Trade Secret Protection in Corporate Information Flows: From “Reasonable Steps” to Evidence-Ready Digital Governance

Abstract

Corporate information flows have become the primary environment in which economically valuable knowledge is created, refined, exchanged, and stored, increasingly via cloud collaboration and multi-platform work practices. As a result, many high-value intangibles are protected less by registration and more by sustained confidentiality governance that can be proven in dispute settings. This article develops an evidence-oriented governance model for protecting trade secrets in corporate information flows by translating legal protectability criteria into lifecycle controls, role responsibilities, and remedy-ready documentation. The study applies doctrinal analysis of trade secret standards under TRIPS and the EU Trade Secrets Directive, complemented by a structured review of governance-oriented guidance on “reasonable steps” and by synthesis with contemporary cybersecurity governance frameworks. We then map legal elements to operational controls, define an evidence readiness pack, and contextualize the model with recent threat and breach-cost statistics. The results show that trade secret enforceability depends on continuity of controls across the information lifecycle, not on isolated legal declarations. The strongest operational posture combines: legal routing and asset tiering, least-privilege access and controlled sharing pathways, third-party boundary controls, and incident-time legal hold and reproducible proof artifacts. Empirical indicators underscore scale pressure: the global average cost of a data breach reached USD 4.88 million in 2024, while compromised credentials remained a major initial access vector in recent breach datasets. Future research should validate sector-specific indicator sets against incident datasets, test which evidence artifacts most influence remedy outcomes, and examine how AI-enabled workflows reshape confidentiality boundaries and “reasonable steps” expectations.