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This paper presents a theoretical model for summative e-assessment in distance learning for the future, where exams can be conducted distantly, e.g. at home. This model aims to provide e-learning systems with an authentication approach that guarantees cheating-free summative e-assessment. It utilizes a combination of live video monitoring and a bimodal biometrics approach. Together they form a robust and highly secure model to ensure that the examinee is the correct person throughout the e-assessment period without a need for a proctor. Advanced techniques of image and video processing and feature extraction are required to implement this model.