Helping IT and OT Defenders Collaborate

TL;DR

This paper explores the communication and coordination challenges between IT and OT defenders in cyber-physical systems, proposing visualization and machine learning solutions to improve collaboration and safety assessment during cyber incidents.

Contribution

It introduces a visualization tool and a machine learning method to enhance collaboration and safety estimation between IT and OT defenders in cyber-physical systems.

Findings

Proposed a visualization to facilitate IT and OT communication.

Developed a machine learning approach to estimate system safety state.

Addressed coordination challenges in cyber-physical security.

Abstract

Cyber-physical systems, especially in critical infrastructures, have become primary hacking targets in international conflicts and diplomacy. However, cyber-physical systems present unique challenges to defenders, starting with an inability to communicate. This paper outlines the results of our interviews with information technology (IT) defenders and operational technology (OT) operators and seeks to address lessons learned from them in the structure of our notional solutions. We present two problems in this paper: (1) the difficulty of coordinating detection and response between defenders who work on the cyber/IT and physical/OT sides of cyber-physical infrastructures, and (2) the difficulty of estimating the safety state of a cyber-physical system while an intrusion is underway but before damage can be effected by the attacker. To meet these challenges, we propose two solutions: (1) a visualization that will enable communication between IT defenders and OT operators, and (2) a machine-learning approach that will estimate the distance from normal the physical system is operating and send information to the visualization.