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MINING MASSIVE DATA SETS FOR SECURITY
Penulis: Francoise Fogelman-Soulie •
Identifier: --francoisef-1335
The ever growing flood of data arises from many different sources: huge databases
store increasing amounts of data on customers, sales, expenses, traveling, credit card
usage, tax payments and the like; the Web gives us access to basically unlimited information in the form of text, images, videos and sound. Everything we do leaves an information trail which can potentially be stored and used. Most of the times, the uses are
beneficial (providing us with a list of our expenses, information on our next trip or the
delivery of some book we bought on the Web ”¦), but sometimes this information can
also be exploited by rogues to put us at risk (identity theft, credit card fraud, intrusion
on a sensitive computer network, terrorism ”¦). Information security breach is thus
becoming an every-day threat for the citizens of modern societies and – when linked to
terrorism – it is becoming more and more dangerous. However, discriminating good
uses from bad ones is not easy if we want to maintain our standards of democracy and
individual freedom. We therefore need to develop different – both efficient and noninvasive – security applications that can be deployed across a wide range of activities
in order to deter and to detect the bad uses.