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In this paper, we investigate the performance of a continuous biometric authentication system under various different analysis techniques. We test these on a publicly available continuous mouse dynamics database, but the techniques can be applied to other biometric modalities in a continuous setting also. We test all different combinations of fusion techniques, threshold settings, score boosting techniques and static versus dynamic trust models. We extensively describe the way that performance is reported when analyzing the performance of a continuous authentication system. Contrary to a biometric system for access control at the start of a session can the performance not simply be reported by a single EER value or a DET curve. We show that the optimal performance we can reach with our new techniques improves significantly over the best known performance on the same dataset.