CRAIApr 16, 2019

Helping IT and OT Defenders Collaborate

arXiv:1904.07374v1
Originality Synthesis-oriented
AI Analysis

This addresses collaboration challenges for defenders in critical infrastructures, but it appears incremental as it builds on existing interview insights and notional solutions.

The paper tackles the problem of coordinating detection and response between IT and OT defenders in cyber-physical systems, proposing a visualization tool and a machine-learning approach to estimate system safety during intrusions.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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