AdvancedSecurity trackDE-CP-10

GDPR-Compliant Synthetic Data Generator

Generate synthetic data that preserves statistical utility while resisting membership-inference attacks, with the privacy-utility frontier plotted.

10 Guided Steps480h Internship TierSubmit: GitHub repo or evidence pack + live demo / report + README + milestone logbookVerified CertificateAI Rubric Graded

Program Overview

Generate synthetic data that preserves statistical utility while resisting membership-inference attacks, with the privacy-utility frontier plotted.

What you submit

GitHub repo or evidence pack + live demo / report + README + milestone logbook

How it is graded

Scope & method20
Written scope and rules of engagement, and a method that follows a named framework (OWASP, NIST, MITRE ATT&CK).
Findings quality30
Each finding has steps to reproduce, evidence, a severity rating with reasons, and affected assets.
Remediation20
Fixes are specific, ranked by risk, and at least one is shown working.
Evidence & files15
Logs, screenshots, scripts or configs that a reviewer can check.
Report for a manager15
A one-page summary a non-technical manager can act on.

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes

480-hour Germany programme. German data protection culture is the strictest in Europe

synthetic data is how teams develop without touching real records.

Target Audience

Engineering Students

Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.

Aspiring Developers

Developers who want to build proof-of-work capstone projects for tech resumes.

Job Seekers

Graduates looking for AI-evaluated code review & verified industry credentials.