Stanislav Belyakov
ABSTRACT
The paper considers the flow of cartographic data that arises when solving applied problems by visual analysis of maps, plans or schemes. The flow arises in the process of interactive user-analytics and geographic information services. It is assumed that to solve the task the analyst builds the working area of the analysis, filling it with the necessary objects and relationships. The paper discusses the vulnerability of the analysis process, which is due to the influence of objects with defects on the analyst's situational awareness. An attack using this vulnerability is described. The result of the attack is making inadequate decisions and the occurrence of damage. The paper considers the analysis of the security of the data stream from the geoservice to the client. A model for estimating the allowable level of defects is proposed. A method of analyzing the "characteristic" points of the time series describing the cartographic images in the session is proposed. A method for finding a protective context from a set of contexts used by a server is proposed.
- P. A. Longley, M. Goodchild, D. J. Maguire and D. W. Rhind, Geographic Information Systems and Sciences, 3rd ed. Wiley, 2011.Google Scholar
- S. Shashi, X. Hui, Encyclopedia of GIS. New York: SpringerScience+Buisiness Media, LLC, 2008.Google Scholar
- M.F. Goodchild (2007) Citizens as sensors: the world of volunteered geography. GeoJournal, 69(4), 211--221.Google ScholarCross Ref
- https://www.autodesk.com/products/autocad/included-toolsetsGoogle Scholar
- https://www.esri.com/en-us/arcgis/about-arcgis/overviewGoogle Scholar
- R. Alguliyev, Y. Imamverdiyev, L. Sukhostat (2018). Cyber-physical systems and their security issues, Computers in Industry, 100(9), 212--223.Google ScholarCross Ref
- S. Ntalampiras (2016). Automatic identification of integrity attacks in cyber-physical systems, Expert Systems with Applications, 58(10), 164--173.Google ScholarDigital Library
- Y. Z. Lun, A. D'Innocenzo, F. Smarra, I. Malavolta, M. D. Di Benedetto (2019). State of the art of cyber-physical systems security: an automatic control perspective, Journal of Systems and Software, 149(3), 174--216.Google Scholar
- K. Ooms, G. Andrienko, N. Andrienko, P. De Maeyer, V. Fack (2012). Analysing the spatial dimension of eye movement data using a visual analytic approach, Expert Systems with Applications, 39, 1324--1332.Google ScholarDigital Library
- A. Dey, G. Abowd (2000). Towards a better understanding of context and context-awareness, CHI 2000 Workshop on the What, Who, Where, When, and How of Context-Awareness, pp. 304--307.Google ScholarDigital Library
- M. Berndtsson, J. Mellin 2018 Active Database Knowledge Model, Encyclopedia of Database Systems, Liu L., Özsu M.T. (eds). Springer, New York.Google Scholar
- D. Kotkov, S. Wang, J. Veijalainen (2016). Survey of serendipity in recommender systems. Knowledge-Based Systems, 111(8), 180--192Google ScholarDigital Library
Index Terms
- Safety analysis of the flow of cartographic data with defects
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