USING NETWORK MOTIFS TO SEARCH FOR INDICATORS OF MALIGN FOREIGN ACTIVITIES IN SOCIOTECHNICAL NETWORK MODELS

The vast majority of critical infrastructure (CI) research studies vulnerabilities to system disruption via disaster or attack. However, few studies assess the social networks and businesses that own and operate CI for potential adversarial influence and fraud. For example, if an adversary wishes to access a well-defended system, they could forgo an attack and use legitimate business practices such as mergers, hostile takeovers, and foreign investment to gain access. This work aims to develop analytical techniques that can identify these vulnerabilities. We access and combine three different public data sources to create network models of the people and organizations surrounding CI. Then, we develop a technique using motifs to search the networks for common structural markers that a near-peer adversary uses to influence businesses. We apply our technique to networks generated for the electric vehicle charging industry. Our results indicate that motifs are a simple and effective way to search large networks for indications of malign influence. This work serves as a proof-of-concept that will enable the creation of automated investigative tools to identify and deter foreign and malign influence in emerging CI systems.

Department dc:contributor.department

Operations Research (OR)

Grantor dc:publisher

Monterey, CA; Naval Postgraduate School

Year dc:date.issued

2024

Author dc:creator

• Shannon, Ryan A.

Advisor dc:contributor.advisor

• Eisenberg, Daniel

Statement dc:rights

• This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.

Handle dc:identifier.uri

https://hdl.handle.net/10945/73368

OAI identifier oai:identifier

oai:calhoun.nps.edu:10945/73368