Driving data value requires careful consideration beyond legal compliance under GDPR, HIPAA and state-level laws like CCPA. Once you’ve completed this 5-day course, you’ll know what’s required to maximize data utility while meeting your organization’s regulatory and privacy obligations. This course has several benefits benefits to participants and their organizations; safely leverage sensitive data for analytics that drive priority business outcomes; Aligning business and privacy teams to protect organization’s sensitive data and uncover its untapped value, and improving the efficiency of data analysis and management operations by integrating industry-leading techniques with the existing processes and procedures.
Participants who successfully complete the course will receive Certificate of Participation.
COURSE OBJECTIVES
At the end of this course the participants will learn:
- Key principles behind measuring identifiability and establishing defensible thresholds to render data non-identifiable.
- How to apply de-identification to protect privacy while leveraging the power of your data.
- Risk management and reporting necessary to provide auditable proof you’ve taken consistent, defensible steps toward protecting privacy.
DURATION
5 days
WHO SHOULD ATTEND
This course is designed for professionals working in, Analytics, Compliance, Data, Legal, Privacy, Security, Statistics as well other relevant domains.
COURSE CONTENT
Module 1: Legal Frameworks and Foundations
- Welcome and Course Introduction
- Importance of Data Privacy and De-Identification
- Overview of HIPAA, CCPA, and GDPR regulations
- Understanding legal bases for data use and secondary purposes
- Comparative analysis of HIPAA Expert Determination vs Safe Harbor methods
- CCPA data de-identification criteria
- GDPR requirements for anonymization and pseudonymization
- Case studies: Legal consequences of failed de-identification
Module 2: Concepts, Definitions, and Real-World Risks
- Key Definitions: Identifiers, Quasi-identifiers, Direct vs Indirect Identifiers
- Data Release Models: Open, Semi-restricted, Restricted Access
- Known Re-identification Attacks: AOL dataset, Netflix prize dataset, Hospital discharge data cases
- Classification of Identifiers: Direct, Indirect, Sensitive Attributes
- Privacy models overview: K-anonymity, L-diversity, T-closeness
- Interactive Exercise: Identifying risks in real-world datasets
Module 3: Risk Measurement and Contextual Analysis
- Equivalence Classes and Risk Quantification
- Types of Risks: Identity disclosure, Attribute disclosure, Inferential disclosure
- Metrics for risk assessment: Re-identification probability, Record uniqueness
- Contextual Risk Factors: Public data availability, External data linkability
- Types of Attacks: Prosecutor, Journalist, Marketer attacks
- Setting Re-identification Risk Thresholds: Balancing utility and privacy
Module 4: De-Identification Techniques and Data Transformation
- Methods for Direct Identifier Masking: Suppression, Redaction, Generalization
- Methods for Quasi-Identifier De-Identification:
- Data Swapping
- Data Perturbation
- Synthetic Data Generation
- Aggregation and Sampling
- Choosing Appropriate Techniques Based on Risk and Use Case
- Hands-on Exercise: Applying multiple de-identification techniques to sample datasets
- Measuring post-transformation re-identification risk
Module 5: Risk Management, Documentation, and Final Assessment
- Evaluating if De-identified Data Meets Regulatory Standards
- Building De-Identification Reports:
- Documenting methods used
- Stating assumptions and risk thresholds
- Demonstrating compliance
- Afternoon Session:
- Best Practices for Ongoing Risk Monitoring
- Limitations of De-Identification and Managing Residual Risks
- Group Project: De-identify a sample dataset, assess risk, and create a de-identification report
- Final Q&A and Course Wrap-Up
- Certificates Awarded
GENERAL NOTES
- The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.
- The participants should be reasonably proficient in English as all facilitation and course materials will be offered in English.
- Upon successful completion of this training, participants will be issued with a certificate.
- The training will be held at Kincaid Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.
- All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.
- Accommodation and airport pickup are arranged upon request. For reservations contact the Training coordinator at Email: training@kincaiddevelopmentcenter.org or Tel: +254 724592901
- This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our Kincaid Training Centre or at a convenient location.
For further inquiries, please contact us on Tel: +254 724592901 or send mail to training@kincaiddevelopmentcenter.org
Payments are due upon registration. Payment should be sent to our Bank account before commencement of training and proof of payment sent to training@kincaiddevelopmentcenter.org