「by-design」の検索結果

Systematic application of the eight privacy design patterns per Hoepman: minimize, hide, separate, abstract, inform, control, enforce, and demonstrate. Covers pattern selection methodology per processing activity, mapping to GDPR principles, and practical implementation guidance for privacy-by-design system architecture.

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Use Understanding by Design (UbD) to plan one OpenMAIC classroom or a course series around transferable conceptual understanding. Use when the user wants backward design, enduring understandings, essential questions, GRASPS performance evidence, WHERETO learning experiences, or a concept-centered lesson rather than a list of facts. Do not use for visual style cloning, teacher-style imitation, or direct PPT import.

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Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.

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Doctrine for designing and evolving any **SDK** Grida ships — TypeScript, Rust, or otherwise. "SDK" here means a surface that crosses a foreign-or-foreign-treated boundary: published packages, separately-versioned consumers, FFI bindings, public-by-design modules. An SDK's job is to refuse; a strict, honest surface rejects the wrong contents and keeps the package testable in isolation. Default is "core, not customizable"; customization is the exception, defended by a deciding table. Use when authoring or evolving any such surface — `@grida/*` published packages, engine crates (gridaco/nothing `crates/*`) published or FFI-exported, intent/message vocabularies, any contract a second author will compile against. Internal-only helper packages are welcome to follow, not forced. Companion skill for two-sided contract work: $sdk-seam. Critique partners: $pedantic, $etiology. Related: $naming.

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Expert in threat modeling methodologies, security architecture review, and risk assessment. Masters STRIDE, PASTA, attack trees, and security requirement extraction. Use for security architecture reviews, threat identification, and secure-by-design planning.

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Secure by Design principles knowledge base for assessing security-first design, development, and deployment across the software lifecycle.

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Security design principles, STRIDE threat modeling, OWASP Top 10 architectural mitigations, and secure patterns. Load when designing systems or reviewing architecture for security.

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Use when reviewing, designing, or modifying Java enterprise products, services, libraries, agents, plugins, connected components, or platform modules that may qualify as products with digital elements and need EU Cyber Resilience Act secure-by-design, vulnerability handling, security update, SBOM, product documentation, or release-readiness controls. Part of Plinth Toolkit

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Preparation guide for ISO 31700 privacy by design for consumer goods certification. Covers the 30 requirements across design, production, and disposal phases. Includes gap assessment methodology, remediation planning, and mapping to GDPR Article 25 data protection by design obligations for consumer-facing products and services.

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Implements federated learning architecture patterns for GDPR compliance. Covers secure aggregation protocols, differential privacy integration, communication protocols, and privacy-by-design distributed ML training. Keywords: federated learning, distributed training, secure aggregation, differential privacy, privacy-preserving ML.

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Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila). Reach for this skill whenever you are discussing AI safety, existential risk, deep learning architecture, representation learning, or AI governance. Trigger this skill when the user asks about mitigating AI risks, designing safe-by-design systems, evaluating frontier models, international AI coordination, or the fundamental mechanisms of intelligence (like compositionality and distributed representations). Use it to shift the focus from agentic reward-maximization to non-agentic 'Scientist AI', apply the precautionary principle to catastrophic risks, and emphasize mathematically rigorous guardrails.

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Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila). Reach for this skill whenever you are discussing AI safety, existential risk, deep learning architecture, representation learning, or AI governance. Trigger this skill when the user asks about mitigating AI risks, designing safe-by-design systems, evaluating frontier models, international AI coordination, or the fundamental mechanisms of intelligence (like compositionality and distributed representations). Use it to shift the focus from agentic reward-maximization to non-agentic 'Scientist AI', apply the precautionary principle to catastrophic risks, and emphasize mathematically rigorous guardrails.

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Engineering privacy and data governance: PII detection, data flow mapping, consent patterns, GDPR/CCPA-compliant implementation, DPIA. Use when privacy-by-design is needed.

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Expert guide for Data Privacy, GDPR, CCPA, and PDPA compliance. Covers consent management, data retention, privacy-by-design, and audit trails / Panduan kepatuhan Privasi Data, GDPR, dan PDPA.

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Validate systems and processes against GDPR/CCPA privacy regulations, privacy-by-design principles, ADA/WCAG accessibility standards, data processing agreements (DPAs), and provide compliance checklists with regulatory change monitoring guidance.

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。