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.
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 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.
Data Classification and Sensitivity Handling
Classifying data by sensitivity and applying controls proportionate to that classification: identifying personal, sensitive, and special-category data and tagging it through its lifecycle. Covers classification schemes, labeling, and how classification drives access, encryption, and retention decisions. Includes assessing the impact of a given data type on privacy and security risk.
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.
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.
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.
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.
Global Privacy Regulations and Data Protection Frameworks
The landscape of privacy and data protection law and how core frameworks fit together: controllers vs processors, personal vs sensitive data, lawful processing, and cross-framework concepts. Covers foundational privacy terminology and how to reason about which regimes apply to a given data flow. Serves as the orientation layer beneath the regulation-specific topics.
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.