이 주제의 내용
Personal data · Risk management · AI governance · Compliance · Sovereignty
Map data flows and responsibilities
How do you build an actionable data map? Follow one processing activity from collection through copies, exports, backups and deletion. The register describes purposes, data categories, applications, providers, access, retention, owners and control evidence. The aim is to explain a decision, handle a request and verify a change. Examples concern methodology; legal classification depends on context and should be checked against original sources.
가이드 읽기 EN뉴스 모니터링
모든 국제 뉴스 →저장된 헤드라인 · 새로고침 불가 · 마지막 성공적 수집 : 2026. 10. 22. 오후 9:21
Abnormal AI 직원·에이전트 보안, 정식 제공은 AI Governance뿐 - quasa.io
via Google News · aggregatorAI 거버넌스란 무엇인가요? 모범 사례, 정의 및 사용법 - Illumio
via Google News · aggregatorTaiwan Fines Coupang NT$1.5 Million Over Data Breach - 스페셜경제
via Google News · aggregatorSouth Korea to Introduce Fines of Up to 10% of Revenue for Serious Data Protection Violations - 알파경제
via Google News · aggregatordata-protection 시장 동향, 뉴스 및 투자 가이드 - OneBullEx
via Google News · aggregator교황 레오14세 AI 윤리 기반 새 거버넌스 모델 제시 “AI보다 책임 구조가 먼저” - 사이언스모니터
via Google News · aggregator참고 자료: 데이터, 용도와 한계
문서 검토일 .
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| 출처와 목적 | 확인된 데이터 또는 기준 | 사용 방법 | 유지해야 할 한계 |
|---|---|---|---|
| FIRST · Traffic Light Protocol Indicate who may receive redistributed information. |
TLP 2.0 uses RED, AMBER, GREEN and CLEAR; AMBER+STRICT restricts sharing to the recipient organisation. Labels must not be translated. | Keep the marking with the information and check recipients before forwarding. Ask the source to clarify any ambiguity. | TLP is neither a formal classification nor a reuse licence. It does not guarantee content accuracy. |
| NIST · AI Risk Management Framework Organise management of AI-related risks. |
The AI RMF Core is organised around Govern, Map, Measure and Manage. It is a voluntary risk-management framework. | Define intended use, affected people and error consequences. Connect each risk to an evaluation, owner and stop or recovery mechanism. | The framework certifies neither a model nor an application. Using it does not remove the need to examine applicable requirements. |
| NIST · Privacy Framework Examine risks to people arising from data processing. |
The Privacy Framework is a voluntary privacy risk-management tool. It is distinct from a universal legal compliance checklist. | Describe actual processing: data, purposes, recipients, access and retention. Compare documents, settings and deletion or retrieval tests. | Using the framework alone does not determine compliance with applicable law. Processing context and jurisdiction still need examination. |
게시 및 AI 검색 가시성
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Assign publication decisions to an owner
Public publication and private access require different evidence. Snippet and AI participation choices must be linked to the relevant service and property.
- Record owner, scope, effective choice and inherited publication settings.
- Protect private resources through authorisation; robots.txt publicly reveals listed paths.
- Date acceptance evidence and review documentation again when the service changes.
Compare AI controls and report data →
References reviewed
security.txt와 취약점 공개
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Preserve contact scope when domains change
A migration, provider delegation or subdomain change can make a disclosure channel ambiguous. Domain governance should therefore include publication and review of security.txt.
- Check each relevant host: a parent domain’s file does not automatically apply to its subdomains.
- Compare Canonical URIs with actual retrieval and document provider redirects.
- Review contacts, keys, policy and expiry when responsibility transfers; preserve older versions as history.
Read the security.txt reference and disclosure cases →
Sources checked on · IETF · RFC 9116 · §2.5, §3, §5