Emergency restoration prioritization plans

Identifies documents containing references to emergency restoration prioritization plans in Australian contexts. This information type is classified as personally identifiable information under applicable data protection regulations.

Type: regex
Engine: boost_regex
Confidence: medium
Confidence justification: structural regex with domain-specific anchors and constrained context replaces phrase-only marker.
Detection quality: Mixed
Jurisdictions: global
Regulations: AML/CTF Act (Cth), HRIPA (Cth), IPA 2009 (Qld), My Health Records Act 2012 (Cth), NDB Scheme (Cth), Privacy Act 1988 (Cth), TIA Act 1979 (Cth)
Frameworks: ISO 27001, ISO 27701
Data categories: pii
Scope: wide
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?is)\b(?:emergency\s+restoration|restoration\s+priority|service\s+restoration)\b

Corroborative evidence keywords

emergency restoration prioritization plans, emergency, restoration, prioritization, plans, critical, infrastructure, systems

Proximity: 300 characters

Should match

Emergency restoration prioritization plans — Exact phrase marker match
emergency restoration prioritization plans — Case-insensitive phrase match
Emergency restoration prioritization plans — Normalized whitespace phrase
structured sample with matching anchors — Structural anchor sample

Should not match

unrelated generic text — No relevant phrase context
placeholder value 12345 — Random text should not match phrase marker
generic policy prose without anchors — Should reject generic mentions without structural anchor terms

Known false positives

Common words and phrases related to emergency restoration prioritization plans 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.legislation.gov.au/C2018A00029/latest/text
https://www.disasterassist.gov.au/