Robustness of Spatial Databases against Intentional Attacks and Random Errors
Hedefalk, Finn LU
and Östman, Anders
(2010)
13th AGILE International Conference on Geographic Information Science
p.1-9
- Abstract
- Demands on the quality and reliability of volunteered geographic information have increased because of its rising popularity. Due to the less controlled data entry, there is a risk that people provide false or inaccurate information to the database. One factor that affects the effect of such updates is the structure of the database schema, which in this paper is described by network models. By analyzing GIS data models, we have found that their class diagrams have small-world properties and long-tailed distributions. Moreover, an analysis of the error and attack tolerance showed that the data models were robust against random errors but very fragile against attacks. In a network structure perspective, these results indicate that false... (More)
- Demands on the quality and reliability of volunteered geographic information have increased because of its rising popularity. Due to the less controlled data entry, there is a risk that people provide false or inaccurate information to the database. One factor that affects the effect of such updates is the structure of the database schema, which in this paper is described by network models. By analyzing GIS data models, we have found that their class diagrams have small-world properties and long-tailed distributions. Moreover, an analysis of the error and attack tolerance showed that the data models were robust against random errors but very fragile against attacks. In a network structure perspective, these results indicate that false updates on random tables of a database should usually do little harm, but falsely updating the most central cells or tables might cause big damage. Consequently, it may be necessary to monitor and constrain sensitive cells and tables in order to protect them from attacks (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7854431
- author
- Hedefalk, Finn
LU
and Östman, Anders
- publishing date
- 2010
- type
- Contribution to conference
- publication status
- published
- subject
- pages
- 9 pages
- conference name
- 13th AGILE International Conference on Geographic Information Science
- conference location
- Guimarães, Portugal
- conference dates
- 2010-05-11
- language
- English
- LU publication?
- no
- id
- 15bb1c51-bd6b-4ef9-a204-254485747210 (old id 7854431)
- alternative location
- http://agile2010.dsi.uminho.pt/pen/ShortPapers_PDF/111_DOC.pdf
- date added to LUP
- 2016-04-04 13:34:08
- date last changed
- 2019-06-14 02:19:56
@misc{15bb1c51-bd6b-4ef9-a204-254485747210,
abstract = {{Demands on the quality and reliability of volunteered geographic information have increased because of its rising popularity. Due to the less controlled data entry, there is a risk that people provide false or inaccurate information to the database. One factor that affects the effect of such updates is the structure of the database schema, which in this paper is described by network models. By analyzing GIS data models, we have found that their class diagrams have small-world properties and long-tailed distributions. Moreover, an analysis of the error and attack tolerance showed that the data models were robust against random errors but very fragile against attacks. In a network structure perspective, these results indicate that false updates on random tables of a database should usually do little harm, but falsely updating the most central cells or tables might cause big damage. Consequently, it may be necessary to monitor and constrain sensitive cells and tables in order to protect them from attacks}},
author = {{Hedefalk, Finn and Östman, Anders}},
language = {{eng}},
pages = {{1--9}},
title = {{Robustness of Spatial Databases against Intentional Attacks and Random Errors}},
url = {{https://lup.lub.lu.se/search/files/6152165/7854438.pdf}},
year = {{2010}},
}