Zero Trust for Integrated Data Science


Zero Trust is a strategic approach in security by eliminating implicit trust and continuously validating every stage of a digital interaction. Originating from cyber it is valuable and modern approach to also apply it to data and algorithm management and governance.

In this talk, I will explain what Zero Trust Architecture is, which problems in data science it solves and how you could implement this into DataOps and MLOps processes. Furthermore, I will connect the concepts to the GDPR and the new/ proposed AI Act and use concrete examples from my projects in cyber security, banking and retail.

The key concepts from Zero Trust Security are conditions and controls, to create a continuous context-aware security model for real-time risk based validation. For example, for a process where humans interact with computer systems this creates a security model that controls access or requires multi-factor authentication in specific scenarios. Applying Zero Trust to data-driven processes is less trivial, because it requires identity propagation which is typically broken in a micro-serviced model landscape. Exploiting latest advances in data lineage, version control and CI/CD tooling one can create a Zero Trust Data & Algorithm Architecture.


Dr. Casper Rutjes is Chief Technology Officer (CTO) at ADC (Amsterdam Data Collective), a Data & AI Consultancy in Europe. Rutjes is responsible for R&D, (Tech) Partnerships, consulting quality & standardization and IT. He leads global teams of consulting specialists in the areas of strategy & innovation, data engineering and data science across our key industries, mainly healthcare/life science, public and finance. At clients he is a trusted advisor and senior project lead for challenges on the interface of regulation, IT and business.

Open Data Science




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