OOF™ Origin Open Foundation™

Independent Methodological Authority

OriginID: OOF-OID-INTEGROS-IDS-IDDM-2026-07-21-0001
Architecture Ecosystem: Structured Reality Standards™
Architecture Family: INTEGROS® — Integrity Governance Architecture
Parent Standard: Integrity Deviation Standard (IDS)
Operational Layer: Meta-Integrity Governance Layer
Category: Governance & Enforcement
Subcategory: Integrity Governance
Type: Parent Standard Module
Governed Space: Integrity Deviation Detection
Version: 1.0
Status: Canonical · Open Module
Origin Date: 21 July 2026
Compatibility: OOF Methodology OS · GOA™ · OBIDENITY® · ART™ · ORA™ · AGA™ · AIG® · CLIA® ·
MGIA™ · ASGA™
AI-Readable: Yes
Authority: OOF®
Protection: MIP™ — Methodological Intellectual Property
Canonical Language: English (UCL)

Governed Space

Integrity Deviation Detection

Canonical Definition

Integrity Deviation Detection Module (IDDM) defines the governance framework
for identifying the earliest signs of deviation from an approved integrity
state. It establishes the detection methods, observation criteria, evidence
requirements, and governance controls required to recognize integrity
deviations before they develop into integrity breaches throughout the complete
lifecycle of a governed entity.

Operational Role

IDDM governs the detection layer of integrity deviation management by
providing continuous identification of abnormal conditions, behavioral
changes, structural inconsistencies, or operational anomalies that indicate
emerging integrity deviations.

Minimum Implementation Framework

1. Define Deviation Detection Scope

Identify the integrity conditions, measurements, indicators, operational
events, and behavioral changes that must be monitored for potential
deviations.

2. Define Detection Requirements

Establish detection methods, observation criteria, monitoring frequency,
evidence requirements, sensitivity levels, and governance responsibilities.

3. Define Detection Validation Logic

Define how detected deviations are verified for accuracy, consistency,
significance, evidence sufficiency, and compliance with approved governance
methodology.

4. Define Governance Response

Establish governance actions for detected deviations, false positives,
monitoring alerts, escalation, investigation, and corrective intervention.

5. Preserve Detection Records

Maintain detection events, supporting evidence, timestamps, governance
decisions, investigation records, and audit documentation throughout the
complete lifecycle.

Example Use Cases

Use Case 1 — Autonomous AI Governance

Scenario

An autonomous AI system begins producing decisions that increasingly diverge
from approved governance policies while still operating within acceptable
performance thresholds.

Application

IDDM detects the early behavioral deviation, validates the supporting
evidence, and initiates governance review before an integrity breach occurs.

Result

Integrity deviations are identified at an early stage, enabling proactive
governance and preventing escalation.

Use Case 2 — Financial Transaction Monitoring

Scenario

A financial institution observes unusual transaction patterns that deviate
from established operational integrity baselines.

Application

IDDM detects the deviation, validates its significance, and initiates
governance procedures for further evaluation.

Result

Potential integrity risks are identified before they evolve into fraud,
compliance failures, or operational breaches.

Canonical Closing Statement

Integrity preservation begins with early awareness. Integrity Deviation
Detection Module establishes the canonical governance framework for
identifying the earliest signs of integrity deviation, enabling timely
intervention, proactive governance, and continuous protection of integrity
throughout the complete lifecycle of every governed entity.