War-gaming simulation outputs

Identifies documents containing references to war-gaming simulation outputs in Australian contexts. This information type is classified as personally identifiable information under the Privacy Act 1988.

Type

regex

Engine

boost_regex

Confidence

medium

Confidence justification

category-aware structural regex with anchor and context constraints replaces phrase-only detection.

Detection quality

Mixed

Jurisdictions

global

Regulations

AML/CTF Act (Cth), IPA 2009 (Qld), NDB Scheme (Cth), Privacy Act 1988 (Cth)

Frameworks

ISO 27001

Data categories

government-id, pii

Scope

wide

Platform compatibility

Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?is)\b(?:war\s+gaming|simulation\s+output|tabletop\s+exercise|scenario\s+analysis|defense\s+simulation|operational\s+planning|threat\s+modeling|national\s+security|classified\s+simulation|military\s+exercise)\b

Corroborative evidence keywords

war-gaming simulation outputs, war, gaming, simulation, outputs, defense, intelligence, government, agency, department, ministry, public sector, civil service, welfare, social services, public administration, statutory authority, regulatory body, public servant, government program (+2 more)

Proximity: 300 characters

Should match

• war gaming — Primary topic phrase match
• simulation output — Case-insensitive topic phrase match
• tabletop exercise — Alternative topic phrase match
• scenario analysis — Additional topic phrase match

Should not match

• unrelated generic text without domain phrases — No relevant topic phrases present
• placeholder value 12345 — Random text should not match topic-specific regex
• classified contingency — Generic word pair from old broad template should not match

Known false positives

• Common words and phrases related to war-gaming simulation outputs appearing in policy documents, training materials, HR templates, or compliance guidelines without actual personal data. Mitigation: Require corroborative evidence keywords within the proximity window to confirm sensitive data context rather than general discussion.
• In Australian English, similar terminology used in formal or administrative contexts (education, professional documentation) that does not constitute sensitive data collection. Mitigation: Layer with additional contextual signals such as structured identifiers, form fields, or database column headers to distinguish sensitive records from general references.
• High-frequency pattern matches in large document corpora due to broad regex anchors. Expected match rate is significantly higher than specific identifier patterns. Mitigation: Tune confidence thresholds for bulk scanning. Consider using this pattern primarily as a pre-filter with secondary validation.

References

• https://www.protectivesecurity.gov.au/
• https://www.defence.gov.au/business-industry/export/controls