Visible to the public ACE: Advanced CIP Evaluator

TitleACE: Advanced CIP Evaluator
Publication TypeConference Paper
Year of Publication2018
AuthorsGordon, Kiel, Davis, Matthew, Birnbaum, Zachary, Dolgikh, Andrey
Conference NameProceedings of the 2018 Workshop on Cyber-Physical Systems Security and PrivaCy
PublisherACM
ISBN Number978-1-4503-5992-4
Keywordscommon industrial protocol, industrial control systems, passive network analysis, pubcrawl, resilience, Resiliency, Scalability, scalable
Abstract

Industrial control systems (ICS) are key enabling systems that drive the productivity and efficiency of omnipresent industries such as power, gas, water treatment, transportation, and manufacturing. These systems consist of interconnected components that communicate over industrial networks using industrial protocols such as the Common Industrial Protocol (CIP). CIP is one of the most commonly used network-based process control protocols, and utilizes an object-oriented communication structure for device to device interaction. Due to this object-oriented structure, CIP communication reveals detailed information about the devices, the communication patterns, and the system, providing an in-depth view of the system. The details from this in-depth system perspective can be utilized as part of a system cybersecurity or discovery approach. However, due to the variety of commands, corresponding parameters, and variable layer structure of the CIP network layer, processing this layer is a challenging task. This paper presents a tool, Advanced CIP Evaluator (ACE), which passively processes the CIP communication layer and automatically extracts device, communication, and system information from observed network traffic. ACE was tested and verified using a representative ICS power generation testbed. Since ACE operates passively, without generating any network traffic of its own, system operations are not disturbed. This novel tool provides ICS information, such as networked devices, communication patterns, and system operation, at a depth and breadth that is unique compared with other known tools.

URLhttps://dl.acm.org/citation.cfm?doid=3264888.3264891
DOI10.1145/3264888.3264891
Citation Keygordon_ace:_2018