Abstract
This chapter explores methods for determining the reliability of Automated Identification System (AIS) messages. The primary use of AIS messages in the naval domain is to avoid collisions, therefore they contain kinematic information about ships. Moreover, AIS messages contain information like the ship name and its identifiers, so AIS messages can be used to identify ships. However, since the information contained in these messages is not necessarily correct (because, for instance, a malicious sender might want to declare a different identity than its own), in order to properly use them, we should assess their trust level. In general, trust is an important concept that helps to take decisions when the available information is limited or contradicting. In the case of AIS messages, this might occur when only few messages about a given ship are available or when messages conflict either against themselves or against other sources like Web sites reporting ship information. We describe ongoing work about the quantification of trust assessments in AIS messages, by means of statistical and logical analysis and by enriching AIS messages with information obtained from the Web.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
For instance, in 2010 the fleet of an Iranian company tried to disguise its identity. See: http://www.nytimes.com/2010/06/08/world/middleeast/08sanctions.html?pagewanted=all
- 2.
In particular, we crawled http://www.vesseltracker.com and http://www.shipais.com websites
- 3.
In particular we crawled the International Telecomunication Union website (http://www.itu.int/online/mms/glad/cga_mids.sh?lng=E) and from Citymap HQ website (http://www.citymaphq.com/codes/itu.html)
- 4.
References
Castelfranchi C, Falcone R (2000) Trust is much more than subjective probability: mental components and sources of trust. In: Proceedings of the 33rd Hawaii international conference on system sciences, HICSS2000, vol 6, pp 154–165
Ceolin D, Groth P, van Hage WR (2010) Calculating the trust of event descriptions using provenance. In: Sahoo SS, Zhao J, Missier P, Gomez-Perez JM (eds) Second international workshop on the role of semantic web in provenance management (SWPM 2010). http://ceur-ws.org/Vol-670/completeSWPM10Proceedings.pdf
Ceolin D, van Hage WR, Fokkink W (2010) A trust model to estimate the quality of annotations using the web. In: Web science conference (WebSci10), 26–27 Apr 2010. http://journal.webscience.org/315
Ceolin D, van Hage WR, Fokkink W, Schreiber G (2011) Estimating uncertainty of categorical web data. In: Bobillo F et al (eds) 7th international workshop on uncertainty reasoning for the semantic web (URSW 2011), pp 15–26. http://ceur-ws.org/Vol-778/proceedings.pdf
Dempster A (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 2(38):325–339
Ferguson TS (1973) A bayesian analysis of some nonparametric problems. Ann Stat 1(2):209–230
Fink D (1995) A compendium of conjugate priors. Technical report, Cornell University
Jøsang A (2007) Probabilistic logic under uncertainty. In: Gudmundsson J, Jay CB (eds), Theory of computing 2007. Proceedings of the thirteenth computing: the Australasian theory symposium (CATS2007), Ballarat, Victoria, Australia, proceedings, ser. CRPIT, Jan 30 – Feb 2, 2007, vol 65, pp 101–110. Australian Computer Society, Darlinghurst
Jøsang A, McAnally D (2005) Multiplication and comultiplication of beliefs. Int J Approx Reason 38(1):19–51
Moreau L, Clifford B, Freire J, Futrelle J, Groth P, Gil Y, Kwasnikowska N, Miles S, Missier P, Myers J (2010) The open provenance model core specification (v1.1). Futur Gener Comput Syst (online). Available: http://dx.doi.org/10.1016/j.future.2010.07.005
Pitman J (1995) Exchangeable and partially exchangeable random partitions. Probab Theory Relat Fields 102(2):145–158
Raiffa H, Schlaifer R (1968) Applied statistical decision theory. MIT, Cambridge
Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton
Acknowledgements
This research has been carried out as a part of the Poseidon project at Thales under the responsibility of the Embedded Systems Institute (ESI). This project is partially supported by the Dutch Ministry of Economic Affairs under the BSIK program.
We would like to thank the editors for their effort spent in reviewing this chapter.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Ceolin, D., van Hage, W.R., Schreiber, G., Fokkink, W. (2013). Assessing Trust for Determining the Reliability of Information. In: van de Laar, P., Tretmans, J., Borth, M. (eds) Situation Awareness with Systems of Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6230-9_13
Download citation
DOI: https://doi.org/10.1007/978-1-4614-6230-9_13
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-6229-3
Online ISBN: 978-1-4614-6230-9
eBook Packages: EngineeringEngineering (R0)