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Data Governance & Ethics Framework

ISS LLC / SecureAssure Platform Governance Documentation | Zero-Trust | CMMC 2.0 Level 2 | NIST CSF 2.0 | Last Updated: March 2026

1. Data Governance Charter

Purpose

This charter establishes the principles, policies, and procedures governing the collection, processing, storage, and sharing of data across all SecureAssure products (SHIELD PWA and ATLAS platform). Built on zero-trust architecture with MOSA-compliant data governance and mission-based cyber risk assessment (DoWM 5000.103). Our commitment is to responsible data stewardship that prioritizes user safety while respecting privacy and civil liberties. CMMC 2.0 Level 2 compliant.

Principles

2. Privacy Impact Assessment Summary

Data Collection Matrix

Data TypePurposeStorageSharingUser Control
GPS LocationSafeWalk, panic alerts, geofencingLocal device only (unless shared via panic)Emergency contacts only on triggerPermission toggle, per-session
AccelerometerFall detection, gait analysisLocal device onlyNever sharedFeature toggle
MicrophoneSmokeGuard (3-4kHz alarm detection)Not recorded; frequency analysis onlyNever sharedPermission toggle
BluetoothTracker detection (AirTag, Tile, etc.)Scan results stored locally 24hNever sharedPer-scan activation
Network InfoTravelSafe, signal monitoringLocal device onlyNever sharedFeature toggle
Interaction MetricsCognitive overload protectionLocal device only (localStorage)Never sharedFull purge via Data Dashboard
Community ReportsCrowdShield safety intelligenceServer (PostgreSQL, 365-day retention)Anonymized to communityAnonymous submission, no PII
Phone/URL ReputationMisinformation filter, trust layerServer (crowd-sourced database)Aggregated scores onlyVoluntary reporting
No biometric data is stored. Gait analysis computes cadence averages locally. Audio analysis extracts frequency patterns without recording. Bluetooth scans identify device signatures without pairing.

3. Abuse Prevention Framework

CrowdShield Moderation System

The community reporting system (CrowdShield) implements multiple layers of abuse prevention:

Rate Limiting

Maximum 10 reports per hour per IP address. Prevents spam flooding and automated abuse. Rate limits applied at the API gateway level.

Community Voting

Reports are subject to upvote/downvote by the community. Trust scores calculated as (upvotes - downvotes). Higher-scored reports surface; low-scored reports suppressed.

Automatic Flagging

Reports automatically flagged when: 3+ downvotes received AND downvotes outnumber upvotes by 3:1 ratio. Flagged reports removed from active feed.

IP Tracking

Reporter IP addresses recorded (not displayed publicly) for abuse investigation and potential IP-level blocking of persistent bad actors.

Misinformation Filter Governance

4. Ethical Use Policy

Permitted Uses

Prohibited Uses

Violation Consequences: Users who violate the ethical use policy are subject to IP-level rate limiting, report flagging, and potential platform access restriction. False community reports are a violation of the Terms of Service.

5. Liability & Disclaimers

6. Third-Party Data Handling

Third PartyData FlowPurposeUser Data Shared
NASA FIRMSInbound onlyActive fire detectionNone
USGSInbound onlyEarthquake monitoringNone
NOAA NWSInbound onlyWeather alertsNone
FEMAInbound onlyDisaster declarationsNone
CISAInbound onlyCyber threat intelligenceNone
StripeBidirectionalPayment processingEmail, payment info (Stripe-managed)
CDC PLACESInbound onlyCommunity health dataNone
US CensusInbound onlySocial vulnerability indexNone
All federal data feeds are public APIs with no authentication required. No user data is transmitted to any federal agency. Stripe handles payment data under PCI DSS Level 1 compliance; SecureAssure never stores credit card numbers.

7. Community Moderation Board

Structure

As the platform scales, SecureAssure will establish a Community Safety Advisory Board with the following composition:

Board Responsibilities

8. Civilian/Defense Separation Governance

SecureAssure maintains strict separation between civilian and defense capabilities:

Default Mode: Civilian Resilience

All users see only civilian MOSA-compliant modules by default. No military terminology, no defense-specific features, no restricted content. This is the platform as presented to investors, grant reviewers, and the public. FEMA/NIMS aligned.

Defense Mode: Zero-Trust Access-Gated

Defense capabilities require zero-trust authentication via zero-trust access gate. JADC2-aligned, DDIL-capable. When activated, the interface clearly labels the operating mode. Defense features are additive with full-stack congruence; they do not modify civilian data or workflows. CMMC 2.0 Level 2 compliant.

Data Isolation & Congruent Architecture

Civilian and defense operations share MOSA-compliant infrastructure with zero-trust logical data separation and full-stack congruence. Defense-specific data (tactical overlays, mission plans) is stored in separate namespaces. Mission-based cyber risk assessment (DoWM 5000.103) governs classification boundaries.

Documentation

All public-facing documentation, marketing materials, grant applications, and investor communications use civilian framing exclusively. Defense documentation is maintained separately and distributed only to authorized stakeholders.

9. AI Governance & Federated Machine Workforce

Context: The Federated AI Imperative

The Pentagon, CIA, and DIA are building a federated machine workforce where AI agents operate as "coworkers" embedded in intelligence, cyber, planning, and mission execution workflows (April 2026). The core question is no longer "Can AI help?" but "Who owns judgment, authority, and responsibility once AI is embedded inside mission workflows?"

SHIELD/ATLAS addresses this through an AI audit engine (Anthropic Claude) and human-in-the-loop gates that maintain sovereign control over AI decision chains. The architecture supports multiple providers, but only Anthropic is currently active; pay-per-use providers (OpenAI/OpenRouter, Perplexity) are disabled per program directive 2026-04-23.

Human Judgment as Mission Assurance

"Appropriate human judgment" is now a formal Mission-Assurance requirement. As autonomy scales, governance must scale with it. SHIELD/ATLAS implements this through:

AI Cross-Validation Architecture

The audit framework supports independent validation by multiple AI providers. Currently only the Anthropic Claude lane is active; OpenAI, Gemini, and Perplexity lanes are off pending program reactivation. Human review is mandatory before any kill-chain promotion.

Cryptographic Audit Chain

SHA-256 hash chain records every AI decision, input, output, and human override. Tamper-evident governance chain-of-custody from sensor input to commander decision. Full accountability trail.

Human-in-the-Loop Gates

Kill chain transitions from TRAJECTORY to COUNTER-FIRE require explicit human authorization. AI recommends, humans decide. The gate cannot be bypassed programmatically.

Sovereign Federated Architecture

No single-vendor AI dependency. The multi-provider architecture ensures operational continuity even if one AI provider is compromised, sanctioned, or experiences outage. America needs a sovereign AI stack, not single-vendor dependency.

AGOS Decision Framework

The AI Governance Operating System (AGOS) provides real-time oversight of all AI agent actions within the platform:

Mission Assurance Rule: Governance must scale as autonomy scales. Every increase in AI agent authority requires a corresponding increase in audit depth, human oversight frequency, and accountability documentation. This is not optional — it is a Mission-Assurance requirement.

ISS LLC / SecureAssure (SDVOSB) | Software-Defined | MOSA-Compliant | JADC2-Aligned | CMMC 2.0 L2 | governance@secureassure.com

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