Narrative of the Iris Algorithm

Now that we know what constitutes the iris biometric, and how it can be captured, we need to know how the algorithm works.

Once an iris is captured, it is then transformed into a template that is 2,048 bits in length. To evaluate a live template to the orientation template, a simple restricted OR (XOR) operation is done on the two values. Their equivalent mask bit vectors are used in an AND operation to verify that there were no artifacts affecting the assessment. The norms of the resulting XOR and operations are used to calculate a Hamming Distance. The Hamming Distance is a establish of difference between the two iris templates. This distance is then used to conclude whether there is a match or not. Since there are many degrees of independence in the iris code, a relatively large Hamming Distance can be used to still assurance a near-zero FAR. This simplicity of the algorithm allows for very fast matching in the range of 100,000 per second on a 300MHz machine.

How Can This Biometric Be Spoofed?

The iris is an extremely difficult trait to spoof, yet there have been attempts at spoofing. There is little doubt that others will try and, given enough time, money, and energy, they may be successful. Attacks on the iris biometric fall into the following categories:

·         Attacking the physical iris

·         Using artifacts

·         offensive the communications

·         Compromising the pattern

·         offensive the fallback system

Iris biometrics appears to offer the Holy Grail of biometrics. Iris biometrics is quick, robust, and fast to measure up to, and refuse to accept spoofing better than any other trait so, this should be the ideal biometric for network security. From a pure technological position, it is the clear winner, hands down. The last difficulty to be answered is: Why has the iris biometric not overtaken every other biometric and been widely deployed? The reasons are quite simple:

1.    Hardware cost— particular cameras are still necessary. These cameras need to have their own exclusive light source. As such, there are only certain economies of scale that can be leveraged to decrease the cost of the hardware. Sustained research in this area will yield lower-cost products.

2.    User awareness— Even though it is quite clear that the infrared light being used is completely safe, the mere thought of incredible being shined into the eye is disturbing to the user.

3.    Placement— to get the iris in the proper position takes a fair amount of management. Therefore, some users will never be able to use the product, and others will require longer times to become fully familiar to its use. Some cameras use eye acknowledgment techniques to try to auto-pan and focus the camera. These solutions, while better, do increase the cost of the camera and may still require some user management.

4.    Size— while the current size of the camera has been summary to that of a desktop camera on steroids, it is still rather large. As the camera decreases in size, it will become easier to find the required desk real estate for its consumption.