Analysis on credit card fraud detection methods
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- @InProceedings{Raj:2011:ICCCET,
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author = "S. Benson Edwin Raj and A. Annie Portia",
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title = "Analysis on credit card fraud detection methods",
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booktitle = "2011 International Conference on Computer,
Communication and Electrical Technology (ICCCET)",
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year = "2011",
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month = mar,
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pages = "152--156",
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abstract = "Due to the rise and rapid growth of E-Commerce, use of
credit cards for online purchases has dramatically
increased and it caused an explosion in the credit card
fraud. As credit card becomes the most popular mode of
payment for both online as well as regular purchase,
cases of fraud associated with it are also rising. In
real life, fraudulent transactions are scattered with
genuine transactions and simple pattern matching
techniques are not often sufficient to detect those
frauds accurately. Implementation of efficient fraud
detection systems has thus become imperative for all
credit card issuing banks to minimise their losses.
Many modern techniques based on Artificial
Intelligence, Data mining, Fuzzy logic, Machine
learning, Sequence Alignment, Genetic Programming etc.,
has evolved in detecting various credit card fraudulent
transactions. A clear understanding on all these
approaches will certainly lead to an efficient credit
card fraud detection system. This paper presents a
survey of various techniques used in credit card fraud
detection mechanisms and evaluates each methodology
based on certain design criteria.",
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keywords = "genetic algorithms, genetic programming, survey",
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DOI = "doi:10.1109/ICCCET.2011.5762457",
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notes = "Also known as \cite{5762457}",
- }
Genetic Programming entries for
S Benson Edwin Raj
A Annie Portia
Citations