Zero-Tolerance Security Paradigm for Enterprise-Specific Industrial Internet of Things

Abstract

The complex industrial environment of the 21st century is equipped with the Internet of Things platform, with the objective of real-time operational visibility, improved device management and predictive maintenance. To unleash the focused importance of its policy, a secure connectivity must be realized through a range of existing and dissimilar devices and data sources. During the conceptualization phase, the authors aimed to compel the following: (a) that restriction of access should be based on the presence of unexpected device actions that may point to a security breach, and (b) ensure the safety of the system by constant tracking of connected devices and data. In this paper, a policy-driven, zero-trust defense model is proposed to address numerous vulnerable entry points, validate device access to legitimate enterprise functions, quarantine unsecure devices, and trigger automated warnings and policy validation for hardware, software, network connectivity and data management. To handle active scanning, bots, passive auditing, outbound threat management, and device interconnections, an experimental environment was put up. This environment provides holistic visibility and a persistent view of all resources, including those that were previously unknown. A steady stream of reliable and authenticated data has helped to develop and adjust a scalable implementation strategy by avoiding recognized anomalous traps. Actual data was aggregated and analyzed to assess the proposed methodology. Comparative analysis of ‘device exposure view, attack path analysis, controlled view of devices, comprehensive vulnerability evaluation, and effective communication of cyber risk’ has proved the effectiveness of the proposed methodology.