The EU-funded TeSLA project -- Adaptive Trust-based e-Assessment System for Learning (http://tesla-project.eu) -- has developed a suite of instruments for e-Authentication. These include face recognition, voice recognition, keystroke dynamics, forensic analysis and plagiarism detection, which were designed for integration within a university's virtual learning environment. These tools were trialed across the seven partner institutions: 4,058 participating students, including 330 students with special educational needs and disabilities (SEND); and 54 teaching staff. This paper describes the findings of this large-scale study where over 50% of the students gave a positive response to the use of these tools. In addition, over 70% agreed that these tools were "to ensure that my examination results are trusted" and "to prove that my essay is my own original work". Teaching staff also reported positive experiences with TeSLA: the figure reaching 100% in one institution. We show there is evidence that a suite of e-authentication tools such as TeSLA can potentially be acceptable to students and staff and be used to increase trust in online assessment. Also, that while not yet perfected for SEND students it can still enrich their experience of assessment. We find that care is needed when introducing such technologies to ensure building the layers of trust required for their successful adoption.