Hyperdimensional Neurosymbolic Cyber Course-of-Action Planning and Replanning under Deception

SBIR · Phase: BOTH · Topic DPA27BZ02-DV001 · Solicitation 27.BZ

Future cyber operations will be conducted in contested environments in which observations are incomplete, timing is compressed, adversaries actively manipulate defender beliefs, and the state of the mission cannot be fully observed from any single node or operator position. In such settings, success depends not only on detecting malicious behavior, but on understanding what actions remain feasible, what dependencies govern those actions, which alternatives best satisfy mission objectives, and how plans should be revised as assumptions fail or new opportunities emerge. Current cyber tools do not adequately support this planning problem. Many existing capabilities focus on alerting, anomaly scoring, static attack-path enumeration, or post hoc analytics. These functions are valuable, but they do not provide operators with an integrated capability to construct, compare, and revise cyber COAs as the environment changes. Rule-based playbooks can be brittle under novelty and obfuscation. Optimization and reinforcement-learning approaches may generate recommendations but often provide limited interpretability and can be difficult to adapt when observations are sparse, manipulated, or only partially relevant. Large-model assistants may accelerate interaction, but by themselves do not provide a persistent, auditable, machine-interpretable planning state suitable for operational use. This topic seeks a new class of cyber planning technologies built around hyperdimensional, vector-symbolic, neurosymbolic, or closely related compositional reasoning methods. Of particular interest are approaches that maintain explicit internal representations of cyber objectives, prerequisites, access dependencies, branching opportunities, constraints, anticipated adversary reactions, and uncertainty in forms that are robust, updateable, and inspectable by both machines and operators. Hyperdimensional and related high-dimensional symbolic representations are of interest when they enable compact encoding of structured cyber context; efficient binding of entities, roles, temporal order, and dependencies; similarity-based retrieval across partially matching situations; graceful degradation under incomplete or deceptive observations; and deployment in resource-constrained or communications-constrained environments where retraining-heavy or centralized approaches are poor fits. This topic seeks prototype capabilities that support cyber COA planning and replanning as structured decision processes rather than static checklists. Desired systems should represent plans through inspectable mission graphs, task webs, tiled workspaces, or comparable compositional artifacts in which each element captures sub-objectives, preconditions, dependencies, candidate actions, supporting evidence, uncertainty, timing, cost, reversibility, and mission relevance. The system should generate multiple feasible COAs for a stated objective, compare alternatives using explicit decision criteria, identify key assumptions and information gaps, and recommend revisions when new evidence changes branch viability or reveals newly feasible options. A responsive solution should not treat hyperdimensional or neurosymbolic reasoning as novelty for its own sake. Instead, the proposer should clearly show how the chosen representation materially improves cyber planning performance in one or more of the following ways: • compact encoding of evolving cyber context and plan structure without exhaustive recomputation; • compositional updates as new observations, constraints, or objectives arrive; • retrieval of relevant prior plan fragments or analogous situations under partial mismatch; • maintenance of competing plan branches or hypotheses under obfuscation and ambiguity; • lightweight exchange of decision-relevant symbolic or semantic representation among distributed agents or operator cells; • interpretable rationale linking recommended actions to plan structure, assumptions, and uncertainty. Represe…

SBIR/STTR 은 미국 중소기업만 지원할 수 있습니다(Small Business Act 법정 요건). • 계열사를 포함해 상시 종업원 500명 이하 • 미국 시민 또는 영주권자 1인 이상이 50%를 초과해 직접 소유·지배 • 미국 내 사업장을 두고 주로 미국 내에서 사업을 영위할 것 • 수행책임자(PI)의 주된 근무처가 신청 기업일 것 출처: https://www.sbir.gov/faq/eligibility-requirements

Primary country

🇺🇸 United States

Also eligible

None

Foreign companies

No

Local entity

Required

Location condition

미국 내 사업장을 두고 미국 시민·영주권자가 50%를 초과해 소유한 중소기업만 신청할 수 있습니다(법정 요건).

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Official URL

https://www.dodsbirsttr.mil/topics-app/

Application URL

https://www.dodsbirsttr.mil/topics-app/

Last fetched

2026.11.06

Human review

Not reviewed — check the official announcement

First seen

2026.11.06

Data status

Auto-collected, not reviewed

AI enrichment

Needs verification