ICS Security: Thinking outside the Cybersecurity. "Box"
Operational Technology Behavioral Analytics: Decoding the Patterns of Industry
While the concept of "behavior" often finds itself restricted to biological entities, in the realm of ICS, every machine, system, and process exhibits its unique pattern of operation. This consistent operational rhythm, derived from historical data and enriched with domain-specific insights, forms the cornerstone of Operational Technology Behavioral Analytics (OTBA). By decoding and understanding these patterns, industries could unveil a potent tool to detect anomalies and secure their operations against potential cyber threats.
Understanding the Core:
Behavioral Analytics, at its heart, is an intricate dance of data. It leverages vast historical datasets to establish a baseline for "normal" operational behavior. Domain expertise is then folded into this data-driven model, refining it to predict the expected behavior of machines, processes, or systems under varying conditions.
For instance, a data-driven behavioral model for a steel furnace might incorporate years of operational data, including how the furnace reacts under different temperatures, raw material quality, and ambient conditions. With this model in place, if the furnace starts behaving anomalously—say, taking longer to reach a temperature or consuming more energy than predicted—it could raise red flags.
Simple yet Illustrative Examples and Applicability:
Manufacturing Line Speed: If a manufacturing line historically produces 100 units per hour under certain conditions, and suddenly drops to 70 without any discernible changes in those conditions, it could signify a potential system compromise.
Energy Consumption Patterns: Electrical grids or individual machines have typical energy consumption patterns. Unexplained surges or drops in energy usage, when not aligned with known operational changes, might indicate a cyber intrusion.
Machinery Wear Rate: Machines have a predictable rate of wear and tear based on usage. If maintenance issues arise more frequently than past data suggests, it could hint at either operational issues or malicious tampering.
Supply Chain Consistency: If a supplier typically delivers materials within a specific time frame, unexpected and unexplained delays might not just be logistical issues but could also signify data breaches or cyber-attacks on logistical planning systems.
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Benefits and Challenges:
The prowess of Behavioral Analytics lies in its proactivity. By understanding what 'normal' looks like, industries can quickly identify deviations, enabling timely interventions. This methodology, being deeply rooted in data, also offers precision, thereby reducing false positives. I also believe this will play nicely into the overall enterprise risk metrics when tied to the IT User and Entity Behavioral Analytics (UEBA)?systems.
One of the lessons learned about using AI/ML to parse through the data is this annotation:
“While statistical analysis and machine learning provide valuable information, deep learning can be used to provide even greater insights. Characteristics and behaviors that are not easily detected can be brought to light. Deep learning techniques explore hidden relationships and allow automated feature learning. This approach moves us closer to true artificial intelligence.”
The study also notes "Network visibility was achieved by configuring switch span ports from critical physical interconnection points and then consolidating all traffic streams to a single aggregation device." (Black, et al, 2022) I would propound that this study and Deep learning may have benefited from tapping directly into the asset’s configurations through the use of a Configuration Management Database (CMDB) for OT while augmenting the network traffic data.
Some challenges with OTBA may persist. The sheer volume of data required can be daunting, and ensuring its quality and relevance is paramount. Tuning alone could become an art and career choice. Additionally, while deviations might indicate potential threats, they could also signify evolving operational processes, necessitating a constant refinement of the behavioral models. That oversight could also become a potential opportunity to serve as an OT Cyber Defender. As advancements in OT-specific cybersecurity TTPs continue to expand, and OT Cybersecurity disciplines are widely defined and adopted within the industry, so do career opportunities aboard the OT Cybersecurity carrier group.
With vast potential, within the sea of industry, OTBA could stand as a vigilant Captain, attuned to the slightest vibration, undercurrent, or ship’s shutter. As cyber threats grow in frequency and sophistication, the armada of synchronized data and domain knowledge might just be the additional cyber defense, that helps shelter operations to a secure port.?
Wow… Well done! This study and concept deserve a Bravo Zulu!
Coolest thing since the beginning of frozen things.