The security strategy of “defense-in-depth” allows a system or an organization to prevent an attack by coordinating complementary defense techniques, taking advantage of the strengths of each one while relying on the combination to shore up weaknesses in the others.  The end result is a more complex and nuanced system that is resilient to a much greater number of attacks.

In a similar vein, we can see that any single device recognition strategy on the Web is going to run into some serious limitations, mostly related to the quality and the variety of the data that can be collected from a browser.  There are a number of sources of data that we can use to construct a view of a device on the Web, but most of them can be manipulated, and all of them have problems with uniqueness.  How to build a system that is resilient to so much data uncertainty?  Yeah, I know you’re already a step ahead of me – we design in depth. (more…)

As iovation continues to expand its subscriber-base across multiple industries, the number of shared devices (meaning those devices seen at multiple sites) continues to rise. As we see this cross-over between subscribers rise, new and existing subscribers have a greater chance of encountering devices that already have a reputation. This increases the proactive value of device reputation and directly supports the significance of having a shared device database.

The increase in the number of shared devices can in part be understood by analyzing the population of “reactivated” devices. Reactivated devices are devices that iovation re-identifies after having not seen the device for more than 90 days. By studying these devices in contrast to the device population as a whole, it is clear that iovation’s expanding customer base is a significant contributor to this trend as a vast majority of reactivated devices have been seen in multiple customer networks. (more…)

When I talk with fraud managers, they often express concern that the benefits of a reputation-based system won’t be instantly apparent. While a reputation service inherently becomes more valuable over time as companies log their fraud experiences into the system, it’s worth pointing out that device recognition and device reputation provide a number of benefits that can have an immediate effect, such as the following:

• Expose relationships between transactions –Device recognition gives fraud management teams instant visibility into the relationships between all online transactions (fraudulent or not). This provides immediate value in assisting with investigations and resolving issues.
• Receive velocity alerts –The number of purchases, applications, account creations, etc. that originate from one user in a given period of time is highly indicative of fraudulent behavior. For example, wouldn’t it be valuable to know that in the span of one hour, ten credit card applications were all submitted by one person? Unfortunately, since most fraudsters use fake or stolen identities, this can be incredibly hard to detect—unless you focus on the device. With device recognition, you can monitor the velocity of transactions coming from a single device, regardless of the identities provided.

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