Description:
OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Advanced Computing and Software;Trusted AI and Autonomy
The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
OBJECTIVE: Research and identify the Publicly Available Information (PAI) military units leave behind as a result of using commercial entities to support military operations. Assess if a potential adversary could use that information to target military units to delay, disrupt or degrade US military capabilities and intentions. Unclassified data includes locations & details of military assets, capabilities, & plans for upcoming operations. While this information may not be classified, it can still be used by adversaries to gain an advantage, such as by preparing for an attack or developing countermeasures to US military capabilities. PAI as a result of dependencies on contracted commercial entities generates a significant amount of unclassified information.
DESCRIPTION: Since the mid-1990s the US military has become increasing reliant on contracted support from commercial entities with Operation Desert Storm being the last major military operation with a predominance of support from military units. The DoD projects that contractors will provide most of the support to future major military operations. Coordination for this support requires communication and transmission of militarily relevant information on unclassified commercial systems and this represents a potential military vulnerability. Joint doctrine directs planners to consider contractors as “forces available” for military operations and in some cases supplanting military logistics forces. This can relieve the US strategic transportation system of the burden of transporting military logistic units into a theater of operations in lieu of combat forces. If planners can expect to contract for heavy equipment transport trucks in theater, then they can plan to move more combat units into theater earlier in the plan. In addition, contractors are often used to fill gaps in military capabilities, provide additional expertise, or to augment the military's capacity to respond to emerging threats. Contractors provide a wide range of support services, such as logistics, transportation, construction, and maintenance, as well as technical and professional services, such as engineering, IT, and intelligence support. They also provide support for functions such as catering, laundry, and other services that are required to sustain military personnel in an operational environment. These activities occur alongside military personnel executing classified missions. Even if the contractor had no knowledge the actual military mission, their presence, and the signals they generate in the environment could provide a discernable pattern that an innovative adversary could use to derive the capabilities and intentions of the US military. This research intends to determine the feasibility of developing a capability for military units to assess the type of pattern that their Publicly Available Information (PAI) creates and if it represents a risk to military operations.
PHASE I: Period of performance objectives are: 1. Conduct a thorough analysis of the types of Publicly Available Information (PAI) generated by military units in receiving support from commercial entities. Include a review of existing datasets, software solutions and technical requirements. 2. Developing a detailed software design document that outlines the architecture, features, and functionality of a proposed solution. 3. Describe a proof-of-concept prototype of the software, which could include a minimum viable product (MVP) or a demo version of the software. 4. Develop a plan for conducting user testing and gathering feedback on the prototype to evaluate its usability and identify areas for improvement. 5. Develop a plan to conduct market research to assess the potential demand for the software, identify potential customers and competitors, and estimate the size of the target market. USE CASES to analyze feasibility, a proof of concept will eventually be able to demonstrate these capabilities, using real or “realistic” fictitious data.
1. UNIVERSAL INTROSPECTION: a commander with sufficient role-based access, should be able to traverse data in the system to understand time, location, co-location, disposition, etc, of their people & assets … a) Doctrinal: does the adversary know our staging location preferences per a type of, or specific objective? b) Plan: does the adversary know our primary COA for placement of assets? c) Execution: our adversary’s able to detect friendly locations in real-time d) Report: our adversary knows our own friendly account of where an asset was e) Lessons Learned: the adversary’s perception of our measure of success f) Rewrite: our adversary’s estimation on our plans to change based on past
2. OPSEC VISUALIZATION: Military operations are increasingly vulnerable to adversary detection due to exploitation of publicly available and open-source data. Currently the military has very few if any tools to allow military units to “see themselves” in the PAI and OSINT environment, especially as it applies to the use of contracted commercial entities. In 2020 a US Army opposing force (OPFOR) commander gave a US Army Brigade Combat Team (BCT) a visualization of their electronic signature on a simulated battlefield, as shown in “This is What Ground Forces Look Like to an Electronic Warfare System” (https://www.thedrive.com/the-war-zone/33401/this-is-what-ground-forces-look-like-to-an-electronic-warfare-system-and-why-its-a-big-deal) The BCT conducting the training was conducting its operations as intended by US Army doctrine and policy. The unit was camouflaged per standard operating procedure and in a tactical posture to avoid detection from the known means of adversary collection. Even so, the BCT was lit up like a Christmas tree in the electronic spectrum and thereby detectable to an adversary with the capability to collect in that spectrum. The signals from the BCT were attributed to unit equipment with modern features required to survive in the operational environment. They were also attributed to active radars and communications systems required to operate a brigade headquarters. Even so, the very equipment necessary for a decisive battlefield advantage also had a significant and heretofore previously unknown or unappreciated downside. Likewise, and because of the dependency on contracted commercial entities, military units may be emitting a signature in the PAI and OSINT environments that is equally detectable by an innovative adversary. These same military units may not be aware of these signatures even though they are utilizing their contracted commercial support in accordance with doctrine and policy. This research intends to relook OPSEC paradigms and investigate the potential for novel data-system design and operationalize OPSEC by allowing military units to see their signatures in the PAI and OSINT environments.
3. BIG DATA ANALYSIS: This call is for a system that not only looks inward for a rich detailed friendly force picture but provides the full range of user functions surrounding the lifecycle of that data: from doctrinal templates, to plans, execution, reporting, lessons learned, & semi-automatically implementing numerical tweaks to doctrinal templates based on the deficiency findings in lessons learned. This is a functional big data approach to providing streamlining automations on internal data. Big data analysis of external data classically requires faulty human analysis. A corresponding match of all-encompassing consolidated internal data, combined with external data & analytic models, provides widely accessible & interactive OPSEC cueing.
PHASE II: Phase II awardees will develop the proof-of-concept prototype described in the software design document developed during the Phase I. Once the prototype has achieved a minimum viable product (MVP) awardee will begin conducting user testing with warfighters such as planners at Pacific Air Forces (PACAF) or other Major Command (MAJCOM). User testing will include gathering feedback on the prototype to evaluate its usability and identify areas for improvement. MVP will preferably be delivered in the python program language and should be able to demonstrate the USE CASES define in the Phase I; 1. UNIVERSAL INTROSPECTION 2. OPSEC VISUALIZATION 3. BIG DATA ANALYSIS
PHASE III DUAL USE APPLICATIONS: Phase III awardees will have a proof-of-concept prototype that has completed user testing in an operational warfigher environment such as an exercise held by Pacific Air Forces (PACAF) or other Major Command (MAJCOM) resulting in a TRL 7 at entry. Phase III will focus on transitioning the developed technology to multiple warfighting organizations across the Department of Defense through final refinements required to be accepted into a targeted System of Record (SoR) at TRL 9.
REFERENCES:
1. This is What Ground Forces Look Like to an Electronic Warfare System” (https://www.thedrive.com/the-war-zone/33401/this-is-what-ground-forces-look-like-to-an-electronic-warfare-system-and-why-its-a-big-deal)
KEYWORDS: Contested Logistics; OPSEC; operational contract support (OCS); contractors authorized to accompany the force (CAAF); data centric; data system schema design
