nist-privacy-identify

name	nist-privacy-identify
description	Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Maps NIST PF controls to GDPR requirements for dual-framework compliance. Keywords: NIST Privacy Framework, IDENTIFY function, ID.BE, ID.DA, ID.IM, ID.RA, privacy risk assessment, data actions.
license	Apache-2.0
metadata	{"author":"mukul975","version":"1.0","domain":"privacy","subdomain":"privacy-impact-assessment","tags":"nist-privacy-framework, identify-function, privacy-risk, data-actions"}

Implementing NIST Privacy Framework IDENTIFY Function

Overview

The NIST Privacy Framework Version 1.0 (January 2020) provides a voluntary enterprise risk management tool structured around five core functions: IDENTIFY, GOVERN, CONTROL, COMMUNICATE, and PROTECT. The IDENTIFY function develops the organisational understanding to manage privacy risk arising from data processing. This skill covers the four IDENTIFY subcategories: Inventory and Mapping (ID.IM), Business Environment (ID.BE), Risk Assessment (ID.RA), and Data Processing Ecosystem Risk Management (ID.DE).

IDENTIFY Function Structure

ID.IM — Inventory and Mapping

Data processing inventory and mapping activities are understood by the organisation.

Subcategory	Description	Implementation
ID.IM-P1	Systems/products/services that process data are inventoried	Maintain a comprehensive register of all systems processing personal data, including SaaS tools, internal databases, and third-party integrations
ID.IM-P2	Owners of systems/products/services are identified	Assign a data processing owner to each system with documented responsibility for privacy compliance
ID.IM-P3	Categories of individuals whose data are processed are inventoried	Map all data subject categories (employees, customers, patients, vendors, website visitors)
ID.IM-P4	Data actions of the systems/products/services are inventoried	Document data lifecycle actions: collection, retention, logging, generation, transformation, use, disclosure, sharing, transmission, disposal
ID.IM-P5	Purposes for data actions are inventoried	Document specific purposes for each data action, aligned with GDPR Art. 5(1)(b) purpose limitation
ID.IM-P6	Data elements within the data actions are inventoried	Catalogue all personal data elements processed per system and per purpose
ID.IM-P7	Environmental factors affecting the data processing ecosystem are understood	Assess external factors: legal/regulatory requirements, industry standards, market expectations, organisational risk tolerance
ID.IM-P8	Data processing is mapped	Create and maintain data flow maps showing how personal data moves through the organisation

ID.BE — Business Environment

The organisation's mission, objectives, stakeholders, and activities are understood and prioritised.

Subcategory	Description	Implementation
ID.BE-P1	The organisation's role in the data processing ecosystem is identified and communicated	Determine controller/processor/joint controller status for each processing activity
ID.BE-P2	Priorities for organisational mission, objectives, and activities are established and communicated	Align privacy programme with business objectives; ensure privacy is a design requirement
ID.BE-P3	Systems/products/services that support organisational priorities are identified and key requirements communicated	Identify which processing activities are critical to business operations and prioritise privacy investment accordingly

ID.RA — Risk Assessment

The organisation understands the privacy risks to individuals and how such processing creates privacy risks to the organisation.

Subcategory	Description	Implementation
ID.RA-P1	Contextual factors related to the systems/products/services and data actions are identified	Assess context: relationship with data subjects, data subject expectations, sensitivity, volume, collection method
ID.RA-P2	Data analytic inputs and outputs are identified and evaluated	For data analytics and AI, identify inputs (training data, inference data) and outputs (predictions, scores, decisions)
ID.RA-P3	Potential problems for individuals that arise from data processing are identified	Identify privacy harms: loss of autonomy, discrimination, economic loss, physical harm, reputational damage, loss of trust
ID.RA-P4	Problematic data actions, the likelihood that they occur, and the resulting problems for individuals are identified and assessed	Assess likelihood and severity of each problematic data action — aligned with GDPR DPIA risk assessment
ID.RA-P5	Risk responses are identified and prioritised	For each identified risk, determine response: mitigate, transfer, avoid, accept

ID.DE — Data Processing Ecosystem Risk Management

The organisation identifies, assesses, and manages privacy risks associated with data processing by third parties.

Subcategory	Description	Implementation
ID.DE-P1	Data processing ecosystem risk management policies, processes, and procedures are identified, established, assessed, and managed	Vendor privacy management programme with due diligence, contractual requirements, and ongoing monitoring
ID.DE-P2	Data processing ecosystem parties are identified, prioritised, and assessed	Map all processors, sub-processors, and third-party recipients with risk rating
ID.DE-P3	Contracts with data processing ecosystem parties are established, maintained, and managed	Art. 28 DPAs with all processors; joint controller arrangements per Art. 26
ID.DE-P4	Interoperability frameworks or mechanisms are established for data processing ecosystem parties	Standard data formats, APIs, and privacy-preserving data exchange protocols
ID.DE-P5	Data processing ecosystem parties are managed consistent with the organisation's risk strategy	Ongoing processor performance monitoring, audit rights exercise, sub-processor change management

NIST PF to GDPR Mapping

NIST PF Subcategory	GDPR Equivalent	Implementation Overlap
ID.IM-P1 through P8	Art. 30 Records of Processing Activities	RoPA fulfils the core inventory and mapping requirements
ID.BE-P1	Art. 26 Joint Controllers, Art. 28 Processors	Role determination aligns directly
ID.RA-P1 through P5	Art. 35 DPIA	DPIA risk assessment methodology maps to NIST risk assessment
ID.DE-P1 through P5	Art. 28 Processor Requirements	Processor governance maps to ecosystem risk management

Implementation Methodology

Phase 1: Establish Inventory and Mapping (Months 1-3)

1. Deploy a data discovery tool to identify personal data across all systems.
2. Conduct departmental interviews to identify informal data processing.
3. Create the system-level processing inventory (ID.IM-P1, P2).
4. Map data subject categories (ID.IM-P3) and data elements (ID.IM-P6).
5. Document data actions per system (ID.IM-P4) and purposes (ID.IM-P5).
6. Create data flow maps (ID.IM-P8).
7. Cross-reference with existing Art. 30 RoPA.

Phase 2: Business Environment Analysis (Month 2-3)

1. Determine controller/processor/joint controller roles (ID.BE-P1).
2. Align privacy programme priorities with business strategy (ID.BE-P2).
3. Identify critical processing activities (ID.BE-P3).

Phase 3: Risk Assessment (Months 3-5)

1. For each processing activity, assess contextual factors (ID.RA-P1).
2. Identify problematic data actions using the NIST problematic data action taxonomy:
   • Appropriation: use of data in ways beyond data subject expectations
   • Distortion: use of inaccurate data or misleading inferences
   • Induced disclosure: pressure to reveal more data than intended
   • Insecurity: inadequate protection of data
   • Re-identification: linking anonymised data back to individuals
   • Stigmatisation: association with disfavoured groups
   • Surveillance: excessive monitoring
   • Unanticipated revelation: discovery of information beyond original data
   • Unwarranted restriction: limiting access to services based on data
3. Assess likelihood and severity for each problematic data action (ID.RA-P4).
4. Determine risk responses (ID.RA-P5).

Phase 4: Ecosystem Risk Management (Months 4-6)

1. Inventory all third-party data processors and recipients (ID.DE-P2).
2. Conduct vendor privacy due diligence assessments.
3. Verify DPA compliance for all processors (ID.DE-P3).
4. Establish ongoing monitoring programme (ID.DE-P5).

Enforcement Context

While the NIST Privacy Framework is voluntary and not directly enforceable, organisations demonstrating NIST PF implementation show a mature privacy programme that can support GDPR accountability under Art. 5(2) and Art. 24. US state privacy laws (California CPRA, Virginia VCDPA, Colorado CPA) increasingly reference the NIST PF as a compliance resource.