Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
False Alarm Reduction in Maritime Surveillance
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
2016 (Engelska)Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
Abstract [en]

Context. A large portion of all the transportation in the world consists of voyages over the sea. Systems such as Automatic Identification Systems (AIS) have been developed to aid in the surveillance of the maritime traffic, in order to help keeping the amount accidents and illegal activities down. In recent years a lot of time and effort has gone into automated surveillance of maritime traffic, with the purpose of finding and reporting behaviour deviating from what is considered normal. An issue with many of the present approaches is inaccuracy and the amount of false positives that follow from it.

Objectives. This study continues the work presented by Woxberg and Grahn in 2015. In their work they used quadtrees to improve upon the existing tool STRAND, created by Osekowska et al. STRAND utilizes potential fields to build a model of normal behaviour from received AIS data, which can then be used to detect anomalies in the traffic. The goal of this study is to further improve the system by adding statistical analysis to reduce the number of false positives detected by Grahn and Woxberg's implementation.

Method. The method for reducing false positives proposed in this thesis uses the charge in overlapping potential fields to approximate a normal distribution of the charge in the area. If a charge is too similar to that of the overlapping potential fields the detection is dismissed as a false positive. A series of experiments were ran to find out which of the methods proposed by the thesis are most suited for this application.  

Results. The tested methods for estimating the normal distribution of a cell in the potential field, i.e. the unbiased formula for estimating the standard deviation and a version using Kalman filtering, both find as many of the confirmed anomalies as the base implementation, i.e. 9/12. Furthermore, both suggested methods reduce the amount of false positives by 11.5% in comparison to the base implementation, bringing the amount of false positives down to 17.7%. However, there are indications that the unbiased method has more promise.

Conclusion. The two proposed methods both work as intended and both proposed methods perform equally. There are however indications that the unbiased method may be better despite the test results, but a new extended set of training data is needed to confirm or deny this. The two methods can only work if the examined overlapping potential fields are independent from each other, which means that the methods can not be applied to anomalies of the positional variety. Constructing a filter for these anomalies is left for future study.

Ort, förlag, år, upplaga, sidor
2016. , s. 39
Nyckelord [en]
maritime surveillance, potential field, anomaly detection, bayesian learning, kalman filtering, false positive reduction
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:bth-12655OAI: oai:DiVA.org:bth-12655DiVA, id: diva2:943515
Externt samarbete
Swedish Coast Guard, HiQ
Ämne / kurs
TE2501 Examensarbete för civilingenjörer
Utbildningsprogram
DVACD Civilingenjör i datorsäkerhet
Handledare
Examinatorer
Tillgänglig från: 2016-07-01 Skapad: 2016-06-22 Senast uppdaterad: 2022-05-12Bibliografiskt granskad

Open Access i DiVA

fulltext(1371 kB)460 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 1371 kBChecksumma SHA-512
40be43ee7b4e2c229bd0f939542a6eb795a0e47be0621d548e89f0dbe84be09fded2e7620c855fbbc23152eb802032350ce72002f1ebe254c3da5e5dc139da11
Typ fulltextMimetyp application/pdf

Av organisationen
Institutionen för datalogi och datorsystemteknik
Datavetenskap (datalogi)

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 460 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

urn-nbn

Altmetricpoäng

urn-nbn
Totalt: 825 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf