should be published for others to emulate and become best practices. 5. End-to-End 5.1–Protect Continuously: SHALL be produced for all stages of Lifecycle Protection Personal data must be the software development lifecycle continuously protected across the from referencing applicable principles, entire domain and throughout the policies, and regulations to defining data life-cycle from creation to privacy requirements, to design, destruction. implementation, maintenance, and retirement. 5.2–Control Access: Controls on access to personal data should be SHALL reference requirements, risk commensurate with its degree of analyses, architectures, design, sensitivity, and be consistent with implementation mechanisms, recognized standards and retirement plan, and sign-offs with practices. respect to privacy and security. 5.3–Security and Privacy SHALL reference security metrics Metrics: Applied security AND privacy properties and metrics standards must assure the designed and/or deployed by the confidentiality, integrity and software, or monitoring software, or availability of personal data and otherwise in the organization, and be amenable to verification across partnering software systems or organizations. Applied privacy standards must assure user/data subject comprehension, choice, consent, consciousness, consistency, confinement (setting limits to collection, use, disclosure, retention, purpose), and context(s) around personal data at a functional level, and minimized identifiability, linkability, and observability; maximized traceability, audibility and accountability at a systems level, and be amenable to verification. 6. Visibility and 6.1–Open Collaboration: Privacy SHALL reference the privacy policies Transparency requirements, risks, and documentation of all other implementation methods and collaborating stakeholders outcomes should be documented include description of contextual throughout the development visibility and transparency lifecycle and communicated to mechanisms at the point of contextual interaction with the data subject (user)
should be published for others to emulate and become best practices. 5. End-to-End Lifecycle Protection 5.1–Protect Continuously: Personal data must be continuously protected across the entire domain and throughout the data life-cycle from creation to destruction. 5.2–Control Access: Controls on access to personal data should be commensurate with its degree of sensitivity, and be consistent with recognized standards and practices. 5.3–Security and Privacy Metrics: Applied security standards must assure the confidentiality, integrity and availability of personal data and be amenable to verification Applied privacy standards must assure user/data subject comprehension, choice, consent, consciousness, consistency, confinement (setting limits to collection, use, disclosure, retention, purpose), and context(s) around personal data at a functional level, and minimized identifiability, linkability, and observability; maximized traceability, audibility and accountability at a systems level, and be amenable to verification. SHALL be produced for all stages of the software development lifecycle from referencing applicable principles, policies, and regulations to defining privacy requirements, to design, implementation, maintenance, and retirement. SHALL reference requirements, risk analyses, architectures, design, implementation mechanisms, retirement plan, and sign-offs with respect to privacy and security. SHALL reference security metrics AND privacy properties and metrics designed and/or deployed by the software, or monitoring software, or otherwise in the organization, and across partnering software systems or organizations. 6. Visibility and Transparency 6.1–Open Collaboration: Privacy requirements, risks, implementation methods and outcomes should be documented throughout the development lifecycle and communicated to SHALL reference the privacy policies and documentation of all other collaborating stakeholders include description of contextual visibility and transparency mechanisms at the point of contextual interaction with the data subject (user)