Robustness of Spatial Databases against Intentional Attacks and Random Errors
Finn Hedefalk, Anders Östman · Lund University Publications (Lund University) · 2010
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.