists of random tiling and equal probable discretisation. Random tiling is a feature transformation method to derive random features from biometric data based on a user specific key. In the event of template is compromised, a refreshed biometric template can easily be issued by replacing the compromised key with a new user specific key. On the other hand, we propose a modified equal probable discretisation to partitions the uneven biometric data distribution into different equal probable segments rather than equal width segments. This guarantees each set of the codeword has the same likelihood of occurring and thus user privacy is strengthened as it becomes difficult for an adversary to correctly guess the codeword associated with each segment. The proposed method is evaluated using multimodal biometrics - the fusion of fingerprint and palmprint at feature level. Encouraging experimental results vindicate the feasibility of our approach.