Exploiting vector map properties for GIS data copyright protection

Ahmed  Abubahia; Mihaela Cocea

doi:10.1109/ICTAI.2015.89

Exploiting vector map properties for GIS data copyright protection

Ahmed Abubahia, Mihaela Cocea

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

88 Downloads (Pure)

Abstract

Geographic Information System (GIS) vector maps have become more widely available, prompting a need to prevent their unauthorized use. This is commonly done through the use of a digital watermark, with many approaches
applying techniques from image map watermarking, without exploiting the particular properties of vector map data. In previous work we showed that using k-medoids clustering and the bounding box property of vector maps in the embedding process leads to increased robustness against simplification (removing vertices from vector data) and interpolation (adding new vertices to the data) attacks, which may distort the watermark and prevent the identification of the map owner. In this paper we show that the advantages of using the bounding box property are maintained even with a different clustering
approach (k-means), and argue that they would hold regardless of the method used for identifying the watermark embedding locations in the map.

Original language	English
Title of host publication	Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	575 - 582
Number of pages	8
ISBN (Electronic)	978-1-5090-0163-7, 978-1-5090-0162-0
DOIs	https://doi.org/10.1109/ICTAI.2015.89
Publication status	Published - 7 Jan 2016
Event	2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI) - Vietri sul Mare, Italy Duration: 9 Nov 2015 → 11 Nov 2015

Conference

Conference	2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)
Country/Territory	Italy
City	Vietri sul Mare
Period	9/11/15 → 11/11/15

Access to Document

10.1109/ICTAI.2015.89

ICTAI2015
© © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Accepted author manuscript (Post-print), 676 KB

Cite this

@inproceedings{45b5ab65c06f43ef96f4c623755dfd74,

title = "Exploiting vector map properties for GIS data copyright protection",

abstract = "Geographic Information System (GIS) vector maps have become more widely available, prompting a need to prevent their unauthorized use. This is commonly done through the use of a digital watermark, with many approachesapplying techniques from image map watermarking, without exploiting the particular properties of vector map data. In previous work we showed that using k-medoids clustering and the bounding box property of vector maps in the embedding process leads to increased robustness against simplification (removing vertices from vector data) and interpolation (adding new vertices to the data) attacks, which may distort the watermark and prevent the identification of the map owner. In this paper we show that the advantages of using the bounding box property are maintained even with a different clusteringapproach (k-means), and argue that they would hold regardless of the method used for identifying the watermark embedding locations in the map.",

author = "Ahmed Abubahia and Mihaela Cocea",

year = "2016",

month = jan,

day = "7",

doi = "10.1109/ICTAI.2015.89",

language = "English",

pages = "575 -- 582",

booktitle = "Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI) ; Conference date: 09-11-2015 Through 11-11-2015",

}

Abubahia, A & Cocea, M 2016, Exploiting vector map properties for GIS data copyright protection. in Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). Institute of Electrical and Electronics Engineers Inc., pp. 575 - 582, 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), Vietri sul Mare, Italy, 9/11/15. https://doi.org/10.1109/ICTAI.2015.89

TY - GEN

T1 - Exploiting vector map properties for GIS data copyright protection

AU - Abubahia, Ahmed

AU - Cocea, Mihaela

PY - 2016/1/7

Y1 - 2016/1/7

N2 - Geographic Information System (GIS) vector maps have become more widely available, prompting a need to prevent their unauthorized use. This is commonly done through the use of a digital watermark, with many approachesapplying techniques from image map watermarking, without exploiting the particular properties of vector map data. In previous work we showed that using k-medoids clustering and the bounding box property of vector maps in the embedding process leads to increased robustness against simplification (removing vertices from vector data) and interpolation (adding new vertices to the data) attacks, which may distort the watermark and prevent the identification of the map owner. In this paper we show that the advantages of using the bounding box property are maintained even with a different clusteringapproach (k-means), and argue that they would hold regardless of the method used for identifying the watermark embedding locations in the map.

AB - Geographic Information System (GIS) vector maps have become more widely available, prompting a need to prevent their unauthorized use. This is commonly done through the use of a digital watermark, with many approachesapplying techniques from image map watermarking, without exploiting the particular properties of vector map data. In previous work we showed that using k-medoids clustering and the bounding box property of vector maps in the embedding process leads to increased robustness against simplification (removing vertices from vector data) and interpolation (adding new vertices to the data) attacks, which may distort the watermark and prevent the identification of the map owner. In this paper we show that the advantages of using the bounding box property are maintained even with a different clusteringapproach (k-means), and argue that they would hold regardless of the method used for identifying the watermark embedding locations in the map.

UR - https://sites.google.com/site/ictai2015italy/

U2 - 10.1109/ICTAI.2015.89

DO - 10.1109/ICTAI.2015.89

M3 - Conference contribution

SP - 575

EP - 582

BT - Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)

Y2 - 9 November 2015 through 11 November 2015

ER -

Exploiting vector map properties for GIS data copyright protection

Abstract

Conference

Access to Document

Fingerprint

Cite this