Model Based System Engineering Improves Ship Security Decision Making

The Challenge

One of the challenges facing the U.S. Navy today is maintaining a ship’s comprehensive cybersecurity from stern to bow, and doing so with limited resources. Historically, in order to test a ship’s cybersecurity, the U.S. Navy had two options – either test against an in-service ship, or create a replica of each ship class to test against. The first option presents risk because testing against an in-service ship could expose the ship itself to damage; but creating a replica ship is very costly. 

The Solution

Life Cycle Engineering helped meet the Navy’s directive of better, faster, cheaper, while ensuring ship security. Our cybersecurity and software engineers designed a tool that creates a virtual model of a ship, stern to bow, including all Platform IT systems, versions, and known vulnerabilities. Our SMEs then ran a series of simulated attacks against the virtual model to gathered data on any security risk areas. We assessed the risks and were able to provide the customer with recommendations to best focus their limited resources to secure the ship. 

LCE’s solution leverages model-based systems engineering techniques to assess the cybersecurity posture of ships’ systems and networks. The tool allows the user to provide stimuli to the model to analyze the impacts of this stimuli. The results allow the user to better understand the effects of the compromise of a shipboard system, allowing for better use of limited funding to resolve security vulnerabilities. Our efforts include developing and implementing plans for adding new ship classes, developing concepts for modeling components and combinations of components and systems to support the evaluation of mission impacts from vulnerabilities, and creating the initial controlled vocabularies for hull, mechanical, and electrical (HM&E) systems.

The Results

LCE’s model allows the Government to run various scenarios in a virtual environment, which:

As an added benefit, these virtual models can also be used to manage the configuration management of the PIT systems.