Methods and apparatuses for identifying transmission lines via impedance inhomogeneity patterns

Abstract

Methods and apparatuses for using the impedance inhomogeneity pattern (IIP) of a transmission line, or one or more segments thereof, to verify the identity of the transmission line and/or detect whether or not the transmission line has been altered or tampered with. Because the impedance inhomogeneity pattern of a transmission line is unique, unpredictable, and uncontrollable, it can be used as a physical unclonable function (PUF). The IIP can be obtained by a method such as frequency domain reflectometry or time domain reflectometry, and is then compared with a previously stored intrinsic IIP obtained from a transmission line (or segment(s)) prior to first use through the use of, for example, correlation or coherence functions. The method can be used on any transmission line, including electrical, optical and acoustic transmission lines. The method is useful for enabling or enhancing physical layer communication link security, transmission line sensing security, supply chain security, product authentication, physical encryption, anti-counterfeiting, manufacturing traceability, and the like.

Claims

1. A method for analyzing a transmission line, the method comprising: an analog wave generator transmitting a travelling wave through a connector into at least a segment of a transmission line; an analog receiver measuring backscattered wave reflections as a function of distance along a propagation direction of the segment of the transmission line; extracting an impedance inhomogeneity pattern (IIP) from the measured backscattered wave reflection; and comparing the IIP with an intrinsic IIP extracted from the segment of the transmission line prior to first use of the transmission line.

2. The method of claim 1 further comprising concluding that the transmission line has been altered or tampered with if the comparing step comprises determining the IIP is sufficiently different from the intrinsic IIP.

3. The method of claim 1 further comprising concluding that the transmission line has not been altered or tampered with and/or that the segment of the transmission line generated the intrinsic IIP if the comparing step comprises determining the IIP is sufficiently identical to the intrinsic IIP.

4. The method of claim 3 further comprising authenticating the transmission line and/or an article which the transmission line is integrated with, embedded in, or attached to.

5. The method of claim 1 repeated for a plurality of segments of the transmission line.

6. The method of claim 1 wherein the analog wave generator generates a pulse comprising a predetermined waveform, and the measuring step comprises directly measuring a back-reflection coefficient as a function of distance using time domain reflectometry.

7. The method of claim 6 wherein the predetermined waveform comprises a step function or an impulse function.

8. The method of claim 1 wherein the analog wave generator comprises a frequency modulated continuous wave source or a broadband wave source.

9. The method of claim 8 wherein a vector network analyzer comprises the analog wave generator and analog receiver.

10. The method of claim 8 comprising using a microwave interferometer to perform homodyne detection.

11. The method of claim 8 wherein the extracting step comprises performing an inverse Fourier transform of complex reflection coefficients obtained in the frequency domain over a bandwidth of the wave source in order to perform frequency domain reflectometry.

12. The method of claim 1 wherein the segment of the transmission line is selected by using time gating.

13. The method of claim 1 wherein the comparing step comprises performing a cross-correlation.

14. The method of claim 1 wherein an equal error rate obtained during the comparing step is less than approximately 0.1%.

15. The method of claim 1 wherein the equal error rate is less than approximately 20 ppm.

16. The method of claim 15 wherein the equal error rate is approximately zero.

17. The method of claim 1 wherein the comparing step comprises using a coherence function.

18. The method of claim 1 wherein a result of the comparing step is approximately independent of a temperature of the transmission line.

19. The method of claim 1 wherein a result of the comparing step is approximately independent of a termination quality of the transmission line.

20. The method of claim 1 wherein the transmission line is selected from the group consisting of two-wire line, twisted pair Ethernet cable, a high speed digital transmission cable, coaxial cable, parallel plate transmission line, microstrip line on a printed circuit board (PCB), stripline on a PCB, coplanar waveguides (CPW) on a PCB, metallic or dielectric waveguide, transmission line on a flexible printed circuit (FPC), flexible flat cable (FFC), on-chip transmission line inside an integrated circuit (IC), high frequency circuit vias, connector, optical fiber, optical waveguide, optical strip waveguide on a photonic integrated circuit (PIC), optical rib waveguide on a PIC, segmented optical waveguide, photonic crystal waveguide, plasmonic waveguide, laser-inscribed optical waveguide, light pipe, fiber-to-chip coupler, acoustic pipe, and combinations thereof.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The accompanying drawings, which are incorporated into and form a part of the specification, illustrate the practice of embodiments of the present invention and, together with the description, serve to explain the principles of the invention. The drawings are only for the purpose of illustrating certain embodiments of the invention and are not to be construed as limiting the invention. In the drawings:

(2) FIG. 1 is the exemplary plot of a random, unique and unclonable impedance inhomogeneity pattern as a function of distance in a transmission line.

(3) FIG. 2 is an exemplary system architecture using an impedance inhomogeneity pattern as ID to secure communication links.

(4) FIG. 3 is an exemplary system architecture using an impedance inhomogeneity pattern as ID to identify a complete system (host of the transmission line).

(5) FIG. 4 is an exemplary system architecture using an impedance inhomogeneity pattern as ID to identify an object having an embedded transmission line.

(6) FIG. 5 is an exemplary system architecture using an impedance inhomogeneity pattern as ID and a sensing element simultaneously to secure such sensors and sensing systems.

(7) FIG. 6 is an exemplary system architecture of a time domain reflectometry (TDR) based ID scanner to extract impedance inhomogeneity pattern for ID applications.

(8) FIG. 7 is an exemplary system architecture of a frequency domain reflectometry (FDR) based ID scanner to extract impedance inhomogeneity patterns for ID applications. The dotted arrow pointing from the broadband wave transmitter to wave receiver represents a local oscillator path, indicating the homodyne/interferometry-type of measurement configuration, which is optional in an FDR based ID scanner.

(9) FIG. 8 is an exemplary system architecture of ID storage methods, including cloud storage, local storage, and hybrid cloud-local storage.

(10) FIG. 9 is an exemplary system architecture of an integrated ID scanner in a communication system with shared modules.

(11) FIG. 10 is an exemplary system architecture of an integrated ID scanner in a transmission line sensing system with shared modules.

(12) FIG. 11A is a plot of exemplary impedance inhomogeneity patterns of two different equal length (ID1 and ID2) transmission line sections.

(13) FIG. 11B is a plot of exemplary impedance inhomogeneity patterns of the same transmission line section, extracted at different time points (ID 1 and ID 1 at a different time).

(14) FIG. 11C is an exemplary plot of the cross-correlation results between ID 1 and ID 1 at a different time, and the cross-correlation results between ID 1 and ID 2.

(15) FIG. 12 is an exemplary plot showing the use of transmission line identification technology for simultaneous identification and tamper and/or snooping detection.

(16) FIG. 13 shows reflection coefficient magnitude as a function of time from a 2 m-long coaxial cable.

(17) FIG. 14 is an example of TX-Line PUF in database.

(18) FIG. 15 shows an example of genuine cross-correlation.

(19) FIG. 16 shows an example of impostor cross-correlation.

(20) FIG. 17 shows genuine and impostor distributions for a 10 cm TX-Line PUF.

(21) FIG. 18A shows genuine and impostor distributions for a 5 cm PUF length.

(22) FIG. 18B shows genuine and impostor distributions for a 2 cm PUF lengths.

(23) FIG. 19A shows genuine and impostor distributions for a 20 cm TX-Line PUF with a 20 GHz bandwidth.

(24) FIG. 19B shows genuine and impostor distributions for a 20 cm TX-Line PUF with a 5 GHz bandwidth.

(25) FIG. 19C shows genuine and impostor distributions for a 20 cm TX-Line PUF with a 1.25 GHz bandwidth.

(26) FIG. 20 shows correlation peak as a function of temperature.

(27) FIG. 21A shows genuine and impostor distributions within the first half of a 2 m cable of a TX-Line (5 cm TX-Line PUF).

(28) FIG. 21B shows genuine and impostor distributions within the second half of the 2 m cable.

(29) FIG. 22A shows coherence examples for the coherence function of a 10 cm TX-Line PUF.

(30) FIG. 22B shows genuine and impostor distributions of a 10 cm TX-Line PUF.

(31) FIG. 23A shows genuine and impostor distributions with short termination (10 cm TX-Line PUF).

(32) FIG. 23B shows genuine and impostor distributions with open termination (10 cm TX-Line PUF).

(33) FIG. 24 shows genuine and impostor distributions using the homodyne detection method (1 cm TX-Line PUF).

(34) FIG. 25 shows genuine and impostor distributions of twisted pair TX-Line PUFs (10 cm TX-Line PUF).

(35) FIG. 26A shows the intrinsic impedance inhomogeneity pattern from a backscattered TDR signal (10 cm TX-Line PUF).

(36) FIG. 26B shows genuine and impostor distributions obtained using the TDR of FIG. 26A.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

(37) The intrinsic impedance inhomogeneity pattern of a transmission line upon manufacture is unique, unpredictable, uncontrollable, unclonable, and fingerprint-like, which can be considered a physical unclonable function (PUF). After manufacture a transmission line can be intentionally modified artificially, or modified as a result of environmental effects, via various physical and chemical processes, such as by modulating the material chemically, for example via etching, modulating the material thermally, for example using a soldering iron or laser, or by mechanically modulating the transmission line, for example by creating a kink in the transmission line by bending or twisting it at one or more locations. Such modifications will typically change the impedance inhomogeneity pattern of the transmission line. The intrinsic impedance inhomogeneity pattern can thus be used as a PUF to identify TX-Lines or discrete sections of TX-Line for identification (ID) and other identification-based applications. Embodiments of the present invention comprise various methods of using impedance inhomogeneity patterns of a transmission line as a physical unclonable function (PUF) for purposes of ID of the transmission line, or objects that include such a transmission line, the entire transmission line or transmission path, or a section of the transmission line, as well as other identification-based applications. Examples include enabling or enhancing physical layer (PHY) communication link security, TX-Line-based sensing security, supply chain security, anti-counterfeiting, manufacturing traceability, etc.

(38) The impedance inhomogeneity pattern can be extracted through the measurement of backscattered reflection waves along the propagation direction of the TX-Line, also known as the reflection coefficient as a function of propagation distance. The reflection coefficient as a function of time/distance can be measured via time domain reflectometry (TDR) technology. TDR equipment includes a pulse generator to send pulse(s) from a connector into an electrical TX-Line, a receiver to collect the back-reflections from the same connector, and a controller/synchronization module. This apparatus directly measures the back-reflection coefficient as a function of distance, i.e. the variation of impedance as a function of time or impedance inhomogeneity pattern (IIP). Alternatively, it can be measured in the frequency domain first and then converted to time/distance domain. The latter approach is known as frequency domain reflectometry (FDR). FDR instrumentation includes a vector network analyzer which contains a frequency modulated continuous wave (FMCW) source, which is able to measure complex reflection coefficients at different frequency points (S11) over a bandwidth, which is thus used to measure S11 corresponding to a specific electrical TX-Line, and a RF/microwave interferometer. The inverse Fourier transform of S11 provides the IIP. In either case, these devices are analog, and the system for extracting the impedance inhomogeneity pattern from various types of transmission lines via either frequency domain measurement or time/distance domain measurement is referred to as an ID scanner.

(39) Once the impedance inhomogeneity pattern is measured, time gating functions can be used to divide the impedance inhomogeneity pattern of a long TX-Line into smaller sections, thereby isolating the impedance inhomogeneity pattern of each section. An advantage of isolating the impedance inhomogeneity pattern is that the PUF information of the target section can be well preserved, and not affected by the impedance inhomogeneity patterns of other parts of the TX-Line or the impedance mismatch at either transmitter end or receiver end. The extracted impedance inhomogeneity pattern from each isolated TX-Line section can be compared and identified via waveform correlation in either the time/distance domain or the frequency domain.

(40) One can identify the target transmission line or a section of the transmission line by evaluating the correlation or coherence between a currently measured inhomogeneity pattern and a previously stored one (see for example FIG. 11B).

(41) Referring now to the drawings, FIG. 1 illustrates a plot of a randomly distributed, unique, and unclonable impedance inhomogeneity pattern as function of distance in a transmission line. The impedance of a transmission line is determined by the material properties and geometry along the propagation direction of the transmission line.

(42) The impedance patterns of transmission lines can be used to identify communication links to provide a physical layer of protection for communication security. FIG. 2 is an exemplary system architecture using an impedance inhomogeneity pattern as identification (ID) to secure a communication link. As illustrated in FIG. 2, an ID scanner is deployed next to a communication system to collect backscattered waves to extract the ID from the secured transmission line. A base pattern is obtained at the time of installation of the TX-Line and stored for later comparison in a connected database. Any change of the TX-Line from its original state will be detected. The communication system is preferably configured such that it will only send information when the physical layer, i.e. the TX-Line, is secured. For example, a microwave transmission link between two microwave transceivers via the use of a microwave TX-Line can be secured using this method.

(43) The impedance pattern of a transmission line can also be used to identify the host of the transmission line for applications including supply chain security, anti-counterfeiting, etc. This type of system is on a smaller physical scale, but the underlying principal is the same. FIG. 3 is an exemplary system architecture using an impedance inhomogeneity pattern as ID to identify a complete system, including other modules and components comprising the complete system. For example, a PCB is the host of a microstrip transmission line, and the impedance inhomogeneity pattern of the microstrip transmission line can be used to identify that particular PCB for supply chain security and anti-counterfeiting applications. The microstrip thus provides that particular printed circuit board (PCB) with a unique identifiable fingerprint for future identification. Another example is that of an optical waveguide on a silicon photonic transceiver PIC chip, which can be used to identify the transceiver.

(44) FIG. 4 is an exemplary system architecture using an impedance inhomogeneity pattern as an ID to identify a discrete object (non-electronic) with an embedded transmission line. For example, a transmission line on a flexible printed circuit (FPC) can be integrated with or embedded in a medicine bottle as an ID tag for individual identification and anti-counterfeiting (similar to RFID tagging). FIG. 5 is an exemplary system architecture using an impedance inhomogeneity pattern as an ID and a sensing element simultaneously to secure sensing data and a sensing system.

(45) The impedance inhomogeneity pattern can be extracted through the measurement of backscattered reflection waves along the propagation direction of the transmission line, also known as the reflection coefficient as a function of propagation distance. FIG. 6 is an exemplary system architecture using time domain reflectometry (TDR) in an ID scanner to extract the impedance inhomogeneity pattern in a transmission line. In this ID scanner, the wave transmitter launches incident waves with a predetermined waveform, such as an impulse function or a step function, into the transmission line. The backscattered wave is collected for the ID scanner to extract the impedance inhomogeneity pattern. A processing unit is required to process the data and compare the newly measured ID information with previous stored ones.

(46) Alternatively, the impedance inhomogeneity pattern can be measured via a frequency domain reflectometry (FDR)-based ID scanner. A wave transmitter launches continuous wave (CW) travelling waves, using either a broadband source (e.g., noise source or digital clock generator for electrical transmission ID) or frequency/wavelength-swept source (e.g. voltage controlled oscillator or RF synthesizer for an electrical transmission line), into the transmission line. The backscattered wave is collected and processed to extract the impedance inhomogeneity pattern of the transmission line under test. It is worth noting that a local oscillator (LO), which is a signal path that taps a fraction of the launched wave into the receiver to be mixed with the backscattered wave, can be added into this configuration to provide homodyne/interferometry-based frequency domain measurement capability. In addition, in-phase (I) and quadrature (Q) receivers can be used to provide complex signal measurement with better signal-to-noise ratio (SNR). However, a single channel (i.e., either I or Q channel) can also be used.

(47) FIG. 8 is an exemplary system architecture of ID storage of previously measured patterns. During a registration process, ID patterns are measured and can be stored in a secured database in the cloud, stored on a local memory, or stored in a hybrid fashion.

(48) FIG. 9 is an exemplary system architecture of an integrated ID scanner in a communication system. FIG. 10 is an exemplary system architecture of an integrated ID scanner in a transmission line-based sensing system. In these combined systems, all common components, such as the transmitter and receiver, can be shared, leading to a reduced system cost. Although the ID scanner equipment can be integrated in other systems, it can also be a standalone instrument.

(49) The impedance inhomogeneity pattern can be used for identification by evaluating the correlation or coherence between the newly measured ID and the previously stored one in either the time/distance domain or the frequency domain. FIGS. 11A-110 are the exemplary plots of the signal processing of the transmission line ID technology of the present invention. FIG. 11A is a plot of exemplary impedance inhomogeneity patterns of two different but equal length (ID 1 and ID 2) transmission line sections. The difference between the inhomogeneity impedance patterns is clearly seen. FIG. 11B is a plot of exemplary impedance inhomogeneity patterns of the same transmission line section, extracted at different time points (ID 1 and ID 1 at a different time). The pattern is the same, thus providing the ability to identify the transmission line or to confirm that the transmission line has not been physically tampered with. FIG. 11C is a plot of exemplary cross-correlation results between ID 1 and ID 1 at a different time, and the cross-correlation results between ID 1 and ID 2. FIGS. 11A-110 clearly show that the correlation functions can be used to compare the two IDs for this instant invention. It is worth noting that the impedance inhomogeneity pattern in its frequency domain can also be used. Additionally, it is worth noting that the coherence function can also be used.

(50) While a piece or the entire length of transmission line can be used for the ID application, the impedance inhomogeneity pattern in a transmission line can be segmented into smaller transmission line sections as a function of distance. Both the unique inhomogeneity pattern and the location information of each transmission line section can be used for identification. Using the impedance inhomogeneity pattern from multiple transmission lines in a system can be used to provide enhanced system-level security.

(51) In FIG. 12 it can be seen that an external force applied to the transmission line leads to a change of its inhomogeneity pattern, resulting in a weakened or phase shifted coherence spectrum, which can be used for simultaneous identification and tamper and/or snooping detection. FIG. 12 is an exemplary plot showing the use of transmission line ID technology for simultaneous identification and tamper and/or snooping detection.

EXAMPLE

(52) A vector network analyzer (VNA) was employed to measure the impedance inhomogeneity pattern of a coaxial cable with a length of 2 m. The bandwidth of the VNA was set from 300 kHz to 20 GHz with a total number of sampling points of 501. The cable under test was terminated using a 50 ohm cap. An inverse Fourier Transform function was applied to the frequency domain reflection coefficient data to achieve the time domain reflection coefficient data. The reflection coefficient magnitude as a function of time of the entire cable was plotted in FIG. 13. As shown in FIG. 13, the termination of the cable resulted in a small reflection at the end of the cable, which occurred at about 19.5 ns in FIG. 13. Given that the velocity of the travelling wave in the cable is about two thirds of the speed of light in vacuum, the measured data matches the expectation.

(53) Ten 10 cm sections were selected from the 2 m long coaxial cable. The normalized impedance inhomogeneity pattern of each section is used as a PUF. Let X.sup.(P) represent the PUF being extracted from the object to be identified, and X.sup.(D) represent the PUF from the database, where

(54) $\begin{array}{cc}\{\begin{array}{c}{X}^{\left(D\right)}={\left(X^{\left(D\right)}\left[0\right]X^{\left(D\right)}\left[1\right]\mathrm{.Math.}{X}^{\left(D\right)}\left[N-1\right]\right)}^T\\ X^{\left(P\right)}={\left(X^{\left(P\right)}\left[0\right]X^{\left(P\right)}\left[1\right]\mathrm{.Math.}{X}^{\left(P\right)}\left[N-1\right]\right)}^T\end{array}& \left(1\right)\end{array}$
Note that the length of a PUF (N) depends on the length of the TX-Line used by the system. For a specific system, the length is fixed; thus, N, the length of data in each section, is a constant. The length of each section in this example is 10 cm, corresponding to an N of 40 for each section. Cross-correlation was employed to assess the similarity of two PUFs in the proof-of-concept experiment, which can be expressed as:

(55) $\begin{array}{cc}\left(X^{\left(P\right)}*X^{\left(D\right)}\right)\left[m\right]=\underset{k=0}{\overset{N-1}{.Math.}}{X}^{*\left(P\right)}\left[k\right]*X^{\left(D\right)}\left[k+m\right]& \left(2\right)\end{array}$
where m=−N+1, −N+2, . . . N−2, N−1. The similarity, denoted by S, is defined to be the peak value of cross-correlation:
S=max.sub.m(X.sup.(P)*X.sup.(D))[m]  (3)
FIG. 14 shows a typical PUF from the database. A genuine cross-correlation and an impostor cross-correlation are shown in FIG. 15 and FIG. 16, respectively. In the process of verification, only one match is preferred, determined by a hypothesis test:

(56) $\begin{array}{cc}\{\begin{array}{c}{H}_0:X^{\left(P\right)}\mathrm{and}{X}^{\left(D\right)}\mathrm{are}\mathrm{from}\mathrm{different}\mathrm{PUFs}\\ H_1:X^{\left(P\right)}\mathrm{and}{X}^{\left(D\right)}\mathrm{are}\mathrm{from}\mathrm{the}\mathrm{same}\mathrm{PUFs}\end{array}& \left(4\right)\end{array}$
where H.sub.0 outputs “No”, and H.sub.1 outputs “Yes”.

(57) To quantify the verification accuracy, the 10 independent PUFs (10 cm each) selected from the 2 m-long coaxial cable were studied. The PUF was extracted 5,000 times from each cable section. In total, 50,000 PUFs were collected. In order to study the genuine distribution P(S|H.sub.1), one PUF was randomly selected out of the 5,000 extractions from each independent cable section, and stored as the database PUF. In total, 4999×10 genuine-matching scores were collected. For the distribution P(S|H.sub.0), the same database PUFs were used. For each section, 4,999 PUFs from the other 9 cable sections (TX-Line PUFs) were randomly selected for comparison against the corresponding database PUF. As a result, 4999×9 impostor matching scores were collected.

(58) FIG. 17 shows both the genuine and impostor distributions. The x-axis is the similarity evaluation, which is the peak value (S) of the cross-correlation and the y-axis is the probability. Discrimination is sufficiently clear for high-performance verification. The equal error rate (EER), which is the error rate when the threshold is set to the False Alarm Rate equal to one minus Detection Rate, was used as the metric to evaluate the performance of this 10 cm coaxial cable PUF. EER is 0 out of all the samples (50,000 samples) collected. In other words, the EER of this experiment was smaller than 20 ppm.

(59) Performance Evaluation with Different Lengths

(60) Cable PUFs with lengths of 5 cm and 2 cm were studied. At each length, 5,000 impedance inhomogeneity patterns were extracted from 20 samples. The results are shown in FIGS. 18A-B. No false alarm was detected on the 5 cm TX-Line PUF verification, shown in FIG. 18A, indicating that the EER of the 5 cm TX-Line PUF is still below 20 ppm. When shrinking the PUF length to 2 cm, genuine and impostor distribution starts to overlap, shown in FIG. 18B. The EER was calculated to be about 0.1%.

(61) Performance Evaluation With Different Bandwidths

(62) Cables with lengths of 20 cm were measured using different bandwidths of 20 GHz, 5 GHz, and 1.25 GHz, respectively. 5000 impedance inhomogeneity patterns were extracted from all 10 samples. The results are shown in FIGS. 19A-19C respectively. No false alarm was detected for all the measurements. However, as the bandwidth decreases, the genuine and impostor distributions move closer, indicating a decreased PUF verification performance.

(63) Performance Evaluation at Different Temperatures

(64) The intrinsic impedance inhomogeneity pattern is a fundamental property of a TX-Line. Under the influence of temperature change, the impedance inhomogeneity pattern can change. The external temperature change mainly imposes a phase shift to the pattern. In order to evaluate the influence of temperature change on PUF, the cable used in FIG. 17 was deployed in an oven. A PUF of 10 cm was taken and stored at room temperature, then PUF information from the same sample was extracted and evaluated at temperatures up to 78° C. The correlation peak value as a function of temperature is plotted in FIG. 20. It clearly shows that the correlation of the intrinsic impedance inhomogeneity pattern is not significantly affected by the temperature change.

(65) Performance Evaluation at Different Locations Along the TX-Line

(66) Any TX-Line can be considered as a low pass filter. It strips off higher frequency components as the wave propagates along the line. Since the verification performance is frequency dependent, as shown in FIG. 19, the PUF performance is expected to drop as it moves away from the source of the signal generator. In this experiment, the 2 m cable used in previous tests was virtually divided into two 1 m cables. Within each half of the cable, 10 samples with an equivalent length of 5 cm each were selected. Each sample was measured 5,000 times at a bandwidth of 20 GHz. FIGS. 21A and 21B compare the results within the first and the second half of the cable, respectively. It clearly shows that the PUF performance is better within the first half of the cable.

(67) Using the Coherence Function to Compare TX-Line PUFs

(68) Coherence is another well-known technique to compare the similarity of two waveforms. The coherence function assesses “similarity” by looking at the similarity for two variables in frequency space, rather than time/distance space. The magnitude-squared coherence as a function of normalized frequency for a genuine PUF pair and an impostor PUF pair are shown in FIG. 22A. The summation of the coherence spectrum was used as the score to evaluate the similarity of PUF pairs. Using the data from FIG. 17, the distribution of genuine and impostor score was plotted in FIG. 22B. Similar PUF performance was achieved using the coherence function method.

(69) Termination Influence on the PUF Performance

(70) Poorly terminated transmission line results in strong reflection at the termination. In order to show the influence of poor terminations, the experiment shown in FIG. 17 was repeated with a short load and an open load. The results are shown in FIG. 23. The poor terminations have almost no influence on the TX-Line PUF performance.

(71) Extracting PUF Using a Homodyne Detection Instrument

(72) The intrinsic impedance inhomogeneity pattern can be extracted using a microwave interferometer in a process known as homodyne detection. This approach is widely used in all frequency-modulated continuous-wave (FMCW) radar devices. In this experiment, only the in-phase (I) signal was used for impedance inhomogeneity pattern extraction. The bandwidth of the homodyne detection circuit was 8 to 18 GHz, mainly limited by the bandwidth of the circulator used in this design. The same 2 m-long coaxial cable was used to demonstrate the method's feasibility. As shown in FIG. 24, the homodyne method is equally as good as using a VNA, indicating that FDR-based TX-Line PUF technology can be implemented at a lower cost.

(73) Two Wire TX-Lines

(74) In order to demonstrate the feasibility of another type of TX-Line, a twisted pair cable was studied. The TX-Line under test was a different pair in a shielded twisted pair (STP) category 7 (CAT7) Ethernet cable. To compare an Ethernet cable PUF with the coaxial cable PUF, the length of the Ethernet cable under test was 2 m. 10 TX-Line PUFs with a length of 10 cm were extracted for 5,000 times, the same as the coaxial cable experiment shown in FIG. 17. The genuine and impostor distributions are shown in FIG. 25. The twisted pair TX-Line PUF performance was similar to that of a coaxial cable. Because two wire TX-Lines are widely used in high-speed digital communication cables, such as HDMI cables, USB cables, PCIe cables, etc., this technology could be potentially adopted for many identification-enabled physical layer (PHY) communication security applications.

(75) Time Domain Measurement Approach

(76) To demonstrate the feasibility of the TDR-based method to extract an intrinsic impedance inhomogeneity pattern a 2 m-long coaxial cable was studied using a standard TDR instrument based on the classic equivalent time sampling (ETS) method. The ETS sampling rate was 50 GSPS. The backscattered signal, or reflection coefficient against time/distance, was extracted, which is a direct way to measure its intrinsic impedance inhomogeneity pattern, is shown in FIG. 26A. 10 TX-Line PUFs with a length of 10 cm were extracted for 5,000 times, which matches the experiment shown in FIG. 17 for comparison. The genuine and impostor distributions are shown in FIG. 26B. This experiment indicates that the TX-Line PUF performance using the TDR-based method was not as good as the FDR-based method. However, no false alarm was detected over all the comparisons, meaning that the EER is still below 20 ppm, suggesting that the TDR-based method can be used for TX-Line PUF extraction.

(77) To summarize, using a new PUF consisting of the intrinsic impedance inhomogeneity pattern, i.e. the variation of characteristic impedance over distance, of any TX-Line, one can identify the TX-Line with high verification accuracy. The TX-Line PUF information can be extracted using either frequency domain reflectometry (FDR) or time domain reflectometry (TDR) methods. A coaxial cable as short as 2 cm was identified with an equivalent error rate (EER) of below 20 ppm or 0.1%. This can be widely used for identification (ID) and other identification-based applications, such as enabling or enhancing physical layer (PHY) communication link security, TX-Line-based sensing security, supply chain security (e.g., circuit boards and electronic systems), anti-counterfeiting, and manufacturing traceability.

(78) Note that in the specification and claims, “about” or “approximately” means within twenty percent (20%) of the numerical amount cited. As used herein, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a functional group” refers to one or more functional groups, and reference to “the method” includes reference to equivalent steps and methods that would be understood and appreciated by those skilled in the art, and so forth.

(79) Although the invention has been described in detail with particular reference to the disclosed embodiments, other embodiments can achieve the same results. Variations and modifications of the present invention will be obvious to those skilled in the art and it is intended to cover all such modifications and equivalents. The entire disclosures of all patents and publications cited above are hereby incorporated by reference.