Behavioural cues extraction Sample Clauses

Behavioural cues extraction. This section described the extraction of the different behavioural cues and the behaviour inference with respect to user authentication. As indicated in the Description of Work, the BehavAuth will leverage multiple behavioural cues in order to learn the behavioural patterns of the users and based on these patterns to identify them to the TagItSmart platform. The results of the inference of the different behavioural patterns are fused into a coherent authentication result that is propagated to the TagItSmart platform. For the development of the machine-­learning models that learn the behavioural patterns of the users and then authenticate them based on these patterns, the same development process was followed. The data collected from the sensors were converted in the suitable format to be able to train the behavioural model and then to be able to predict the authentication of the user. The system was evaluated on the StudentLife data and the evaluation process is described in detail in the D2.2 [51] deliverable. The BehavAuth library has been developed in a sense to monitor the behaviour of the user for one week and then initiate the authentication process based on the behavioural patterns that have been learned during this period. Each of the models developed were evaluated against multiple machine-­learning techniques in order to understand the accuracy and robustness of each of the machine-­learning approaches. The machine-­learning technique that achieved the highest accuracy was considered as the final technique that will be used in the BehavAuth app. In the following subsections, each of the authentication components that were developed are analysed in detail.
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