Abstract
It was recently proposed to use the human visual system’s ability to perform efficient photon counting in order to devise a new biometric authentication methodology. The relevant “fingerprint” is represented by the optical losses light suffers along different paths from the cornea to the retina. The “fingerprint” is accessed by interrogating a subject on perceiving or not weak light flashes, containing few tens of photons, thus probing the subject’s visual system at the threshold of perception, at which regime optical losses play a significant role. The name “quantum biometrics” derives from the fact that the photon statistics of the illuminating light, as well as the quantum efficiency at the light detection level of rod cells, are central to the method. Here we elaborate further on this methodology, addressing several aspects like aging effects of the method’s “fingerprint,” as well as its inter-subject variability. We then review recent progress towards the experimental realization of the method. Finally, we summarize a recent proposal to use quantum light sources, in particular a single photon source, in order to enhance the performance of the authentication process. This further corroborates the “quantum” character of the methodology and alludes to the emerging field of quantum vision.
Keywords
- quantum
- biometrics
- photon statistics
- quantum light
- visual perception
1. Introduction
It was recently proposed [1] to use the human visual system’s ability to perform photon counting in order to devise a new biometric authentication scheme, which was called “quantum.” The claim made in [1] was that the scheme offers unbreakable security, not unlike the security offered by quantum cryptography [2, 3] against a potential impostor wishing to eavesdrop during the transmission of information. In our case, the “fingerprint” is a physical property of the visual system, including the eyeball, retina and brain. The “fingerprint” is registered and probed using weak-intensity light and the subject’s conscious perception thereof.
In this chapter we will further elaborate in intuitive terms on the workings of the quantum biometric methodology as were outlined in [1]. To do so, we will summarize a recently proposed authentication algorithm [4], which is straightforward to understand, as compared to more elaborate algorithms discussed in [1]. We will then address some basic issues of the authentication methodology. One has to do with the very first registration of one’s “fingerprint.” Another issue is related to aging effects on this “fingerprint,” which have to do with the visual acuity degrading with age. We will also address the central issue of the variability of the “fingerprint” among different individuals.
We will then review recent progress made towards the experimental realization of the quantum biometric methodology using laser light [5]. Finally, we will summarize a recent proposal [4], to use quantum light in order to enhance the method’s performance in terms of the required time to run the authentication algorithm, for given desired values of the false-negative and false-positive authentication probability.
2. Preliminaries
As a short introduction to the basics of our biometric authentication methodology, we first recapitulate the original experiment of Hecht et al. [6], eloquently described by Bialek [7]. In particular, Hecht et al. were the first to unambiguously demonstrate that rod cells, the scotopic photoreceptors in our retina, are efficient photon detectors. Additionally, they obtained the threshold in the number of detected photons for the perception of vision to take place. We denote this threshold by
In more detail, the three authors in [6] exposed their eyes to very weak-intensity light pulses, with the photon number within each pulse being so small, that the visual perception became a probabilistic event. Let
However, when the mean number of photons per pulse incident on the eyeball is
Hence the probability that the number of photons detected by the illuminated patch of the retina is exactly
As noted by Bialek [7], this formula expresses the (perhaps surprising) fact that the probabilistic nature of our visual perception, which is a systemic effect concerning the retina and the brain, is fundamentally governed by the quantum statistical properties of the stimulus light.
To further understand the experiment of Hecht et al., we plot in Figure 1 examples of the dependence of the probability
What is interesting to note is that the change of
The experimental apparatus used by Hecht et al. looks rather primitive from our modern technological perspective. Yet these authors managed to make a remarkable case: even though a subjective observable, as the optical loss parameter
3. Quantum biometrics
Whereas the variability of the parameter
There are three ways to get several light paths to the retina. For all three we suppose that the stimulus light source consists of distinct laser beams, which can illuminate the cornea at several different spots (as shown in Figure 2a), either one at a time, or many. These laser beams are supposed to propagate in parallel from the light source to the cornea. Then, for an emmetropic individual (i.e., somebody not having any refractive errors) all these laser beams will be focused on the same spot on the retina. Instead, for a myopic individual these laser beams focus before the retina and thus will illuminate different spots on the retina, while for a hyperopic individual they focus behind the retina, and again illuminate different spots.
Now, as observed in Section 2, the
In Figure 2 we show the crux of the matter: suppose we have an array of, for example, nine laser beams, patterned in a
To describe the workings of the methodology in more detail, we first note that the prerequisite is that the
3.1 First registration of α -map
The
To avoid amplifying the error made in the estimation of
Let us denote by
This number of interrogations is clearly impractical. In [1] the first authentication algorithm proposed follows a similar route of estimating
This observation had motivated [1, 4] authentication algorithms that, rather than using the precise
3.2 Detailed description
When the subject wishes to be authenticated, for example, in order to enter a high-security facility, the biometric device must implement a measurement protocol in order to positively authenticate the subject. As already apparent, we have restricted the discussion to authentication. That is, we assume that when asking to be authenticated, the subject announces who he or she is. Then the device must make sure that the subject indeed is who he or she claims to be. So henceforth we suppose the biometric device is “aware” of the subject’s
The result of the authentication protocol is either positive or negative, and two central quantifiers of its performance are the false-negative and false-positive probability, denoted by
Let us call Alice the subject who appears and wishes to be positively authenticated. Eve will be an impostor who maliciously claims to be Alice. Now, the biometric device knows Alice’s high-
Now, we will suppose that Eve is not aware of Alice’s
However, what should be allowed as a scenario is for the impostor to have technology that would allow her to estimate the “fingerprint” under consideration by physical means, which do not require access to the fingerprint database nor do they require use of force. For example, one could imagine when discussing, for example, face recognition, that Eve could take an image of Alice’s face without Alice noticing (e.g., from a distance using a high resolution camera) and then use this image to construct a face mask. This scenario is not prevented by physical laws. Nor is there any physical law preventing the face recognition test from being bypassed by an artificial face mask. So in comparing the security of various biometric methodologies, one should study what is in principle possible in terms of bypassing the biometric device, given the laws of physics. Based on current quantum technology, it is inconceivable how Eve would be able to infer Alice’s
In other words, it seems that even in principle, that is, based on the laws of physics and in particular the physics of quantum measurements, Eve cannot physically obtain Alice’s
A crucial detail is that the device illuminates every spot, no matter of what kind it is, with a light pulse
We will now elucidate all of the above using the specific authentication protocol outlined in [4].
3.3 Authentication protocol
This protocol is a variant, which is intuitively simpler to understand than the protocols discussed in [1]. We assume that the biometric device simultaneously illuminates
Now the probability that an impostor called Eve, pretending to be Alice, correctly responds to such an interrogation is
because Eve is not aware of what kind of spots are being illuminated, and
where
Now, as previously mentioned, one interrogation is not enough to achieve adequate performance with respect to the false-positive and false-negative probabilities. Therefore a number of sequential interrogations is used. This number is actually a random variable, coming about as follows [4]. We define an integer success variable
For relatively small values of the parameter
3.4 Optimal photon number
The reader might have inquired how the photon number per pulse per illuminated pixel is chosen. This is easily shown by considering the fact that the probability of Alice’s successful response,
4. Aging effects
One question recurring in presentations of the above scheme is the effect of aging, namely, it is reasonable to assume that the
The subject fixates at the center of a half-sphere, the inner surface of which has a light background illumination (Figure 3a). Then, several spots are illuminated with varying intensity (on top of the background), and the subject reports whether he or she perceives the illuminated spot (Figure 3b), this leading to the threshold of perception. The position of each spot is defined with two angles, one accounting for the temporal vs. nasal position, and the other for the superior vs. inferior position (Figure 3c). The measured threshold as a function of these two angles defines the hill of vision (Figure 3d).
Now, as seen in Figure 4 depicting perimetric data [17], the visual field sensitivity indeed appears to degrade with age. We will use such data to comment on how age can affect the
5. Variability of the α -map
Another crucial issue is the variability of the
Figure 5a depicts the variability of the differential threshold of one particular individual for various viewing angles in the central
Finally, related to the inter-subject variability is the question of how many different subjects would our methodology be able to authenticate without the possibility of a random coincidence of one’s
6. Spatially selective laser light stimulus
The stimulus light source required to realize an authentication algorithm such as the one described above was recently reported in [5]. It consists of two laser beams, one at 532 nm and one at 850 nm, which are combined in a fiber into a single beam. As the laser power at the exit of the fiber combiner fluctuates, in [5] a feedback loop was used to stabilize the power of the 532 nm, which is used as stimulus light. The infrared light is used for pointing, as will be described shortly. In order to create different patterns of pixels across the laser beam’s cross section, the laser beam was propagated through a liquid crystal display (LCD) in a multi-pass configuration. The activated dots of the LCD produced an optical loss in the laser beam, corresponding to dark pixels, whereas the inactivated dots produced the illuminated pixels. In order for the contrast between illuminated versus dark pixels to be acceptable, the beam went through the same configuration of LCD dots five times, as shown in Figure 6a. The five passes where chosen because the relative optical loss obtained from one pass between activated and inactivated LCD dot is 0.35. Now, since we need photon numbers up to 200 photons per illuminated pixel per pulse in order to scan the probability-of-seeing curve, the number of photons going through the inactivated LCD dots should be negligible compared to 200. Since
In Figure 6d we show that indeed the photon statistics of the stimulus light at 532 nm are Poissonian. In particular, this is accomplished by the aforementioned intensity feedback, without which the photon number distribution is wider than the Poissonian. In Figure 6e we show that for photon numbers at least equal to 200 the variance of the photon number is equal to the mean photon number per pulse, hence our stimulus light exhibits Poissonian statistics for all photon numbers of interest for the biometrics protocol. It should also be noted that the control over the number of photons, that is, the ability to change the mean number of photons per illuminated pixel per pulse resides in the feedback system used to stabilize the stimulus light. By changing a voltage within the feedback system, we can scan the number of photons, for example, from 20 to 200 photons.
Finally, we discuss the role of the infrared light. The infrared light is used for pointing, that is, for providing information on the geometry of incidence of the stimulus light on the cornea. As can be seen in Figure 6a, the laser beam illuminates the eye through a beam splitter, so that the camera sitting behind the beam splitter can image the subject’s eye. Moreover, just before the eye we place a glass plate, so that the laser beam is reflected backwards into the camera, since the reflections off the spherical surface of the eye would miss the camera. However, the green stimulus light is too weak (maximum 200 photons per illuminated pixel per pulse) for its reflection to be detected by the camera. Here comes in the infrared light, which is not perceived by the visual system, thus its intensity can be high enough for its reflection to be visible in the camera. This is what is seen in Figure 6f–h, where we depict various examples of patterns of pixels incident on the eye. The large bright pixel on the top left part of each image is the reflection of an infrared lamp providing for ambient light for the camera. The other pixels are the infrared reflections of the illuminated pixels of the laser beam. Due to the spatial overlap of the stimulus and the infrared light, these infrared reflections convey the exact position of the stimulating pixels at 532 nm.
7. Quantum advantage with quantum light
One might wonder if there is some advantage to be gained by using quantum light sources for the stimulus light instead of laser light. Indeed, in [4] it was theoretically shown that a single-photon source, for example, a heralded single-photon source [18, 19, 20, 21] can lead to a quantum advantage. In particular, it was shown that the total interrogation time is reduced by using single photons. The advantage comes about because the narrower distribution of the incident photon number affects the probabilities
The fact that we can use a single-photon source producing a number of, for example, 200 photons in a light pulse stimulating the visual system rests on the rather large temporal summation window [22], which is the time span within which the visual system cannot temporally resolve the perceived light. Were that not the case, one would need Fock states with up to 200 photons, which so far cannot be produced. In contrast, a heralded-single photon source working at 1 kHz rate would do.
It is interesting to note that the quantum advantage obtained, that is, the required number of required interrogations, is reduced by slightly more than 10% compared to laser light. This figure is at first sight not significant, the main reason being that the statistics of the detected photons differ only slightly [4] between quantum light and laser light, because of the high optical losses suffered by light. It is actually these losses that we take advantage of to define the fingerprint of this method. Since these losses are rather large (typical values of
8. Conclusions
We have elaborated on a new biometric authentication method, which is based on the human visual system’s ability to perform photon counting. The method works with weak light, in order for the effect of visual perception to take place when the light intensity is close to the visual threshold. In such a regime, optical losses suffered by light when propagating from the cornea to the retina are crucial in determining the outcome of perception of weak light flashes. These losses form the biometric “fingerprint” of our biometric authentication methodology. We have described an intuitive authentication algorithm based on illuminating a number of retinal spots being associated with either high optical losses or low optical losses, and used this algorithm to discuss basic features of our methodology, like aging effects, and the fingerprint’s inter-subject and intra-subject variability.
We then reviewed recent experimental progress towards developing a laser light stimulus source which provides for light patterns with the desired properties needed for the realization of the authentication protocols. Finally, we presented recent work in exploring a possible quantum advantage that could be obtained by using a quantum light source instead, like a heralded single-photon source.
From a broader perspective, this work further demonstrates the scientific potential of the emerging field of quantum vision, that is, the possibilities for exploring the human and animal visual system using modern photonic and quantum-optical tools [23, 24, 25, 26, 27, 28].
Notes/thanks/other declarations
IK and ML acknowledge co-financing of this work by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call “RESEARCH-CREATE- INNOVATE,” with project title “Photonic analysis of the retina’s biometric photo-absorption” (project code: T1EDK-04921). OEM acknowledges financial support from the Scientific and Technological Research Council of Turkey (TÜBITAK), grant No. 120F200.
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