Establishing fraud detection patterns based on signatures
| dc.contributor.author | Ferreira, Pedro G. | por |
| dc.contributor.author | Alves, Ronnie | por |
| dc.contributor.author | Belo, Orlando | por |
| dc.contributor.author | Cortesao, Luis | por |
| dc.date.accessioned | 2021-04-19T21:09:11Z | |
| dc.date.embargo | 10000-01-01 | |
| dc.date.issued | 2006 | |
| dc.date.updated | 2021-04-16T16:10:27Z | |
| dc.description.abstract | All over the world we have been assisting to a significant increase of the telecommunication systems usage. People are faced day after day with strong marketing campaigns seeking their attention to new telecommunication products and services. Telecommunication companies struggle in a high competitive business arena. It seems that their efforts were well done, because customers are strongly adopting the new trends and use (and abuse) systematically communication services in their quotidian. Although fraud situations are rare, they are increasing and they correspond to a large amount of money that telecommunication companies lose every year. In this work, we studied the problem of fraud detection in telecommunication systems, especially the cases of superimposed fraud, providing an anomaly detection technique, supported by a signature schema. Our main goal is to detect deviate behaviors in useful time, giving better basis to fraud analysts to be more accurate in their decisions in the establishment of potential fraud situations. | por |
| dc.description.sponsorship | Ferreira, P., Alves, R., Belo, O., & Cortesão, L. (2006, 2006//). Establishing Fraud Detection Patterns Based on Signatures. Paper presented at the Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining, Berlin, Heidelberg. | por |
| dc.distribution | international | por |
| dc.identifier.citation | Ferreira, P., Alves, R., Belo, O., & Cortesão, L. (2006, 2006//). Establishing Fraud Detection Patterns Based on Signatures. Paper presented at the Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining, Berlin, Heidelberg. | por |
| dc.identifier.doi | 10.1007/11790853_41 | por |
| dc.identifier.isbn | 3540360360 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | https://hdl.handle.net/1822/72115 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.publisher | Springer Verlag | por |
| dc.relation.publisherversion | https://link.springer.com/chapter/10.1007%2F11790853_41 | por |
| dc.rights | restrictedAccess | por |
| dc.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | por |
| dc.subject.wos | Science & Technology | |
| dc.title | Establishing fraud detection patterns based on signatures | por |
| dc.type | conferencePaper | por |
| dspace.entity.type | Publication | en |
| oaire.citationEndPage | 538 | por |
| oaire.citationStartPage | 526 | por |
| oaire.citationVolume | 4065 | por |
| sdum.bookTitle | ADVANCES IN DATA MINING | por |
| sdum.conferencePublication | ADVANCES IN DATA MINING | por |
| sdum.export.identifier | 10613 | |
| sdum.journal | Lecture Notes in Artificial Intelligence (subseries of Lecture Notes in Computer Science) | por |
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