AN ARCTIC ENVIRONMENT READINESS (AER) MODEL FOR QUANTIFYING THE IMPACT OF EXTREME ARCTIC WEATHER ON SYSTEM READINESS

The Arctic region offers significant opportunities for the U.S. military to expand its footprint, but the geographical location and harsh climate pose challenges to operational expansion in this region. To aid decision makers in assessing the impact of these conditions on readiness of equipment and the feasibility of operational expansion in the Arctic, this thesis develops an Arctic Environment Readiness (AER) model. A case study of a flotilla of ships is used to illustrate how the AER model can estimate readiness and to what degree various factors (such as logistic delay time, temperature, and the addition of a port) impact fleet readiness. The developed model is not only shown capable of quantifying and plotting fleet readiness along a specific route but also scalable and flexible. It can accommodate multiple variables to assess their impact on fleet readiness and allows investigation of requisite maintenance capabilities at a port, which can aid in optimizing port effectiveness and available resources. Although the developed AER model successfully uses a Design Structure Matrices approach to quantify readiness in the design and planning phases, it was limited by a lack of available operational data. With such data in follow-on work, a corresponding model could be developed for different weather conditions and operating environments.Military Expert 5, Republic of Singapore Air ForceApproved for public release. Distribution is unlimited

Assessing the Consequence of Cyber and Physical Malicious Attacks in Complex, Cyber-Physical Systems During Early System Design

This research contributes to the lifecycle assessment of complex cyber-physical systems (CCPSs) to better understand and mitigate risks of malicious attacks through design. This assessment capability is proposed during the early phase of engineering design where significant decision-making flexibility exists. This is done by assessing potential malicious attacks carried out by humans interacting with the system across all phases of the system’s lifecycle. We propose a novel quantifi- cation of an attacker-centric risk, then optimize the large set of attacks using a genetic algorithm. This research is motivated by the increased vulnerability of CCPSs due to their increasingly complex interconnected and digitally connected nature. A specific area of interest for CCPSs has been the increasing degree of connectedness. For example, several recent federal reports indicate that significant risk exists in the design of commercial aircraft where the entertainment system is connected to the avionics through a central network. The result is an increased ability to attack a specific subsystem or component to produce system failure. These findings, as well as others, have led to a significant concern with malicious attacks to target critical components of the CCPS. While assessments can be performed on a CCPS during the later phases of engineering design, techniques are currently not available during the early phase. We propose an assessment technique which is useful to practitioners during conceptual design. In this research, we assess a nuclear power plant as an example CCPS. The resulting methodology provides useful insight to the risks of malicious attacks throughout the system’s lifecycle.This research is partially supported by the Naval Post- graduate School (NPS) and the Finnish Research Pro- gramme on Nuclear Power Plant Safety 2018 (SAFIR2018, http://safir2018.vtt.fi)

ENERGY RESILIENCE IMPACT OF SUPPLY CHAIN NETWORK DISRUPTION TO MILITARY MICROGRIDS

The ability to provide uninterrupted power to military installations is paramount in executing a country's national defense strategy. Microgrid architectures increase installation energy resilience through redundant local generation sources and the capability for grid independence. However, deliberate attacks from near-peer competitors can disrupt the associated supply chain network, thereby affecting mission-critical loads. Utilizing an integrated discrete-time Markov chain and dynamic Bayesian network approach, we investigate disruption propagation throughout a supply chain network and quantify its mission impact on an islanded microgrid. We propose a novel methodology and an associated metric we term "energy resilience impact" to identify and address supply-chain disruption risks to energy security. A case study of a fictional military installation is presented to demonstrate how installation energy managers can adopt this methodology for the design and improvement of military microgrids.Outstanding ThesisLieutenant, United States NavyApproved for public release. Distribution is unlimited

Assessing the Consequence of Cyber and Physical Malicious Attacks in Complex, Cyber-Physical Systems during Early System Design

This research contributes to the lifecycle assessment of complex cyber-physical systems (CCPSs) to better understand and mitigate risks of malicious attacks through design. This assessment capability is proposed during the early phase of engineering design where significant decision-making flexibility exists. This is done by assessing potential malicious attacks carried out by humans interacting with the system across all phases of the system’s lifecycle. We propose a novel quantifi- cation of an attacker-centric risk, then optimize the large set of attacks using a genetic algorithm. This research is motivated by the increased vulnerability of CCPSs due to their increasingly complex interconnected and digitally connected nature. A specific area of interest for CCPSs has been the increasing degree of connectedness. For example, several recent federal reports indicate that significant risk exists in the design of commercial aircraft where the entertainment system is connected to the avionics through a central network. The result is an increased ability to attack a specific subsystem or component to produce system failure. These findings, as well as others, have led to a significant concern with malicious attacks to target critical components of the CCPS. While assessments can be performed on a CCPS during the later phases of engineering design, techniques are currently not available during the early phase. We propose an assessment technique which is useful to practitioners during conceptual design. In this research, we assess a nuclear power plant as an example CCPS. The resulting methodology provides useful insight to the risks of malicious attacks throughout the system’s lifecycle.This research is partially supported by the Naval Post- graduate School (NPS) and the Finnish Research Pro- gramme on Nuclear Power Plant Safety 2018 (SAFIR2018, http://safir2018.vtt.fi)