The “shelf-life” of devices is a frequently studied topic in web fraud detection. The basic question is: how long does a device remain active and relevant from the perspective of a fraud analyst? Understanding at what age a device typically ceases to be active is an important factor in designing a device recognition system that can be efficient and effective for mitigating fraud.

Since device recognition provides the platform for iovation’s Device Reputation service, we recently conducted a study to examine device shelf-life. The study looked at all transactions seen by ReputationManager over a multi-day period and identified the age of each device associated to fraudulent behavior during that period. The distribution of devices by age—depicted in the chart below—shows that 57 percent of devices involved in fraud during that period were initially identified by iovation more than 90 days prior to the transaction. (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…)

IP Addresses have long been used in device fingerprinting solutions, but their utility has been hit-and-miss due to differences in how groups of IP addresses are managed. As a result, solutions relying on the IP address for device identification generally experience high false positive rates; this is especially true in cases where the same IP address has been issued to different end users over time.

Based on data iovation has collected from performing over two billion device identification requests, we’ve developed techniques to more accurately assess the relevance of an IP address in identifying and re-recognizing a device. This allows us to use IP address as a factor, when appropriate, and ignore it when not. (more…)