IW4500 Information Warfare Systems Engineering

Information Warfare Systems Engineering

This course is designed to equip Department of War (DoW) United States Marine Corps (USMC) officers with the specialized systems engineering and mission engineering skills required to conceive, develop, and integrate systems for Information Warfare (IW). By combining rigorous systems engineering principles with a mission-focused approach supported by the principles of mission engineering, this course will prepare officers to build and deploy capabilities that achieve information dominance and decision advantage in a contested battlespace.

Students will begin by establishing a foundation in systems thinking as it applies to the unique, non-kinetic, and often intangible nature of the information environment. Students will then master the Systems Engineering Concept Development Phase, learning how to translate a commander's intent for information dominance into technical requirements for C5ISR, cyber, electronic warfare, and influence-related systems.

A critical focus of this course is the direct integration of Mission Engineering with the IW systems engineering process. Students will learn to architect and align technical IW solutions with strategic information objectives, ensuring engineered systems produce desired effects on adversary perception, decision-making, and technical capabilities.

The course provides a robust set of analytical tools to support decision-making in this complex domain. Student will learn to apply Critical Path Analysis to deconstruct and analyze information-centric mission threads and cyber kill chains. Furthermore, student will gain hands-on experience with a variety of modeling and simulation techniques relevant to IW challenges, including:

Causal Loop Modeling: To map the feedback structures of influence campaigns and network effects.
Linear Programming: For optimizing the allocation of resources
Regression Modeling: To analyze relationships between information activities and observed adversary behaviors.
Monte-Carlo Simulation: To model and assess the probable outcomes of IW operations under conditions of uncertainty.
Probabilistic Modeling: To quantify and manage uncertainty in intelligence assessments and predict adversary actions.

Upon completion of this course, you will be equipped to lead and contribute to the design, development, and integration of complex Information Warfare systems that directly support the USMC's ability to fight and win in the information environment.

Prerequisite

IW3101

Lecture Hours

Lab Hours

Course Learning Outcomes

Systems Thinking and Fundamentals

Outcome ID	Learning Outcome
1.1	Define systems thinking and articulate, in writing,threekey principles and their direct implications for DoW systems engineering challenges.
1.2	Analyze a DoW-relevant case study and identify at leastfivesystemic issues, distinguishing between symptoms and root causes.
2.1	Given a notional operational need, develop a preliminary system concept document that correctly identifies all primary stakeholders, the system boundary, and at leastfiveobjectives high-level functional requirements.

Mission and Systems Engineering Integration

Outcome ID	Learning Outcome
3.1	Author a Concept of Operations (CONOPS) that explicitly integratestwoMission Engineering principles into the Systems Engineering Concept Development Phase for a given scenario.
3.2	Evaluate a system design proposal and provide a written critique identifying its alignment (or misalignment) with at leastthreestated operational mission goals.

Analytical Application

Outcome ID	Learning Outcome
4.1	For a given mission thread, apply Critical Path Analysis to correctly identify the sequence of critical tasks, calculate the total duration, and identifytwopotential chokepoints.
5.1	Construct a causal loop diagram for a complex operational problem that accurately depicts at leasttworeinforcing loops andtwobalancing loops.
5.2	Formulate and solve a linear programming problem with at leastthreeconstraints to determine the optimal allocation of resources for a given logistics or operational scenario.
5.3	Using a provided dataset, perform a linear regression analysis to create a predictive model and use it to forecast a specific outcome with a quantifiable margin of error.
5.4	Design and execute a Monte-Carlo simulation with a minimum of1,000 iterationsto assess the probability of mission success under conditions of uncertainty and apply it to critical path risk analysis.
5.5	Apply a probabilistic model to a given intelligence scenario to update the likelihood of an event occurring based on new information.