Reliable user authentication is becoming an increasingly important task in the Web-enabled world. The consequences of an insecure authentication system in a corporate or enterprise environment can be catastrophic, and may include loss of confidential information, denial of service, and compromised data integrity. The value of reliable user authentication is not limited to just computer or network access. Many other applications in everyday life also require user authentication, such as banking, e- commerce, and physical access control to computer resources, and could benefit from enhanced security.
The prevailing techniques of user authentication, which involve the use of either passwords and user IDs (identifiers), or identification cards and PINs (personal identification numbers), suffer from several limitations. Passwords and PINs can be illicitly acquired by direct covert observation. Once an intruder acquires the user ID and the password, the intruder has total access to the user's resources. In addition, there is no way to positively link the usage of the system or service to the actual user, that is, there isno protection against repudiation by the user ID owner. For example, when a user ID and password is shared with a colleague there is no way for the system to know who the actual user is. A similar situation arises when a transaction involving a credit card number is conducted on the Web. Even though the data are sent over the Web using secure encryption methods, current systems are not capable of assuring that the rightful owner of the credit card initiated the transaction.
In the modern distributed systems environment, the traditional authentication policy based on a simple combination of user ID and password has become inadequate. Fortunately, automated biometrics in general, and fingerprint technology in particular, can provide a much more accurate and reliable user authentication method. Biometrics is a rapidly advancing field that is concerned with identifying a person based on his or her physiological or behavioral characteristics. Examples of automated biometrics include fingerprint, face, iris, and speech recognition. User authentication methods can be broadly classified into three categories as shown in Table 1.1. Because a biometric property is an intrinsic property of an individual, it is difficult to surreptitiously duplicate and nearly impossible to share. Additionally, a biometric property of an individual can be lost only in case of serious accident.
Biometric readings, which range from several hundred bytes to over a megabyte, have the advantage that their information content is usually higher than that of a password or a pass phrase. Simply extending the length of passwords to get equivalent bit strength presents significant usability problems. It is nearly impossible to remember a 2K phrase, and it would take an annoyingly long time to type such a phrase (especially without errors). Fortunately, automated biometrics can provide the security advantages of long passwords while retaining the speed and characteristic simplicity of short passwords.
Even though automated biometrics can help alleviate the problems associated with the existing methods of user authentication, hackers will still find there are weak points in the system, vulnerable to attack. Password systems are prone to brute force dictionary attacks. Biometric systems, on the other hand, require substantially more effort for mounting such an attack. Yet there are several new types of attacks possible in the biometrics domain. This may not apply if biometrics is used as a supervised authentication tool. But in remote, unattended applications, such as Web-based e-commerce applications, hackers may have the opportunity and enough time to make several attempts, or even physically violate the integrity of a remote client, before detection.
A problem with biometric authentication systems arises when the data associated with a biometric feature has been compromised. For authentication systems based on physical tokens such as keys and badges, a compromised token can be easily canceled and the user can be assigned a new token. Similarly, user IDs and passwords can be changed as often as required. Yet, the user only has a limited number of biometric features (one face, ten fingers, two eyes). If the biometric data are compromised, the user may quickly run out of biometri features to be used for authentication
Figure 3.2 illustrates the identity verification process. The biometric image is again captured. The unique characteristics are extracted from the biometric image to create the users "live" biometric template. This new template is then compared with the template previously stored and a numeric matching score is generated, based on the percentage of duplication between the live and stored template. System designers determine the threshold value for this identity verification score based upon the security requirements of the system
Figure 3.2 Schematic of a verification process
Secure identification systems use biometrics for two basic purposes: to identify or authenticate individuals. Identification (1-to-many comparison) verifies if the individual exists within a known population. Identification confirms that the individual is not enrolled with another identity and is not on a predetermined list of prohibited persons. Identification will typically need a secured database containing a list of all applying individuals and their biometrics. The biometric for the individual being considered for enrollment would be compared against all stored biometrics. For many applications, an identification process is used only at the time of enrollment to verify that the individual is not already enrolled.
Authentication (1-to-1 comparison) confirms that the credential belongs to the individual presenting it. In this case, the device that performs the authentication must have access only to the individual's enrolled biometric template, which may be stored locally or centrally.