The oil and gas industry, a vital lifeline fueling the global economy, finds itself at a pivotal juncture where the convergence of operational technology (OT) and information technology (IT) has ushered in unprecedented opportunities and challenges. As digital transformation sweeps across this sector, the imperative to fortify cybersecurity defenses against ever-evolving threats has become paramount.
Innovative and forward-looking oil and gas organizations across the globe are adopting the cloud in many forms because of their digital transformation initiatives. Data lakes, edge technology, machine-to-machine communication, and machine learning (ML) algorithms have been enabling this industrial digital transformation. This transformation is also driving changes to the OT landscape, and, as these environments continue to evolve, OT environments are leveraging well-proven IT solution patterns to improve the productivity and efficiency of production operations.
Industrial customers often start their digital transformation journey by sending OT data to the cloud for analysis and analytics without sending commands back to the industrial automation and control systems. This process is often called “open loop” operations because there is one-way communication from edge to cloud. Customers generally find this relatively easy to secure and manage.
More often, however, we are witnessing requirements to optimize operations by generating an automatic or operator-initiated response in the oil and gas production operation, rig management based on insights gained from cloud analytics. This process is often referred to as “closed loop” operations with two-way communication between edge and cloud. The security and compliance practices for closed-loop operations are more rigorous because closed operations manipulate OT devices remotely. Developing these practices should be rooted in a cyber risk assessment to help businesses understand and prioritize security concerns.
This paper proposes how the strengths of cloud computing can become key enablers for oil and gas organizations in helping them enhance their overall security posture and manage risks within OT environments. Solution patterns described in this paper have been deployed as the foundational pillar of several oil and gas organizations’ overall OT system architecture to unlock both open-loop and closed-loop operations in a secure, reliable, and cost-effective manner.
The specific scope items covered in this paper focus on a custom security uplift framework with the following four foundational components:
- Cloud-led architecture patterns to provide next-generation network segmentation strategies in an OT demilitarized zone
- OT asset inventory and vulnerability management
- Centralized security monitoring and incident response with the help of artificial intelligence (AI), most recently providing a generative-AI-based virtual assistant to query security event data from OT systems
- Security maturity model and project-execution best practices
The case studies discussed in the paper highlight how customers have been able to remediate critical security vulnerabilities within weeks after implementation by deploying a comprehensive asset inventory discovery and vulnerability assessment. This has helped reduce mean time to identify and mitigate vulnerabilities from months to days with automated testing in preproduction environments; ensure quick detection and response toward security incidents with the help of advanced security monitoring and incident response playbooks, covering 100% of the OT assets through this capability; and leverage advanced data analytics and machine learning to perform log mining, data cleansing, data validation, log mining, and analysis through natural language processing such as conversational AI assistants powered by large language models in the cloud.