「riva」の検索結果

Creates GDPR Article 30(1) Records of Processing Activities (RoPA) for data controllers with all seven mandatory fields: controller identity and contact details, processing purposes, data subject categories, personal data categories, recipient categories, third country transfers, and retention periods. Includes Python generator for automated RoPA creation. Activate for controller RoPA, Art. 30(1), processing records, data mapping.

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Automated cookie consent validation using Selenium and Playwright. Covers banner interaction testing, consent state verification, tag firing audit after consent choices, regression testing for cookie compliance, and CI/CD pipeline integration.

日本語の概要は準備中です。原文の説明を表示しています。

Configures cloud storage retention policies across AWS S3, Azure Blob Storage, and Google Cloud Storage. Covers lifecycle rules, object lock, legal hold, immutability policies, cross-region replication retention alignment, and compliance mode configuration. Activate for cloud retention, S3 lifecycle, Azure retention, GCP retention policy queries.

日本語の概要は準備中です。原文の説明を表示しています。

Implements strict data minimization and retention limits for children's personal data under GDPR Art. 5(1)(c), Recital 38, UK AADC Standard 8, and COPPA Section 312.7. Covers strict necessity testing, shorter retention periods, limited profiling, parental dashboard design, and automated deletion. Keywords: data minimization, children, retention, necessity test, parental dashboard.

日本語の概要は準備中です。原文の説明を表示しています。

Implement the Kantara Initiative consent receipt specification including machine-readable receipt structure, JWT-based verification mechanisms, receipt lifecycle management, and integration patterns for consent management platforms. Supports ISO/IEC 27560 consent record information structure.

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive methodology for auditing website cookies and tracking technologies. Covers automated scanning, cookie categorization, lifecycle documentation, and compliance gap analysis referencing the Planet49 CJEU ruling (C-673/17).

日本語の概要は準備中です。原文の説明を表示しています。

Develops data classification policies with tiered handling (public, internal, confidential, restricted), labeling requirements, enforcement mechanisms, and procedures per tier. Covers policy governance, exception handling, and compliance monitoring. Keywords: classification policy, data tiers, handling procedures, labeling, enforcement, data governance, information security.

日本語の概要は準備中です。原文の説明を表示しています。

Manages direct communication to affected data subjects following a personal data breach under GDPR Article 34 when the breach is likely to result in a high risk to their rights and freedoms. Covers the high risk threshold, required notification content per Art. 34(2), exemptions under Art. 34(3), and breach notification letter templates for five scenarios. Keywords: data subject notification, Article 34, high risk, breach communication, GDPR.

日本語の概要は準備中です。原文の説明を表示しています。

Guides systematic mapping of international personal data flows across an organisation. Covers system-by-system inventory methodology, third-party identification, transfer mechanism assignment, gap analysis, and data flow visualisation. Keywords: data flow mapping, international transfers, data inventory, transfer register, cross-border data flows.

日本語の概要は準備中です。原文の説明を表示しています。

Harmonises data classification across jurisdictions mapping GDPR special categories vs CCPA sensitive PI (1798.140(ae)) vs HIPAA PHI (160.103) vs LGPD sensitive data (Art. 5-II). Provides cross-regulation mapping matrix for multinational compliance. Keywords: cross-jurisdiction, GDPR, CCPA, HIPAA, LGPD, sensitive data, multinational, classification mapping.

日本語の概要は準備中です。原文の説明を表示しています。

Technical architecture guide for building a multi-purpose consent preference center. Covers per-purpose granularity, easy withdrawal under Article 7(3), version history, audit trails, and IAB Transparency and Consent Framework v2.2 integration. Includes database schema, API design, and UI component specifications.

日本語の概要は準備中です。原文の説明を表示しています。

Guides the end-to-end GDPR Data Protection Impact Assessment process under Article 35, including mandatory trigger identification per Art. 35(3), DPIA content requirements per Art. 35(7), and EDPB WP248rev.01 methodology. Activate for systematic profiling, large-scale special category processing, or large-scale public monitoring. Keywords: DPIA, Article 35, impact assessment, WP248, data protection, risk assessment.

日本語の概要は準備中です。原文の説明を表示しています。

Builds comprehensive data inventory per GDPR Art. 30 Records of Processing Activities. Covers system-by-system discovery, data flow diagramming, third-party identification, and legal basis per category. Keywords: data inventory, data mapping, Art 30, RoPA, data flow, processing activities.

日本語の概要は準備中です。原文の説明を表示しています。

Executes breach notification under California Civil Code Section 1798.82 (California data breach notification law). Covers data elements triggering notification, timing requirements (most expedient time possible), AG notification for 500+ California residents, specific content and format requirements, and substitute notice provisions. Keywords: California, breach notification, Cal. Civ. Code 1798.82, attorney general, CCPA, data elements.

日本語の概要は準備中です。原文の説明を表示しています。

Technical enforcement of GDPR Article 5(1)(b) purpose limitation principle. Covers purpose-tagged data stores, access control per purpose, Article 6(4) compatibility assessment factors, and system design for preventing purpose creep. Includes purpose binding architecture and compatibility test implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Guides DPIA for migrating personal data to cloud infrastructure covering controller-processor analysis under Art. 28, international transfer assessment, encryption requirements, and shared responsibility model evaluation. Activate for cloud adoption, SaaS procurement, or data centre migration projects. Keywords: cloud migration, DPIA, Art. 28, processor, encryption, shared responsibility, SaaS, IaaS, PaaS.

日本語の概要は準備中です。原文の説明を表示しています。

Methodology for auditing A/B testing of consent banners to ensure compliance with equal ease of acceptance and rejection. Covers CNIL enforcement patterns including the EUR 150M Google fine, dark pattern detection methodology, manipulative design identification, and regulatory-compliant experimentation boundaries.

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Maintains the GDPR Article 33(5) breach register documenting all personal data breaches regardless of whether supervisory authority notification was required. Covers mandatory register fields including facts, effects, and remedial actions, retention periods, audit readiness, and integration with the accountability framework. Keywords: breach register, Article 33(5), breach documentation, accountability, audit readiness, remedial actions.

日本語の概要は準備中です。原文の説明を表示しています。

Implements automated PII discovery and classification using tools like Microsoft Purview, BigID, OneTrust DataDiscovery, and AWS Macie. Covers scanning schedules, accuracy tuning, false positive management, and integration patterns. Keywords: data discovery, PII scanning, Purview, BigID, Macie, OneTrust, automated classification, data cataloging.

日本語の概要は準備中です。原文の説明を表示しています。

Implements AI transparency requirements under EU AI Act Arts. 13-14 and GDPR Arts. 13-14. Covers user notification of AI interaction, system capability disclosure, limitation documentation, and meaningful information about automated logic. Keywords: AI transparency, EU AI Act, GDPR notification, explainability, automated decision.

日本語の概要は準備中です。原文の説明を表示しています。

Guides assessment of third-country adequacy decisions under GDPR Article 45 for international data transfers. Covers the current EC adequacy decisions list, adequacy assessment criteria, partial adequacy handling, and monitoring of adequacy decision reviews. Keywords: adequacy decision, Article 45, third country, adequate protection, EC adequacy list.

日本語の概要は準備中です。原文の説明を表示しています。

Conducts structured post-breach remediation using a lessons learned framework covering root cause remediation, control gap closure, policy updates, training modifications, monitoring enhancements, and regulatory follow-up. Provides a systematic approach to preventing breach recurrence and demonstrating accountability to supervisory authorities. Keywords: post-breach, remediation, lessons learned, root cause, control gap, policy update, training.

日本語の概要は準備中です。原文の説明を表示しています。

Implements automated data deletion workflows for GDPR Article 17 right to erasure and retention period expiry. Covers cascading deletion across dependent systems, dependency handling for referential integrity, confirmation logging, and audit trail generation. Activate for automated deletion, erasure automation, data purge, retention expiry queries.

日本語の概要は準備中です。原文の説明を表示しています。

Assesses lawful basis for AI training data processing per EDPB April 2025 report on LLMs and general-purpose AI. Covers legitimate interest balancing tests, consent challenges for ML training, public dataset assessment, and web scraping lawfulness. Keywords: AI training data, lawful basis, EDPB LLM, legitimate interest, consent, web scraping.

日本語の概要は準備中です。原文の説明を表示しています。