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.
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.
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.
Data Minimization and Retention
Collecting and keeping only what is necessary: data minimization at collection, purpose limitation, and retention scheduling with automated deletion. Covers defining retention periods, enforcing them technically, and defensibly disposing of data. Includes balancing operational or analytics needs against minimization obligations.
Privacy-Enhancing Technologies and Anonymization
Technical safeguards that reduce identifiability: anonymization, pseudonymization, tokenization, differential privacy, and related privacy-enhancing technologies. Covers the difference between anonymized and pseudonymized data, re-identification risk, and when each technique is appropriate. Includes evaluating the privacy-utility tradeoff of a given technical control.
US State Privacy Laws (CCPA/CPRA)
California and other US state privacy statutes: consumer rights to know, delete, correct, and opt out of sale or sharing, sensitive-data limits, and the patchwork of state regimes. Covers how US law differs from GDPR in scope and mechanics and how to operationalize opt-out and disclosure duties. Includes the compliance obligations these laws place on data-handling systems.
Privacy and Security Alignment
The relationship between privacy and security: how they overlap and differ, and how access control, least privilege, encryption, and other security controls serve privacy goals. Covers aligning privacy and security programs and reasoning about safeguards that protect personal data at scale. Includes distinguishing a privacy failure from a security failure.