Visualizing and Securing Linguistic Patterns: POS Tag Graphs with Encryption Techniques

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

Digital Content protection is important Ensuring document integrity in the digital age is a critical challenge. Traditional visible and invisible watermarking methods offer partial protection but have limitations. Visible watermarking can be removed and degrade quality, while invisible watermarking requires specialized tools and may degrade through compression. TThis study presents an innovative document authentication framework that leverages part-of-speech (POS) tag-based graph representations. By transforming textual data into structured graphs, the method captures the unique syntactic signature of each document. This linguistic fingerprint is then encrypted and stored independently, enabling robust verification of document authenticity. The approach not only reinforces security and integrity but also seamlessly integrates with existing natural language processing (NLP) pipelines.

Original languageEnglish
Title of host publication2025 IEEE/ACIS 23rd International Conference on Software Engineering Research, Management and Applications, SERA 2025 - Proceedings
EditorsYeong-Tae Song, Mingon Kang, Junghwan Rhee
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages419-423
Number of pages5
ISBN (Electronic)9798331565367
ISBN (Print)9798331565367
DOIs
StatePublished - May 29 2025
Event23rd IEEE/ACIS International Conference on Software Engineering Research, Management and Applications, SERA 2025 - Las Vegas, United States
Duration: May 29 2025May 31 2025

Publication series

Name2025 IEEE/ACIS 23rd International Conference on Software Engineering Research, Management and Applications (SERA)

Conference

Conference23rd IEEE/ACIS International Conference on Software Engineering Research, Management and Applications, SERA 2025
Country/TerritoryUnited States
CityLas Vegas
Period05/29/2505/31/25

Scopus Subject Areas

  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence
  • Computer Science Applications
  • Software
  • Information Systems and Management

Keywords

  • NLP
  • Natural Language Processing
  • POS

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