JetLib News

As anyone who has ever had a valid credit card charge questioned knows, there is a lot of fraudulent use of cards and the Internet has made it even easier for the bad guys to exploit. According to comScore, last year ecommerce in the U.S. reached record levels of spending with more than $160 billion in transactions. With all this activity, it is like looking for the proverbial needle in a very large haystack to try to track down fraudulent transactions. But a look into a couple of new fraud detection and prevention technologies shows that perhaps the good guys are making some inroads in this war.

First is the news that MasterCard is working with Silver Tail Systems to map abnormal Web traffic flows on ecommerce sites. MasterCard has its own detection algorithms that handle things it observes across its payment processing network, but this shows that more effort is needed to understand the ways that fraud happens online too. Expect to see more of these partnerships in the years to come.

A second company that is working in this area is Norse Corporation, a St. Louis-based company that monitors the Internet looking for fraudsters. Their IPViking customers are the banking and payment processors that want more intelligence about who is buying goods and services online, before the transactions hit the payment networks to be processed.

Norse places millions of monitors around the global Internet, looking for anomalies in transactions that are being attempted on various ecommerce sites. Its approach is similar to what Network Box does for general managed general security exploit detection. Take a look at this transaction, which originated from a Brazilian IP address that has been used in the past to launch denial of service attacks and is associated with Brazilian organized crime? The transaction was done on a French ecommerce site and the payment was supposed to be handled by a US-based processor. Norse caught it in time and the payment was refused.

Here is another example of their intelligent network in operation. They found over a series of weeks late last year a set of transactions that originated with Chinese IP addresses using proxy services in Russia, France and China. This means that the originating IP address has been hidden thanks to the proxy, so in theory these seemingly random transactions wouldn’t normally be grouped together. Yet all of the transactions were for funeral home services, and appear to be a situation where someone is testing a card number to see if it can be used for more extensive fraud.

You can see that by detecting these and other patterns, such as a batch of transactions hitting the same ecommerce site within a few seconds of each other (indicating a potential bot net), they can provide a tremendous intelligence to the site owners and help to stop fraud before the transactions are even processed.

As anyone who has ever had a valid credit card charge questioned knows, there is a lot of fraudulent use of cards and the Internet has made it even easier for the bad guys to exploit. According to comScore, last year ecommerce in the U.S. reached record levels of spending with more than $160 billion in transactions. With all this activity, it is like looking for the proverbial needle in a very large haystack to try to track down fraudulent transactions. But a look into a couple of new fraud detection and prevention technologies shows that perhaps the good guys are making some inroads in this war.

First is the news that MasterCard is working with Silver Tail Systems to map abnormal Web traffic flows on ecommerce sites. MasterCard has its own detection algorithms that handle things it observes across its payment processing network, but this shows that more effort is needed to understand the ways that fraud happens online too. Expect to see more of these partnerships in the years to come.

A second company that is working in this area is Norse Corporation, a St. Louis-based company that monitors the Internet looking for fraudsters. Their IPViking customers are the banking and payment processors that want more intelligence about who is buying goods and services online, before the transactions hit the payment networks to be processed.

Norse places millions of monitors around the global Internet, looking for anomalies in transactions that are being attempted on various ecommerce sites. Its approach is similar to what Network Box does for general managed general security exploit detection. Take a look at this transaction, which originated from a Brazilian IP address that has been used in the past to launch denial of service attacks and is associated with Brazilian organized crime? The transaction was done on a French ecommerce site and the payment was supposed to be handled by a US-based processor. Norse caught it in time and the payment was refused.

Here is another example of their intelligent network in operation. They found over a series of weeks late last year a set of transactions that originated with Chinese IP addresses using proxy services in Russia, France and China. This means that the originating IP address has been hidden thanks to the proxy, so in theory these seemingly random transactions wouldn’t normally be grouped together. Yet all of the transactions were for funeral home services, and appear to be a situation where someone is testing a card number to see if it can be used for more extensive fraud.

You can see that by detecting these and other patterns, such as a batch of transactions hitting the same ecommerce site within a few seconds of each other (indicating a potential bot net), they can provide a tremendous intelligence to the site owners and help to stop fraud before the transactions are even processed.

Facial recognition and detection software is a hot button issue on the web right now. Facebook has stirred a hornets nest by using facial recognition with users pictures, prompting people to tag their friends that Facebook has recognized. Google has said that is a line of creepy it will not cross.

Facial detection software is not just limited to the web though. A new startup in Chicago called SceneTap uses facial detection and people-counting cameras to scope out your local bar to tell you “what is going on.” What is the male-to-female ratio at your favorite club? Who is buying drinks? SceneTap cameras see it all and provide the data to users and bar owners. Seem a little creepy? Maybe not as much as you might think.

The stated goal of SceneTap is to give real-time information into your local bar scene. As such, it is a location-based service that gives you information, deals and social media connections, location information and more. It is kind of like Yelp plus Foursquare plus Groupon with Facebook and Twitter integration, operating in real-time.

According to founder and CEO Cole Harper, the cameras used by SceneTap are not meant to be looked at by anyone. There is a demarcation between “facial detection” and “facial recognition” that SceneTap says it does not broach. The way it works is that there is a camera facing the door of the bar. A person comes in and the camera creates a box around the face, analyzing the eyes, nose and facial structure. It takes that data and scans it through a database to find the most similar type of match. Are you a 25-year-old female? That is what the SceneTap camera is trying to find out.

The cameras are not monitored by people and information is not stored. Bar owners do not have access to the feeds as the stream is encrypted from the backend. SceneTap does technically have access to the visual feed but Harper says that it would only be used for maintenance.

Big Data for Bar Owners for the First Time

The value proposition for bar goers and bar owners is significant. Fundamentally, SceneTap is trying to bring big data on a granular level to the restaurant industry. It analyzes what type of people are coming in, what they are buying and when they come and go. That information can be cross-referenced with promotions, advertisements and on-site staff (does Bartender A bring in more male patrons than Bartender B, for instance).

This is not the type of information that restaurants and bars have ever had access. Even with the most sophisticated point-of-sale systems, the ability to have specific gender-related data on a timeline that can be studied over a period of time is not available. Yet, add SceneTap data with the POS system and all of a sudden restaurant owners know everything about their clientele.

For bar goers, the design is meant to give real-time information to help you decide where you are going. Is Bartender A working? How many girls are there and how old are they?

SceneTap will launch in Chicago in the middle of July and have partners in select cities across the country shortly thereafter including New York, Boston, Miami, Austin, Columbus, Phoenix, St. Louis, San Diego and Las Vegas.