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Detecting fraud in the real world. (English) Zbl 1010.68064

Abello, James (ed.) et al., Handbook of massive data sets. Dordrecht: Kluwer Academic Publishers. Massive Comput. 4, 911-929 (2002).
Summary: Finding telecommunications fraud in masses of call records is more difficult than finding a needle in a haystack. In the haystack problem, there is only one needle that does not look like hay, the pieces of hay all look similar, and neither the needle nor the hay changes much over time. Fraudulent calls may be rare like needles in haystacks, but they are much more challenging to find. Callers are dissimilar, so calls that look like fraud for one account look like expected behavior for another, while all needles look the same.
Moreover, fraud has to be found repeatedly, as fast as fraud calls are placed, the nature of fraud changes over time, the extent of fraud is unknown in advance, and fraud may be spread over more than one type of service. For example, calls placed on a stolen wireless telephone may be charged to a stolen credit card. Finding fraud is like finding a needle in a haystack only in the sense of sifting through masses of data to find something rare. This chapter describes some issues involved in creating tools for building fraud systems that are accurate, able to adapt to changing legitimate and fraudulent behavior, and easy to use.
For the entire collection see [Zbl 0986.00022].

MSC:

68P25 Data encryption (aspects in computer science)
68P05 Data structures
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