DEDA – Tracking Dots Extraction, Decoding and Anonymisation Toolkit
DEDA is an open-source Python toolkit that detects, decodes, and removes printer tracking dots from documents to prevent hardware-based surveillance.
summary is enough The GitHub README efficiently explains the tool's purpose, installation commands, and usage workflow for stripping printer tracking dots.
summary
Commercial color laser printers embed microscopic yellow tracking dots encoding device serial numbers and timestamps on every printed page. DEDA is a Python toolkit that allows users to parse, extract, and decode these forensic patterns from scanned documents using command-line utilities or a graphical interface. It also provides an anonymisation workflow that generates printer-specific masks to cover or disrupt tracking dots on PDF documents before printing. The software is based on academic research from a 2018 workshop on information hiding and multimedia security.
key points
- Nearly all commercial color laser printers automatically embed systematic tracking dots containing serial numbers on every printout.
- DEDA provides tools to parse, extract, compare, and generate tracking dot matrices from 300 dpi scanned documents.
- Anonymisation involves printing a calibration page, scanning it to generate a printer-specific mask, and applying that mask to source PDFs.
who should read it
Privacy advocates, security researchers, and technical users interested in printer forensics and hardware tracking.
discussion mixed
Reportedly, OpenPrinter will not have these dots by default. I did wonder if this omission would cause them issues. As I understand it, the dots are not mandated by law.
It raises the question of whether alternative printers that omit tracking dots face legal or regulatory pressure.
Generated by an LLM from the article and thread. Check the sources before relying on it.