Live Biometric Authenticity Check

ABSTRACT This research defined the underpinning concepts of a system that was highly secure, yet was efficient and non-invasive enough for everyday use. The live biometric authenticity check augmented invariant fingerprints with variable live features offered superior security by combining physical characteristics of the users with a passcode (numerical PIN) or passphrase (a string of words), and might also easily be augmented with other biometric video imaging devices for the utmost security. KEYWORDS: Wavelet transforms, sub-band coding, fingerprints, face recognition system, vocal input password, speaker recognition system, biometric, security, keys, anti-terrorist. I. INTRODUCTION In the context of anti-terrorists, we began with the strong hypothesis (debatable in details but in principle helped us thinking creatively outside the box) that any digital form of gatekeeper data could be duplicated somewhere on the way, and thus imitated, not secure enough for the ultimate authenticity check, while only a live person might be unique (baring the reproductive cloning). In this paper, we wish to explore how to capture the aliveness features of a user and introduce the concept of rate of denial (ROD) to quantify the degree of authenticity check of any gatekeeper system. We reviewed briefly the current state of art of hardware and software, in order to point out potential pitfalls, before augmented the invariant fingerprints with variant live features in a live biometric authenticity check gatekeeper system. Various forms of modern security often depended on the safety of objects, key words, numbers or actions. Although security and encryption had made enormous progress on protecting the safety of people and information, the weakest link was frequently the key itself. Physical security devices such as metallic keys and smart cards were not linked to the individuals they were issued to, and could be easily stolen, misplaced or duplicated. Password security depended on the strict diligence of numerous users of varying levels of dedication and loyalty. Benign users might accidentally leave written passwords in their workspaces, and malignant users might provide intruders with their passwords. In general, users were reluctant to change passwords, and sometimes would accidentally provide their passwords to intruders posing as security personnel. Existing biometric systems did not exhibit many of these shortcomings, but could be defeated in other ways. The fingerprint or hand reader could be cracked with synthetic fingerprints lifted and generated from objects touched by the authorized person. Sophisticated image captures or synthetic dummies could also eventually crack retinal scanners. Future DNA scanners could be fooled with stolen bodily fluids or tissue. Traditional voice input passwords, sometimes used on personal computers, were convenient, but a simple audio recorder was often all an attacker needed to gain access. Combining the FBI standard automatic fingerprints identification system (AFIS) with automatic face speaker recognition systems, we will further mix them for the transmission safety from the gatekeeper to the gatekeeper computer, in terms of the discrete wavelet sub-band coding. The biometric system provided an exceptional level of duplication and tamper-resistant security. The software of automatic target recognition (ATR) was mainly based on traditional Fisher classification methodology by means of nearest neighborhood classification logic. As a result, any input would have always had a nearest neighbor, thus a class label would be issued at every trial; but it might turn out to be intruder-winning false positive, or authorized users nuisance false negative. Thus, in principle, current ATR methods were based on ad hoc threshold of the separation distance that could not ward off an intruder 100%.