data-minimization

WORK ITEM: Repo for Data Minimization and selective disclosure

Local-first AI WAF, compliance gate, and cryptographic provenance engine for agentic workflows. Intercepts payloads, slashes token spend via Prose-Tax minimization, and mints tamper-evident audit chains on local silicon.

A simple data minimization and anonymization microservice wrapped around go-minimizer

Data minimization, pseudonymization, and anonymization helpers for Go

Contains all the code used and submitted for the indiviual assignments of the Data Protection Technologies (https://coursecatalogue.uva.nl/xmlpages/page/2023-2024-en/search-course/course/110258) as part of the MSc in Computer Science (Big Data Engineering track).

Organizational Cognitive Telemetry (OCT) — a system for capturing sanitized AI interaction telemetry to identify cognitive friction, knowledge gaps, and usage patterns across an organization, without storing sensitive content or individual identities.

Source code of IJCB2024 paper "Controllable Privacy in Face Recognition: A Filter-based Approach"

Export minimal debugging reports from Playwright traces with an explicit omission manifest.

Reusable code-graph and Git co-change analysis for reviewing parallel changes. Local demos and a PR-coordination runtime. Source-available; hosted App suspended.

Client-side metadata minimisation for Miden private notes.

A JavaScript client with a graphical user interface for Kalita, a text-to-speech software with a focus on data minimization and user privacy.

privacy.md — a privacy boundary for personal AI agents, enforced before the data leaves your machine. AGENTS.md tells an agent how to work; privacy.md tells it what it may send.

Data Prism is an open-source privacy layer for Java/Spring teams putting LLM agents or MCP clients in front of internal APIs holding customer data. It pseudonymises personal data per privacy scope, refuses anything unclassified, and can keep a hash-chained audit trail.

🛡️ The consent firewall for AI agents. Your agent can use the world's public data — the world can't use yours. Field-level minimization, in-flow consent, LLM tokenization, prompt-injection quarantine & hash-chained privacy receipts. MCP server included.

What happens when privacy law meets skewed data? A reproducible 960-run computational experiment measuring the joint effects of data minimization and class imbalance on ML performance and fairness. PhD dissertation research.

Offline proof of concept: coarse categorical incident postcards from 512-channel classical residual frames, with no raw-data sharing.

Open Agent Privacy Protocol & Runtime for pseudonymization, data minimization, scoped re-identification and privacy-safe AI agent access.

Decide whether an activity event may be retained and produce a minimized record under an explicit consent/retention policy.

2026 AI Co-Scientist Challenge Korea(AI 연구 동료 경진대회) /Reproducible experiment code for the AI Co-Scientist Challenge 2026.

A Java speech synthesizer and backend server for Kalita, a text-to-speech software with a focus on data minimization and user privacy.