Security Governance, Risk & Privacy Topics
Governance, compliance frameworks, regulatory requirements, compliance implementation, and compliance-driven risk management. Covers compliance frameworks (SOX, GDPR, HIPAA, FCPA, etc.), regulatory interpretation, compliance control design, audit and control effectiveness evaluation, and compliance process management. For operational security implementation and technical threat mitigation, see Security Engineering & Operations.
Privacy-Preserving Analytics and Experimentation
Doing measurement and data science without over-collecting or exposing individuals: privacy-preserving experiment design, aggregate and on-device measurement, and privacy-respecting attribution. Covers techniques for analytics and A/B testing that limit personal-data use and honor consent. Includes reconciling measurement quality with privacy constraints.
Research Ethics and Consent
Handling personal data in research responsibly: informed consent for studies, research ethics review, participant protection, and secondary-use limits. Covers designing user research and data-collection studies that respect participants and comply with privacy obligations. Includes balancing research value against participant privacy.
Data Subject Rights and Request Handling
Operationalizing individual rights: access, rectification, erasure, portability, restriction, and objection requests. Covers identity verification, response timelines, locating data across systems to fulfill a request, and handling edge cases and exemptions. Includes designing systems that can execute deletion and export reliably at scale.
GDPR Principles and Compliance
The General Data Protection Regulation in depth: the six lawful bases, data subject rights, accountability and records obligations, DPO requirements, and enforcement and fines. Covers how GDPR principles translate into concrete engineering and product controls. Includes controller and processor obligations and demonstrating compliance.
Regulatory Change Management and Interpretation
Keeping a compliance and privacy program current as regulations, standards, and guidance evolve. Covers monitoring the regulatory landscape, interpreting ambiguous or new requirements, performing impact assessments and gap analyses against current controls, and driving program changes to close gaps. Emphasizes navigating regulatory ambiguity and translating guidance into concrete obligations.
Privacy by Design and Default
Embedding privacy into architecture and the development lifecycle: the privacy-by-design principles, privacy-protective defaults, and on-device or edge processing to minimize data exposure. Covers integrating privacy controls into product and program design and into engineering workflows rather than bolting them on. Includes designing privacy-first solutions and reference architectures.
Risk Assessment and Management
Identifying, analyzing, prioritizing, and treating information-security, compliance, and privacy risk. Covers qualitative and quantitative risk assessment methodologies, threat and vulnerability identification, likelihood and impact (and severity-of-harm) scoring, risk registers, and treatment decisions (accept, mitigate, transfer, avoid). Includes privacy-specific assessments such as DPIAs and PIAs: when an assessment is required, how to structure it, and how to weigh likelihood and severity of harm to individuals, plus prioritizing compliance and privacy risk across a portfolio of initiatives. Emphasizes structured, repeatable methodology tied to business context.
Communicating Security and Privacy Risk to Stakeholders and Leadership
Translating technical security, compliance, and privacy risk into language that executives, boards, and non-technical stakeholders can act on. Covers framing risk in business terms, influencing leadership on investment and strategy, tailoring the message to the audience, and driving decisions through communication. The persuasion-and-translation skill, distinct from the metrics themselves.
Privacy in Emerging Technologies
Privacy challenges raised by newer technologies and business models: AI and machine learning, biometrics, IoT, and other data-intensive innovations, plus how regulators are responding. Covers anticipating future privacy risks and adapting practices ahead of formal rules. Includes reasoning about privacy in novel data uses where guidance is still forming.