2,245 件 ・ 関連度順
概要と使いどころ
GDPR Article 28(2) sub-processor approval workflow management. Covers prior specific and general authorization mechanisms, change notification procedures, objection windows, flow-down obligation enforcement, and sub-processor chain risk monitoring.
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。
Tracks and monitors US state privacy legislation across all 50 states, DC, and territories. Covers enacted comprehensive privacy laws (California CCPA/CPRA, Virginia VCDPA, Colorado CPA, Connecticut CTDPA, Utah UCPA, and subsequent enactments), pending bills, effective dates, and key requirement differences. Keywords: state privacy law, CCPA, CPRA, VCDPA, CPA, CTDPA, UCPA, multi-state.
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 Privacy Impact Assessment for vendor and third-party data processing arrangements. Covers processor due diligence, Data Processing Agreement (DPA) requirements under GDPR Article 28, sub-processor management, cross-border vendor transfers, cloud service provider assessments, and ongoing vendor monitoring. Keywords: vendor PIA, processor assessment, DPA, Article 28, sub-processor, cloud privacy, third-party risk.
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 NIST Privacy Framework GOVERN function covering GV.AT awareness and training, GV.MT monitoring and review, GV.PO policy development, and GV.RR roles and responsibilities. Provides governance structure templates, training programs, and accountability frameworks for privacy governance.
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。
Addresses healthcare AI privacy at the intersection of HIPAA and the EU AI Act for clinical decision support systems. Covers training data PHI handling, model transparency and explainability, patient rights in algorithmic decisions, FDA/OCR regulatory coordination, and bias monitoring. Keywords: healthcare AI, HIPAA, AI Act, clinical decision support, PHI training data, model transparency.
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。
Assessing privacy risks in large language model outputs including training data memorisation, PII leakage in generated text, prompt injection leading to data extraction, and hallucinated personal data. Covers output filtering, guardrails, and monitoring. Keywords: LLM privacy, output risk, memorisation, PII leakage, prompt injection, hallucinated PII.
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 legal hold and data preservation processes including triggering events, custodian notification, hold-in-place technical implementation, release procedures, and interaction with retention schedules. Covers litigation hold registers, compliance monitoring, and Art. 17(3)(e) exception documentation. Activate for legal hold, litigation preservation, data freeze, e-discovery hold 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。
Manages Data Subject Access Request procedures for employee requests under Art. 15 GDPR. Covers scope of disclosable HR records, emails, CCTV footage, performance reviews, monitoring data, and training records. Implements third-party data redaction, legal professional privilege, exemptions for ongoing proceedings, and the one-month response timeline. Keywords: DSAR, subject access request, Art. 15, employee records, redaction, privilege, HR data, SAR.
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。
Implements BYOD privacy compliance frameworks for personal device use in the workplace. Covers personal vs corporate data separation, MDM capabilities and limitations, employee consent requirements, data wiping boundaries, and monitoring restrictions on personal devices. Keywords: BYOD, mobile device management, MDM, personal device, data separation, containerisation, remote wipe, employee privacy.
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。
Guides audit follow-up and verification processes including follow-up scheduling, remediation effectiveness testing, finding closure criteria, re-testing procedures, status reporting, and escalation of unremediated findings. Implements IIA Standard 2500 monitoring requirements and ISO 19011 follow-up guidance for privacy audit engagements. Keywords: audit follow-up, verification testing, finding closure, remediation effectiveness, re-testing, follow-up audit.
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 technical breach detection capabilities including SIEM integration, DLP alert configuration, anomaly detection rules, and insider threat monitoring. Provides a breach classification taxonomy across confidentiality, integrity, and availability dimensions. Covers detection tool selection, alert tuning, and integration with privacy incident response workflows. Keywords: breach detection, SIEM, DLP, anomaly detection, insider threat, classification.
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。
Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup. Keywords: AI deployment, privacy checklist, go-live, model deployment, compliance gate.
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。
Guides privacy audit risk assessment including risk universe development, inherent and residual risk scoring, control effectiveness evaluation, risk-based audit planning, heat map generation, risk appetite alignment, and audit prioritization by risk exposure. Covers the full audit risk assessment cycle from scoping through ongoing monitoring. Keywords: audit risk assessment, risk universe, inherent risk, residual risk, control effectiveness, risk-based audit planning.
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。
AWS cost optimization, monitoring, and operational excellence expert. Use when analyzing AWS bills, estimating costs, setting up CloudWatch alarms, querying logs, auditing CloudTrail activity, or assessing security posture.
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 centralized audit logging and SIEM integration. Configure log retention and security monitoring. Use when implementing audit trail requirements.
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。
Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.
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。
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
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。
Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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。
Create original short videos using the 叙事拆幕｜情绪场景连续退到片场与监看层 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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。
Observability and SRE expert. Use when setting up monitoring, logging, tracing, defining SLOs, or managing incidents. Covers Prometheus, Grafana, OpenTelemetry, and incident response best practices.
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。