Partition clustering for GIS map data protection

Ahmed Abubahia, Mihaela Cocea

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

One of the main research issues of digital data is defined by copyright protection, and digital watermarking is a potential solution to this issue. While there is an abundance of research on digital watermarking for image data, there is far less research on digital watermarking for vector map data, a data format used to store complex information in Geographical Information Systems (GIS). Recently, data mining methods have been used in the process of watermarking vector data. In this paper, we argue that the security of the watermarked vector maps can be increased by employing more suitable data mining methods. In particular, in this paper, we advocate the use of kmedoids partition clustering and compare its deployment with a previous watermarking scheme in which k-means partition clustering is used. The experimental results show that it outperforms the approach based on k-means according to a set of evaluation metrics.
Original languageEnglish
Title of host publication2014 IEEE 26th international conference on tools with artificial intelligence
Subtitle of host publicationICTAI 2014 10-12 November 2014, Limassol, Cyprus
Place of PublicationPiscataway
PublisherIEEE
Pages830-837
ISBN (Print)9781479965724
DOIs
Publication statusPublished - 2014
EventIEEE 26th International Conference on Tools with Artificial Intelligence - Limassol, Cyprus
Duration: 10 Nov 201412 Nov 2014

Conference

ConferenceIEEE 26th International Conference on Tools with Artificial Intelligence
Abbreviated titleICTAI 2014
Country/TerritoryCyprus
CityLimassol
Period10/11/1412/11/14

Keywords

  • Clustering algorithms
  • Clustering methods
  • Geographic information systems
  • Robustness
  • Vectors
  • Watermarking
  • ESRI shapefile
  • GIS
  • copyright protection
  • digital watermarking
  • k-medoids partition clustering
  • vector data

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