Top Ten off-shore Countries using Hidden Proxies in US | Information Security News – SecurityWeek: IT Security News & Expert Insights

Fighting web fraud is a game of cat and mouse between fraud analysts and cybercriminals where the odds are stacked against fraud analysts. The bad guys have the upper hand pitting tools, targets, time and tenacity against fraud analysts doing their best to identify fraudulent transactions, prevent web fraud while at the same time not stopping good customers from transacting at their web site. Intentify Cybercrime Patterns

The fraud analysts I’ve met are diligent, always looking for edge that puts them ahead of scammers. For fraud analysts getting hit by web fraud is personal—like the feeling of violation you would get opening your front door and discovering someone broke into your house. What gives fraud analysts edge against scammers? Data. Like all things digital, web fraud is measurable and mineable.

How does data help fraud analysts stop and prevent fraud? It depends on the nature and context of the transaction. I’ll use an example from the non-digital realm to illustrate. I came across new research by UCLA scientists working with L.A. police to analyze crime patterns in order to identify crime ‘hotspots.’ The research is federally funded by the National Science Foundation and the U.S. Department of Defense. The researchers developed a mathematical model that enables them to predict how “each type of crime hotspot will respond to increased policing, as well as when each type might occur, by a careful mathematical analysis involving what is known as bifurcation theory” according to a UCLA report. The researchers leverage crime data to determine “whether a particular neighborhood will see an increase in crime.” One of the researches, Jeffrey Brantington, observes that “criminal offenders are essentially hunter-gatherers; they forage for opportunities to commit crimes.” Brantington’s observation applies to cybercriminals as well as local neighborhood carjackers.

Fraud analysts leverage data too—to discern patterns and identify cybercrime hotspots. Doing so enables them to adjust their strategy according to the patterns. This insight helps them increase their effectiveness at detecting fraud—and more importantly it helps them go on the offensive to prevent fraud. Here’s a simple example that illustrates how understanding patterns can help head-off fraud.

I queried our ThreatMetrix Fraud Network of global transaction data to see which countries for the month of May had the highest percent of transactions that were conducted using hidden proxies located in the United States. This view of web transaction traffic provides a window into behaviors that can be useful in identifying patterns that tip off cybercrime hot spots still in formation—a system fraud analysts can use to thwart scammers before they strike by tuning the rules that examine transactions looking for risk.

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