Single Fragment Forensic Coding from Van Der Corput Sets

  • Junsheng Liu
  • , Netanel Raviv

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Three-dimensional (3D) printing's accessibility enables rapid manufacturing but also poses security risks, such as the unauthorized production of untraceable firearms and prohibited items. To ensure traceability and accountability, embedding unique identifiers within printed objects is essential, in order to assist forensic investigation of illicit use. This paper models data embedding in 3D printing using principles from error-correcting codes, aiming to recover embedded information from partial or altered fragments of the object. Previous works embedded one-dimensional data (i.e., a vector) inside the object, and required almost all fragments of the object for successful decoding. In this work, we study a problem setting in which only one sufficiently large fragment of the object is available for decoding. We first show that for one-dimensional embedded information the problem can be easily solved using existing tools. Then, we introduce novel encoding schemes for two-dimensional information (i.e., a matrix), which enable the information to be decoded from any sufficiently large rectangle-shaped fragment. Our codes operate asymptotically close to the best possible information rate, and involve a concept from discrepancy theory called Van der Corput sets in a novel way.

Original languageEnglish
Title of host publicationISIT 2025 - 2025 IEEE International Symposium on Information Theory, Proceedings
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9798331543990
DOIs
StatePublished - 1 Jan 2025
Externally publishedYes
Event2025 IEEE International Symposium on Information Theory, ISIT 2025 - Ann Arbor, United States
Duration: 22 Jun 202527 Jun 2025

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Conference

Conference2025 IEEE International Symposium on Information Theory, ISIT 2025
Country/TerritoryUnited States
CityAnn Arbor
Period22/06/2527/06/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Single Fragment Forensic Coding from Van Der Corput Sets'. Together they form a unique fingerprint.

Cite this