Towards a Model for Zero Trust Data

Abstract

The world has realized traditional cybersecurity models are flawed because users and systems behind the perimeter are implicitly trusted. The response has been to treat access requests and behaviors post-access as untrusted. Thus, the aim of such zero trust architecture is to establish a borderless access-control framework. Accordingly, existing research is centered around network perimeters and communications layers. That is, data access channels or endpoints and not data itself. Consequently, we conducted a systematic review of relevant literature and developed a model illustrating a potential application of zero trust tenets and principles to data objects instead of data access pathways based on the findings. Concurrently, given the rising popularity of employing artificial intelligence to zero trust frameworks, our zero trust data concept targets artificial intelligence training and real-world evaluation data segments.