The BIRT methodology will aid biometric system designers in making effective refinements in their systems. The measurement of biological characteristics (biometrics) such as fingerprints and facial images provides a means of identification that neither needs to be carried nor remembered. Evaluation of biometrics has traditionally been focused on the ability of biometric systems to identify members from a population, e.g., for purposes of authentication. As these systems come into more widespread use, attempts will naturally be made to test and frustrate their ability to identify individuals. Understanding these attempts requires a fundamental new analytic approach, based on modeling the capabilities of an adversary with full generality. BIRT develops the adversary model using the information controlled by the adversary, e.g., for recognition, the clothing, glasses and makeup they wear. BIRT uses disinformation theory to abstractly model the adversary capabilities to mask their identity from an interested observer. Disinformation theory is inspired by Shannon's information theoretic model for communications systems, but views the ?noise source? as controlled by the adversary, abstractly modeling the capacity of the adversary to control the noise in the channel (for example, by transforming the image ?signal?) between the biometric sender being identified and the biometric system receiving the identifying information. Face recognition systems will be used to gain experience with and refine the disinformation theory models, with a variety of disguises used as disinformation sources.
CT-ISG: BIRT - Biometric Identification Red Team