CN111695658A

CN111695658A - Anti-counterfeiting method based on PUF, PUF anti-counterfeiting label and preparation method thereof

Info

Publication number: CN111695658A
Application number: CN201910183237.0A
Authority: CN
Inventors: 叶坚; 顾雨清; 何畅; 董欣悦
Original assignee: Shanghai Jiaotong University
Current assignee: Shanghai Jiaotong University
Priority date: 2019-03-12
Filing date: 2019-03-12
Publication date: 2020-09-22
Anticipated expiration: 2039-03-12
Also published as: CN111695658B

Abstract

The invention discloses an anti-counterfeiting method based on Physical Unclonable Features (PUFs). the method provides a pattern formed by random distribution of surface enhanced Raman nanoparticles, acquires data in the pattern, and performs digital processing to form anti-counterfeiting coding information. The invention also discloses a PUF anti-counterfeiting label which comprises an anti-counterfeiting layer, wherein the anti-counterfeiting layer is a pattern formed by the randomly distributed surface enhanced Raman nanoparticles. The anti-counterfeiting method based on the PUF and the PUF anti-counterfeiting label have the advantages of strong imaging signal, high sensitivity, huge coding capacity, short reading time, low cost and the like.

Description

Anti-counterfeiting method based on PUF, PUF anti-counterfeiting label and preparation method thereof

Technical Field

The invention relates to the field of anti-counterfeiting, in particular to an anti-counterfeiting method based on PUF, a PUF anti-counterfeiting label and a preparation method thereof.

Background

In recent years, various fake and shoddy products exist in the market from the clothing industry, the cosmetic industry, the pharmaceutical industry, the food industry to the daily necessities industry, and the like, not only the image of an enterprise is damaged, but also the health and the safety of consumers are threatened. In order to solve the current situation of prevalence of counterfeit and shoddy products, the research of anti-counterfeiting technology is imperative.

The anti-counterfeiting technology widely applied to the market at present is a wireless anti-counterfeiting technology, and a user can be identified by mobile phone scanning through an anti-counterfeiting label with a mobile phone automatic identification arranged on a product. However, such tags are replication-clonable and are highly available to illicit molecules. Other common anti-counterfeiting methods including watermarks, holographic images, security inks, etc. are manufactured by a definite production process and can be imitated, and the security of the methods depends on the limitations of the manufacturing technology and the production materials.

The existing optical anti-counterfeiting label mainly depends on scattering and fluorescence, wherein the former is used for identifying a scattered light signal of the label, and the latter is used for identifying a fluorescence signal of the label. The anti-counterfeit label based on scattering is relatively simple to read, stable in signal, low in encoding capacity and highly dependent on the incident angle of laser; the anti-counterfeiting label based on fluorescence has strong signal, but is easy to generate fluorescence bleaching, and has poor light stability, and the further improvement of the coding capacity is limited by the color cross phenomenon of the fluorescence.

Therefore, an anti-counterfeiting method and an anti-counterfeiting label which are not reproducible need to be designed to meet the anti-counterfeiting requirement.

Disclosure of Invention

In view of the above defects in the prior art, the technical problem to be solved by the present invention is to provide a PUF-based anti-counterfeiting method, a PUF anti-counterfeiting label and a manufacturing method thereof, so as to meet the anti-counterfeiting requirement.

In order to achieve the above object, a first aspect of the present invention provides a PUF-based anti-counterfeiting method, which in one embodiment provides a pattern formed by random distribution of surface-enhanced raman nanoparticles, acquires data in the pattern, and digitizes the data to form anti-counterfeiting code information.

Further, the data are pixel point position information, type information of the surface enhanced raman nanoparticles and raman signal information.

Further, the raman signal information is presence or absence and/or intensity information of the raman signal.

Further, when a surface enhanced raman nanoparticle is used, intensity information is obtained by an appropriate raman peak in a raman spectrum; when two or more surface enhanced raman nanoparticles are used, the raman spectrum of each surface enhanced raman nanoparticle is separated, and an appropriate raman peak in the separated raman spectrum is selected to obtain intensity information. .

Further, the surface enhanced raman nanoparticles are composed of a metal nanomatrix and a characteristic raman molecule.

Optionally, the metal nano-substrate structure is selected from one, two or more of a nano-core-shell particle structure, a nano-dendrite, a nano-star, a nano-sphere, a nano-triangular plate, a nano-rod and a nano-particle dimer; the characteristic Raman molecule is one, two or more selected from p-dimercaptobenzene (1,4-BDT), p-nitrobenzenethiol (4-NBT), o-nitrobenzenethiol (2-NBT), 4-toluenethiol (4-MBT), 2-mercapto-5-nitrobenzimidazole (2-M-5-NBI), 2-mercapto-6-nitrobenzothiazole (2-M-6-NBT), o-chlorobenzenethiol (2-CBT), 4-chlorobenzenethiol (4-CBT), biphenyl-4, 4 '-dithiol (4,4' -BPDT) and 2-naphthalene thiol (2-NT).

In an alternative embodiment, the digitizing process comprises data preprocessing and digitizing the data acquired from the pattern.

Further, the data preprocessing is to filter out partial noise of the raman signal information and remove background signals. Optionally, a loss function fitting of a fourth order polynomial is used to remove the background signal.

In another alternative embodiment, when two or more types of surface enhanced raman nanoparticles are used, the digitization process comprises data preprocessing, component separation and digitization of the data acquired from the pattern.

Further, the components are separated into raman spectra that separate different types of surface enhanced raman nanoparticles.

Optionally, when the pattern is arranged on the substrate layer; and during component separation, after a Raman signal intensity value is obtained, the Raman spectrum and the quadratic term of the base material are added to fit a background signal which cannot be completely removed during data pretreatment.

Further, the digitization is to normalize and segment the raman signal intensity value of the surface enhanced raman nanoparticles to form a relative raman signal intensity; and combining the position information of each pixel point, the type information of the surface enhanced Raman nano particles and the relative Raman signal intensity to form anti-counterfeiting coding information.

Optionally, the digitizing comprises the steps of:

a. normalizing the Raman signal intensity value of each surface-enhanced Raman nanoparticle, and quantifying the Raman signal intensity value of each pixel point;

b. combining the position information of each pixel point, the surface enhanced Raman nanoparticle type information and the relative Raman signal intensity obtained after the segmentation by adopting a coarse graining method to form anti-counterfeiting coding information;

c. a repeatability test experiment was performed to get a more accurate labeling result and was transferred to the database.

Optionally, the pattern is detected by a raman spectrometer to obtain data in the pattern.

Optionally, the detection imaging mode is sample stage movement, laser movement or both movement.

Further, the anti-counterfeiting method based on the PUF further comprises verification that the pattern is detected by adopting a Raman device and compared with data in the database.

A second aspect of the invention provides the use of a PUF-based anti-counterfeiting method as described above in the field of security. Such as anti-counterfeiting of food, medicine, cosmetics, daily necessities, documents, currency and the like.

In a third aspect of the invention, a PUF security tag is provided, which in one embodiment includes an anti-counterfeiting layer, which is a pattern formed by randomly distributed surface-enhanced raman nanoparticles.

Further, the anti-counterfeiting layer is set to provide pixel point position information, surface enhanced Raman nanoparticle type information and Raman signal information.

Further, the raman signal information is the presence or absence of a raman signal and/or signal intensity.

Optionally, the metal nanomatrix structure is selected from one, two or more of a nanoparticle core shell particle structure, a nanotendre, a nanostar, a nanosphere, a nanotaper, a nanorod, and a nanoparticle dimer.

Two or more surface enhanced raman nanoparticles refer to surface enhanced raman nanoparticles having independently distinguishable raman signatures.

Optionally, a gap is formed between the core and shell of the core-shell nanoparticle structure, and the characteristic raman molecule is located in the gap.

Optionally, a gap is formed between the nano core and the shell of the nano core-shell particle structure; the shell layer is provided with a first layer and a second layer, and the second layer is provided with a gap; the characteristic raman molecule is located in the gap.

Alternatively, the characterizing raman molecule is selected from one, two or more of p-dimercaptobenzene (1,4-BDT), p-nitronitrobenzenethiol (4-NBT), o-nitrothiophenol (2-NBT), 4-tolylthiophenol (4-MBT), 2-mercapto-5-nitrobenzimidazole (2-M-5-NBI), 2-mercapto-6-nitrobenzothiazole (2-M-6-NBT), o-chlorothiophenol (2-CBT), 4-chlorothiophenol (4-CBT), biphenyl-4, 4 '-dithiol (4,4' -dt bp) and 2-napthalenethiol (2-NT).

Optionally, the surface enhanced raman particles are one, two or more species.

Further, the PUF anti-counterfeiting label also comprises a substrate layer and a protective layer; the anti-counterfeiting layer is positioned on the base material layer, and the protective layer is positioned on the anti-counterfeiting layer.

Optionally, the substrate layer is made of paper, silicon wafer, glass, metal or polymer; the protective layer is made of silicon chip, plastic film or macromolecule; optionally, the polymer is PVC.

In a specific embodiment, the PUF anti-counterfeit label comprises a substrate layer, an anti-counterfeit layer and a protective layer, wherein the anti-counterfeit layer is a pattern formed by randomly distributed surface enhanced raman nanoparticles, the anti-counterfeit layer is positioned on the substrate layer, and the protective layer is positioned on the anti-counterfeit layer;

the preparation method comprises the following steps: dropping the sol of the surface-enhanced Raman nanoparticles onto the protective layer, covering the substrate layer on the sol, and forming an anti-counterfeiting layer by the sol; or dropping the sol of the surface enhanced Raman nano-particles on the substrate layer, and covering the protective layer on the sol to form the anti-counterfeiting layer.

The invention has the following beneficial effects:

1) the surface enhanced Raman particles are used, so that the imaging signal is strong, the sensitivity is high, and the repeatability is high. Especially, when the surface enhanced Raman particles with the core-shell structure with gaps are adopted, the particles have good light stability, are not easy to generate photobleaching and have good repeatability. And therefore, a clear and stable Raman imaging image can be obtained.

2) The Raman signal intensity information of the surface enhanced Raman particles can be utilized to form a three-dimensional coding mode, even if only one surface enhanced Raman particle is used, the three-dimensional coding mode can also have responses without various signal intensities, and the coding capacity can be greatly improved; the coding capacity can be further improved when a variety of surface enhanced raman particles are used. The improvement of the coding capacity realizes the possibility of preparing the PUF label or the anti-counterfeiting method based on the PUF, so that the formed anti-counterfeiting label is difficult to copy, and the anti-counterfeiting reliability is improved.

3) The PUF-based anti-counterfeiting method or the PUF anti-counterfeiting label using the surface enhanced Raman particles has strong and stable signals, so that the data (Raman signals) reading time is short, and the future commercial application is facilitated.

4) The anti-counterfeiting method based on the PUF and the substrate layer and the protective layer materials used by the PUF anti-counterfeiting label are cheap and easy to obtain, and the preparation method is simple, so that the cost is low and the manufacture is easy.

In conclusion, the anti-counterfeiting method or the anti-counterfeiting label based on the PUF is expected to become the mainstream development trend of the future anti-counterfeiting technology.

The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.

Drawings

FIG. 1 is a schematic diagram of a structure based on surface enhanced Raman nanoparticles in one embodiment of the present invention;

FIG. 2 is 1078cm in Raman spectrum of a pattern collected in one embodiment of the present invention^-1Raman imaging and Raman spectroscopy plots of the intensity of the Raman peak, wherein FIG. 2a is a Raman imaging plot of a pixel of (i)2 × 2, (ii)10 × 10, and (iii)50 × 50 pixels, FIG. 2b is a Raman spectroscopy plot of the corresponding pixel of FIG. 2 a;

FIG. 3 is a diagram illustrating a Raman signal after being digitized in an embodiment of the present invention; fig. 3a is a schematic diagram of raman signals after binary coarse graining mapping in (i)2 × 2, (ii)10 × 10 and (iii)50 × 50 pixels to a set {0,1 }; FIG. 3b is a graph of Raman signals after four-valued coarse-grained mapping into the set {0,1} in (i)2 × 2, (ii)10 × 10, and (iii)50 × 50 pixels; fig. 3c is a perspective view of the signal strength values of fig. 3b.

Fig. 4 is a schematic diagram of a raman signal obtained after data acquisition and digitization processes are performed three times on the same tag in an embodiment of the present invention, and a schematic diagram of a raman signal obtained after three different tags are digitized by a threshold determined by a global search algorithm; wherein (i), (ii) and (iii) in fig. 4a represent the results of three binary coarse granulations of the same label; FIG. 4b (i), (ii) and (iii) represent the results of three quadruplicate coarse granulations of the same tag, respectively; fig. 4c (i), (ii) and (iii) represent the results after binary coarse-grained of three different labels, respectively; FIG. 4d (i), (ii) and (iii) represent the results after four-value coarse-granulation of three different labels, respectively;

FIG. 5 shows 1018-1090cm in Raman spectrum of a mixture of three surface-enhanced Raman nanoparticles collected in one embodiment of the present invention^-1A Raman imaging graph drawn by the integral area of the Raman peak;

FIG. 6 is a three-dimensional perspective view of the Raman imaging view of FIG. 5;

fig. 7 is a raman image of each of three surface enhanced raman nanoparticles in an embodiment of the present invention; wherein i represents the surface enhanced Raman nanoparticles modified with o-nitrothiophenol; ii represents surface enhanced Raman nanoparticles modified with p-dimercapto-benzene; iii represents a surface enhanced Raman nanoparticle modified with p-nitrobenzenethiol; the left half part is an original numerical value Raman imaging graph formed after data reading, and the right half part is a Raman signal schematic diagram after binary coarse graining and four-value coarse graining;

FIG. 8 is a graph of Raman imaging after data is read using a laser shift and data fast processing mode of a confocal Raman spectrometer, in accordance with an embodiment of the present invention;

figure 9 is a diagram of a sandwich PUF tag and its raman image produced in one embodiment of the present invention.

Detailed Description

In a specific embodiment, a pixel point is a pixel point obtained by dividing a region into a plurality of sub-regions of equal size, and each sub-region is a pixel point.

In a specific embodiment, the coarse graining method is to divide an overall range into several sub-ranges according to a certain dividing value, and all values in each sub-range are classified into a specific value (e.g. 0 and 1 in binary coarse graining, and 0,1,2 and 3 in four-value coarse graining). The segmentation value for segmenting the whole range in the coarse-grained method is an optimal threshold determined by a global search algorithm.

In a specific implementation manner, the global search algorithm searches and determines an optimal threshold within a certain search range, for example, for binary coarse graining, only one segmentation value is needed, and the search range of the segmentation value is 0-1; for four-value coarse graining, three segmentation values are required, such as searching between 0-0.15, 0.15-0.4, 0.4-1 respectively.

PUF (Physical unclonable function) technology is a newly developed technology. With this technique, the security label produced by a random process, called PUF security label, is usually patterned with a chaotic distribution of micro-and even nano-structures, which is easy to manufacture but difficult to counterfeit.

However, in the prior art, the intensity of scattered light of the PUF label based on scattering is easily affected by the environment or the angle of incident light, and the encoding capability is not high; fluorescence-based PUF tags are susceptible to fluorescent bleaching, resulting in large variations and instability in signal intensity. Therefore, both scattering-based and fluorescence-based PUF tags can only be encoded with the presence or absence of a signal.

The smart label which adopts the Raman nano material also utilizes the existence or nonexistence of Raman signals, and a bar code label which can be cloned is prepared (such as Chinese patent CN 103186803A). The common Raman nano material is caused by a metal nano core and a structure with Raman signal molecules distributed on the surface, and the Raman material with the structure has unstable property and poor particle repeatability, so that the information of Raman signals can be only utilized.

In order to increase the encoding capacity of the anti-counterfeit label and facilitate the development of the PUF label, the inventors tried to start with a raman nano material and utilize the raman nano material with stable properties and good particle repeatability, so that the raman signal intensity information of the raman material can be utilized.

In one embodiment of the invention, an anti-counterfeiting method based on PUF is provided, wherein a pattern formed by random distribution of surface enhanced Raman nanoparticles is provided, data in the pattern is acquired, and digital processing is performed to form anti-counterfeiting coding information. Wherein the pattern or surface enhanced raman nanoparticle morphology or properties are as described above.

The data are pixel point position information, type information of the surface enhanced Raman nano-particles and Raman signal information. The raman signal information is information on the presence or absence and/or intensity of a raman signal. When a surface enhanced raman nanoparticle is used, intensity information is obtained by appropriate raman peaks in the raman spectrum; when two or more surface enhanced raman nanoparticles are used, the raman spectrum of each surface enhanced raman nanoparticle is separated, and an appropriate raman peak in the separated raman spectrum is selected to obtain intensity information.

I. Patterning using only one type of surface enhanced Raman nanoparticles

The pattern has two-dimensional coding capability, which is the spatial position of the pixel point and the raman signal information respectively. The two-dimensional coding capability can be further divided into a binary coding mode and a multivariate coding mode, and specifically:

1) binary coding, namely representing binary '0' and '1' by the absence or the presence of Raman signals, and combining the spatial positions of pixels, wherein when the resolution of n × m pixels is adopted, the label coding capacity of the binary coding is 2^n·m(ii) a Wherein n and m are positive integers greater than 1.

2) Multivariate coding, namely representing '0', '1' … … and 'z' of (z +1) system by the inexistence and different signal intensity (z signal intensities) of Raman signals, combining the spatial positions of pixels, and when the resolution of n × m pixels is adopted, the label coding capacity of the multivariate coding is (z +1)^n·mFor example, when the intensity of the Raman signal is divided into 3 different intensities, the Raman signal information has 4 kinds of no signal, level 1 signal, level 2 signal and level 3 signal, so that the quaternary code can be formed, and when the resolution of 50 × 50 pixels is adopted, the label coding capacity of the quaternary code is (3+1)²⁵⁰⁰(about 1.4 × 10¹⁵⁰⁵). Wherein n and m are both positive integers larger than 1, and z is a positive integer. Here, if z is 1, it indicates that there is a raman signal, which is the binary code described above.

Specifically, the digitization process includes data reading, data preprocessing, and digitization of the pattern. The data reading mainly comprises reading pixel point position information and Raman signal information in a scanning or imaging mode. The data pre-processing is primarily to remove or at least partially remove noise and background in the raman imaging data. The digitization is mainly to obtain the Raman signal information of the surface enhanced Raman nanoparticles after the previous processing, and the anti-counterfeiting coding information is formed by combining the position information of the pixel points.

Patterning using two or more surface enhanced Raman nanoparticles

The pattern has three-dimensional coding capability, namely the spatial position of a pixel point, the type of the surface enhanced Raman nano-particles and Raman signal information. The three-dimensional coding capability can be further divided into a binary coding mode and a multi-element coding mode, and specifically:

1) binary coding, namely binary '0' and '1' represented by the absence or the presence of a Raman signal, combining the spatial position of pixels and the type (y types) of surface-enhanced Raman nanoparticles, wherein when the resolution of n × m pixels is adopted, the label coding capacity of the binary coding is (2)^y)^n·m(ii) a Wherein n and m are positive integers greater than 1.

2) Multivariate coding, namely representing '0', '1' … … and 'z' of (z +1) system by the inexistence and different signal intensity (z signal intensities) of Raman signals, combining the spatial position of pixels and the type (y types) of surface enhanced Raman nanoparticles, wherein when the resolution of n × m pixels is adopted, the label coding capacity of the multivariate coding is [ (z +1)^y]^n·mFor example, when the intensity of the Raman signal is divided into 3 different intensities, the Raman signal information has 4 kinds of no signal, level 1 signal, level 2 signal and level 3 signal, so that the quaternary code can be formed, and when the resolution of 50 × 50 pixels is adopted and 3 kinds of surface enhanced Raman nanoparticles are adopted, the label coding capacity of the quaternary code is [ (3+1)³]²⁵⁰⁰(about 2.8 × 10⁴⁵²⁵). Wherein n and m are positive integers larger than 1, and y and z are positive integers. Here, if z is 1, it indicates that there is a raman signal, which is the binary code described above.

Specifically, the digitization process includes data reading, data preprocessing, component separation, and digitization of the pattern. The data reading mainly comprises reading pixel point position information and Raman signal information in a scanning or imaging mode. The data pre-processing is primarily to remove or at least partially remove noise and background in the raman imaging data. The component separation is mainly to calculate and obtain the ratio coefficient of each surface enhanced Raman nano-particle according to the total Raman imaging data and the respective reference spectrum of each surface enhanced Raman nano-particle, form the Raman spectrum of each surface enhanced Raman nano-particle after separation by the product of the coefficient and the reference spectrum, and select a proper Raman peak to obtain the Raman signal intensity value of each surface enhanced Raman nano-particle. Optionally, when the pattern is disposed on the substrate layer, after obtaining the raman signal intensity value, the raman spectrum and the quadratic term of the substrate are also added to fit the background signal that cannot be completely removed during the data preprocessing. The digitization mainly comprises the steps of obtaining the type and Raman signal information of the surface enhanced Raman nano particles after the previous treatment, and combining the position information of pixel points to form anti-counterfeiting coding information.

Optionally, more accurate anti-counterfeiting code information in a pattern is obtained through a repeatability test, and the anti-counterfeiting code information is transmitted into a database.

In an optional specific embodiment, the PUF-based anti-counterfeiting method further includes a verification step, that is, after the anti-counterfeiting code information is formed or the anti-counterfeiting code information is loaded into the database, a subsequent user detects the pattern by using a raman device and compares the pattern with data in the database to verify authenticity.

In another embodiment of the invention, a PUF security tag is provided comprising a patterned anti-counterfeiting layer formed from randomly distributed surface-enhanced raman nanoparticles. Anti-counterfeiting coding information is formed by the position information (namely the row and column positions of all pixels), the surface enhanced Raman nanoparticle type information and the Raman signal information of the pixel points in the anti-counterfeiting layer. The raman signal information includes the presence or absence of a raman signal and may also include intensity information of the raman signal.

Wherein, the types of the surface enhanced Raman nanoparticles can be one or two or more:

I. patterning using only one type of surface enhanced Raman nanoparticles

The tag has two-dimensional encoding capability, respectively spatial location of pixels and raman signal information. The two-dimensional coding capability can be further divided into a binary coding mode and a multi-element coding mode, which are specifically described above.

Patterning using two or more surface enhanced Raman nanoparticles

The label has three-dimensional coding capacity, namely the spatial position of a pixel, the type of the surface enhanced Raman nano-particles and Raman signal information. The three-dimensional coding capability can be further divided into a binary coding mode and a multi-element coding mode, which are specifically described above. In order to be able to use the intensity information of the raman signal, the raman particles used are surface enhanced raman nanoparticles. The surface enhanced raman nanoparticles are composed of a metal nano-substrate and characteristic raman molecules.

In an alternative embodiment, the metal nano-substrate includes, but is not limited to, a nano-core-shell particle structure (e.g., chinese patent application having a preparation method according to publication No. CN104914087A and entitled "surface enhanced raman nanoparticle with multi-layer core-shell structure and preparation method"), a nano-dendrite (e.g., chinese patent application having a preparation method according to publication No. CN105973865A and entitled "Au nano-dendrite surface enhanced raman scattering substrate and preparation method thereof"), a nanostar (e.g., chinese patent application having a preparation method according to publication No. CN106442461A and entitled "method for detecting bisphenol a based on enhanced raman spectroscopy effect"), nanospheres (e.g., chinese patent application having a preparation method according to publication No. CN107219212A and entitled "surface enhanced raman substrate material for detecting nitrite and preparation method thereof"), and combinations thereof, One, two or more of a nano triangular plate, a nano rod and a nano particle dimer. Characteristic Raman molecules include, but are not limited to, one, two or more of p-dimercaptobenzene (1,4-BDT), p-nitronitronitromercaptan (4-NBT), o-nitrothiophenol (2-NBT), 4-toluene-thiophenol (4-MBT), 2-mercapto-5-nitrobenzimidazole (2-M-5-NBI), 2-mercapto-6-nitrobenzothiazole (2-M-6-NBT), o-chlorothiophenol (2-CBT), 4-chlorothiophenol (4-CBT), biphenyl-4, 4 '-dithiol (4,4' -BPDT), and 2-napthalenethiol (2-NT).

In an alternative embodiment, the nanocore and shell of the nanocore-shell particle structure have a gap therebetween, and the characteristic raman molecule is located in the gap. For example, see Gandra N, Singmananei S.Adv.Mater.2013,25, 1022-1027; lin L, Zapata M, Ye J, et al nano lett, 2015,15(10), 6419-; LinL, Gu H C, Ye J. chem. Commun.,2015,51, 17740-17743; zhang Y Q, Xiao Z Y, Ye J, et al ACS appl. mater. interfaces 2017,9, 3995-4005.

In another alternative embodiment, the core-shell nanoparticle structure has a gap between the core and shell layers; the shell layer is provided with a first layer and a second layer, and the second layer is provided with a gap; the characteristic raman molecule is located in the gap. For example, the preparation method can comprise the following steps: adding raw material nano-core particles into an aqueous solution of a surfactant, centrifuging, and re-dispersing in the aqueous solution of the surfactant to obtain a nano-core taking the surfactant as a stabilizer; step two, adding a Raman signal molecule solution into the nano-core which is obtained in the step one and takes the surfactant as the stabilizing agent, centrifuging, and re-dispersing in the surfactant aqueous solution to prepare and obtain the nano-particles which are coated with the first Raman signal layer on the outer surface of the nano-core, namely the nano-particles which are modified with Raman signal molecules on the outer surface of the nano-core; step three, adding the nanoparticles obtained in the step two, wherein the outer surfaces of the nano cores are coated with the first Raman signal layer, into a growth solution mixed by an aqueous solution containing a surfactant, a metal ion compound solution and a reducing agent to obtain the nanoparticles with shell layers coated outside the first Raman signal layer, and then obtaining the Raman probe; the metal ion compound solution is selected from one or more of chloroauric acid solution, silver nitrate solution, copper chloride solution, copper sulfate solution and chloroplatinic acid solution.

In an alternative embodiment, the PUF security label has a substrate layer and a protection layer in addition to the security layer. The substrate layer is used for providing certain support for the anti-counterfeiting layer and the protective layer, and plays a role of a carrier. The protective layer is used for preventing the anti-counterfeiting layer from being damaged in the processes of transportation, storage and the like, and plays a role in protection. As known to those skilled in the art, the anti-counterfeiting layer can also be directly arranged on an article needing anti-counterfeiting, such as a document, clothing and food package needing anti-counterfeiting.

In another embodiment of the present invention, a method for preparing a PUF security tag is provided, where the PUF security tag includes a substrate layer, a security layer, and a protection layer, the security layer is a pattern formed by randomly distributed surface enhanced raman nanoparticles, the security layer is located on the substrate layer, and the protection layer is located on the security layer; the preparation method comprises the following steps: and dripping the sol of the surface-enhanced Raman nano particles on the protective layer, and covering the substrate layer on the sol to form the anti-counterfeiting layer. As known to those skilled in the art, the PUF anti-counterfeit label with the above structure can be prepared by various methods, such as dropping a sol of surface enhanced Raman nanoparticles on a substrate layer, and then covering a protective layer.

The technical content of the invention is further explained by the following embodiments: the following examples are illustrative and not intended to be limiting, and are not intended to limit the scope of the invention. The experimental procedures used in the following examples are all conventional procedures unless otherwise specified. Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.

The first embodiment is as follows: preparation of core-shell structured surface-enhanced Raman nanoparticles (coated with p-dimercapto-benzene Raman molecule)

The method comprises the following steps: taking 2mL of gold nano-core particles (with the particle size of 25nm and dispersed in 0.1mol/L of hexadecyl ammonium chloride solution) prepared by a seed growth method at 1nmol/L, and centrifugally separating and re-dispersing the gold nano-core particles in 2mL of 0.025mol/L of hexadecyl ammonium chloride solution to obtain gold nano-cores taking hexadecyl ammonium chloride as a stabilizer;

step two: adding 100uL of p-dimercapto-benzene solution into the gold nano-core, wherein the concentration of the solution is generally more than 2mmol/L, such as 3mmol/L, 4mmol/L, 5mmol/L and the like, mixing and oscillating for 2-4 hours, then centrifugally separating, and re-dispersing in 1mL of 0.05mol/L hexadecyl ammonium chloride solution, repeating for multiple times (for example, repeating for three times and four times) to obtain the gold nano-particle with a layer of Raman molecular layer modified on the outer surface of the gold nano-core;

step three: adding the gold nanoparticles into a growth solution mixed by 20mL of 0.05mol/L hexadecyl ammonium chloride solution, 1mL of 3-7mmol/L (such as 3.42mmol/L, 4.86mmol/L, 6.30mmol/L and the like) chloroauric acid solution and 600uL of 25-55mmol/L (such as 30mmol/L, 40mmol/L, 50mmol/L and the like) ascorbic acid solution, and oscillating and stirring to obtain the surface-enhanced Raman nanoparticles with a core-shell structure, wherein a layer of a gold shell layer is attached to the outer surface of the gold nanoparticles. The schematic diagram of the structure of the nanoparticle is shown in fig. 1, wherein 1 represents a gold shell layer, and 2 represents a characteristic raman signal molecule.

Example two: preparation of surface-enhanced Raman nanoparticles with core-shell structure (coating p-nitrobenzenethiol or o-nitrobenzenethiol Raman molecule)

The method comprises the following steps: taking 2mL of gold nano-core particles (with the particle size of 25nm and dispersed in 0.1mol/L of hexadecyl ammonium chloride solution) prepared by a seed growth method at 0.47nmol/L, and centrifugally separating and re-dispersing the gold nano-core particles in 2mL of 0.025mol/L of hexadecyl ammonium chloride solution to obtain gold nano-cores taking hexadecyl ammonium chloride as a stabilizer;

step two: adding 100uL of p-nitronitromercaptol or o-nitrothiophenol solution into the gold nano-core, wherein the concentration of the solution is generally more than 8mmol/L, such as 9mmol/L, 10mmol/L, 11mmol/L and the like, mixing and oscillating for 10-40 minutes, then centrifugally separating, re-dispersing in 1mL of 0.05mol/L hexadecyl ammonium chloride solution, repeating for many times to obtain the gold nano-particles with a layer of Raman molecular layer modified on the outer surface of the gold nano-core;

step three: adding the gold nanoparticles into a growth solution mixed by 16mL of 0.05mol/L hexadecyl ammonium chloride solution, 800uL of 3-7mmol/L (such as 3.42mmol/L, 4.86mmol/L, 6.30mmol/L and the like) chloroauric acid solution and 480uL of 25-55mmol/L (such as 30mmol/L, 40mmol/L, 50mmol/L and the like) ascorbic acid solution, and oscillating and stirring to obtain the surface-enhanced Raman nanoparticles with a core-shell structure, wherein a layer of gold shell layer is attached to the outer surface of the gold nanoparticles.

Example three: PUF-based anti-counterfeiting method using surface-enhanced Raman nanoparticles

1) Providing a pattern formed by a random distribution of surface enhanced raman nanoparticles

The surface enhanced raman nanoparticle sol modified with p-nitrobenzenethiol prepared according to the second example was concentrated to 0.6nmol/L, and 2 μ L of the solution was dropped onto a silica substrate at will to form a pattern that could not be repeated.

2) Obtaining data

100 × 100 μm in the selected pattern²The area is divided into 2 × 2, 10 × 10 and 50 × 50 pixel points, and a confocal Raman spectrometer sample stage moving mode and a 60 × lens are adopted to respectivelyTesting the spectrum of the random pattern to obtain a Raman spectrum of each pixel, wherein the excitation wavelength is 785nm, and the laser power density is 3 × 10⁵W/cm²The acquisition time was 10 ms. 1078cm in the selected spectrum^-1The intensity of the raman peak was plotted for raman imaging as shown in fig. 2.

3) Digital processing

The PUF label coding is completed mainly by quantifying Raman intensity information of each pixel point in the test and combining position information of each point, and the coding comprises binary coding and quaternary coding.

Data preprocessing: and (4) exporting the data of the Raman imaging image, and performing data preprocessing, including background and noise removal. Specifically, an S-G filter is adopted to filter partial noise, so that the spectral data are smoother, and a fourth-order polynomial with a threshold value of 0.001 and a loss function of asymmetric truncated quadratic is adopted to fit and remove the background;

3b, digitalization: normalizing the Raman intensities of all the pixel points to [0,1 ]; then, an optimal threshold value is determined by adopting a global search algorithm, and Raman intensity data are mapped to a set {0,1} or {0,1,2,3} by means of a binary and quaternary rough graining method to respectively realize binary coding and quaternary coding, in other words, Raman signals are classified into nonexistence or existence after binary rough graining, and Raman signals are classified into nonexistence intensity and three intensities of 1,2 and 3 after quaternary rough graining. The raman signal after processing is schematically shown in fig. 3.

For example, the PUF labels of FIG. 3a (iii) FIG. 3a binary code with 50 × 50 pixel resolution and FIG. 3b (iii) Quaternary code with 50 × 50 pixel resolution may be represented as a matrix

And

the matrix has 2500 rows and 1 column, which respectively represent 2500 pixels and 1 nano-particle, and the element value in the matrix represents Raman signalNumber information 50 × 50 binary and quaternary coded PUF tags with pixel resolution have a coding capacity of 2 for each²⁵⁰⁰(about 3.8 × 10⁷⁵²) And 4²⁵⁰⁰(about 1.4 × 10¹⁵⁰⁵) Therefore, it can be seen that the encoding capability is huge.

4) Authentication

And repeating the two processes of data acquisition and digitization of the PUF label for three times to obtain three times of encoding results of the same label (see fig. 4a and 4b), and digitizing other three different labels by using a threshold value determined by a global search algorithm (see fig. 4c and 4 d). And subtracting the matrixes of the two digital labels to calculate the percentage of the element 0, namely the similarity index i of the two labels. Similarity indices between the same label and different labels were calculated separately and are shown in tables 1 and 2.

TABLE 1 similarity index i between different test methods for the same PUF tag

i_11’-1And i_11’-2Representing the similarity index between the first and second test, the first and third test performed on the same PUF tag in figure 4.

Table 2 similarity index i between different PUF tags

i₁₂、i₁₃And i₁₄Representing the similarity index between the first test of the objective PUF tag in fig. 4 and the other three PUF tags.

From the results it can be seen that the similarity index of the same tag does not reach 100%, probably due to the instability of the raman test system and the signal fluctuations of the nanoparticles themselves. Furthermore, as the resolution increases, the similarity index of the same label becomes more stable. For a label with 2 × 2 pixel resolution, although the repetition rate can sometimes reach 100%, the fluctuation is large; when the resolution is 50 × 50 pixels, the similarity index fluctuation of the same label is small, and the repetition rate can be maintained at 80% or more. In addition, when the resolution is higher, the similarity index difference between different labels and the same label is obvious, which shows that the same label and the different label can be effectively distinguished through the verification process.

Example four: PUF-based anti-counterfeiting method using three surface-enhanced Raman nanoparticles

Three surface enhanced raman nanoparticle sols prepared according to the procedure of example one and example two were mixed uniformly, each at a nanoparticle concentration of 0.6nmol/L, and 2 μ L of the mixed solution was dropped onto a silica substrate with a mark as desired to form an unrepeatable pattern.

2) Obtaining data

The selection is 100 × 100 μm²And the area is divided into 50 × 50 pixel points, the spectrum of the random pattern is tested by adopting a moving mode of a sample stage of a confocal Raman spectrometer and a 60 × lens to obtain the Raman spectrum of each pixel, wherein the excitation wavelength is 785nm, and the laser power density is 3 × 10⁵W/cm²The acquisition time was 10 ms. The Raman peak of p-dimercaptobenzene, p-nitromercaptan or o-nitrothiophenol is 1018-1090cm^-1There is overlap in the bands, so the integrated area of the band in this range was chosen to plot a raman image containing three nanoparticle signals, as shown in fig. 5 and 6.

3) Digital processing

The PUF label coding is mainly completed by quantifying Raman intensity information of each pixel point in the test and combining different types of surface enhanced Raman nanoparticles and position information of each point, and therefore the PUF label coding comprises binary coding and quaternary coding.

component separation: since the raman spectra of the three nanoparticles used in this example overlap, non-negative least squares (NNLS) was used to separate the different components. The Raman spectra measured by the three types of nanoparticles are used as reference spectra, the optimal fitting spectra are obtained by optimizing the coefficients of different components through an algorithm, and the respective Raman spectra of the three types of nanoparticles are obtained by multiplying the coefficients of the components by the corresponding reference spectra. For each type of surface-enhanced raman nanoparticles, the higher the concentration of a certain type of surface-enhanced raman nanoparticles of each pixel point is, the higher the intensity value belonging to the molecule in the total raman intensity of the pixel point is.

The raman spectrum of silica and quadratic term were also added to fit background signals that were not completely removed during pretreatment. Selecting 1033cm for the spectra of the separated o-nitrobenzothiophenol, p-dimercapto and p-nitrobenzenethiol^-1，1058cm^-1And 1078cm^-1The intensity of the raman peak was plotted for each of the three nanoparticles as shown in the left half of fig. 7. The difference of Raman intensity among pixels is obvious, which shows that effective coding can be carried out subsequently;

3c, digitalization: and respectively digitizing the Raman imaging images of the three types of nanoparticles obtained in the last step, wherein the digitization process of each type of nanoparticles is the same. Firstly, normalizing the Raman intensities of all pixel points to [0,1 ]; and then, determining an optimal threshold value by adopting a global search algorithm, and mapping the Raman intensity data to a set {0,1} or {0,1,2,3} by means of a binary and quaternary coarse graining method to respectively realize binary coding and quaternary coding. In other words, after binary coarse graining, the raman signal is classified as absent or present, and after quaternary coarse graining, the raman signal is classified as absent or 1,2,3 intensities. The raman signal after processing is schematically shown in the right half of fig. 7.

The PUF label has three-dimensional coding capacity, namely the spatial position of a pixel, the type of surface-enhanced Raman nanoparticles and Raman intensity. Binary coding in FIG. 7And quad-coded PUF tags may be represented as matrices, respectively

And

the matrix has 2500 rows and 3 columns, which respectively represent 2500 pixels and 3 types of surface-enhanced nanoparticles, and the element values in the matrix represent Raman intensity. The code capacity of the binary and quaternary coded PUF label is (2)³)²⁵⁰⁰(about 5.3 × 10²²⁵⁷) And (4)³)²⁵⁰⁰(about 2.8 × 10⁴⁵²⁵) The encoding capacity is further improved compared with a PUF label containing a nanoparticle.

Example five: read time experiment

The surface enhanced Raman nanoparticle sol modified with p-nitrobenzenethiol prepared according to the second example was concentrated to 4nmol/L, 2. mu.L of the solution was dropped onto a silica substrate to form a non-reproducible pattern, 100 × 100 μm was selected²The region is divided into 50 × 50 pixel points, the spectrum of the random pattern is tested by adopting a laser moving and data rapid processing mode of a confocal Raman spectrometer and a 60 × lens, the excitation wavelength is 785nm, and the laser power density is 3 × 10⁵W/cm²The acquisition time is about 0.7ms, the raman spectrum of each pixel is obtained, and the total reading time is 6 s. If the platform moving mode is adopted, the Raman imaging with the same resolution ratio needs 20 min. 1078cm in the selected spectrum^-1The intensity of the raman peak was plotted for raman imaging as shown in fig. 8.

Both laser and platform movement modes can be read and data obtained. Signals are acquired in a platform moving mode, and the signals are strong; and the laser moving mode is adopted to acquire signals, so that the reading speed is high.

Example six: preparation of PUF (physical unclonable function) anti-counterfeiting label

The surface-enhanced raman nanoparticle sol modified with p-nitrobenzenethiol prepared according to the second example was concentrated to 10nmol/L, 2 μ L of the solution was dropped onto the sticky side of a transparent tape (protective layer) to form a pattern that could not be repeated, and then pasted onto printing paper (substrate) to obtain a PUF label with a sandwich structure.

Selecting 1.8 × 1.8mm²The area is divided into 50 × 50 pixel points, the spectrum of the random pattern is tested by adopting a confocal Raman spectrometer 10 × lens, the excitation wavelength is 785nm, and the laser power density is 6.1 × 10⁴W/cm²The acquisition time is 10ms, and the raman spectrum of each pixel is obtained and then drawn into a raman imaging graph, as shown in fig. 9. The difference of Raman intensity among pixels is obvious, so that an effective PUF label can be obtained through subsequent digital operation; and the background signals of the transparent adhesive tape and the printing paper are very weak, so that the signal test of the nano particles cannot be interfered.

Alternatively, by changing the raman signal molecules at the nanoparticle embedded part, more different surface enhanced raman nanoparticles can be obtained, and different nanoparticles have different raman spectra, and mixed signals can be separated by the NNLS algorithm. The combination of more nanoparticles can increase the coding capacity even further.

In the above manufacturing method, the substrate and the protective layer are cheap and easily available materials, so that the manufacturing cost is low.

The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.

Claims

1. An anti-counterfeiting method based on PUF is characterized in that a pattern formed by random distribution of surface enhanced Raman nanoparticles is provided, data in the pattern are obtained and are subjected to digital processing to form anti-counterfeiting code information.

2. The PUF-based anti-counterfeiting method according to claim 1, wherein the data is pixel point position information, species information of the surface-enhanced raman nanoparticles, and raman signal information.

3. The PUF-based anti-counterfeiting method according to claim 2, wherein the raman signal information is presence and/or intensity information of a raman signal.

4. A PUF-based anti-counterfeiting method according to claim 3, wherein when a surface enhanced raman nanoparticle is used, the intensity information is obtained from a suitable raman peak in the raman spectrum; when two or more surface enhanced raman nanoparticles are used, the raman spectrum of each surface enhanced raman nanoparticle is separated, and an appropriate raman peak in the separated raman spectrum is selected to obtain intensity information.

5. The PUF-based anti-counterfeiting method according to claim 2, wherein the surface-enhanced raman nanoparticles are composed of a metallic nano-substrate and a characteristic raman molecule.

6. The PUF-based anti-counterfeiting method according to claim 5, wherein the metal nano-substrate structure is selected from one, two or more of a nano core-shell particle structure, a nano dendrite, a nano star, a nano sphere, a nano triangular plate, a nano rod, and a nano particle dimer; the characteristic Raman molecule is selected from one, two or more of p-dimercaptobenzene (1,4-BDT), p-nitrobenzenethiol (4-NBT), o-nitrobenzenethiol (2-NBT), 4-toluenethiol (4-MBT), 2-mercapto-5-nitrobenzimidazole (2-M-5-NBI), 2-mercapto-6-nitrobenzothiazole (2-M-6-NBT), o-chlorobenzenethiol (2-CBT), 4-chlorobenzenethiol (4-CBT), biphenyl-4, 4 '-dithiol (4,4' -BPDT) and 2-naphthalene thiol (2-NT).

7. The PUF-based anti-counterfeiting method according to claim 1, wherein the digitization process includes data preprocessing and digitization of data obtained from the pattern.

8. The PUF-based anti-counterfeiting method according to claim 7, wherein the data preprocessing is to filter out partial noise of the raman signal information and remove background signals.

9. A PUF-based anti-counterfeiting method according to claim 7, wherein when two or more types of surface-enhanced Raman nanoparticles are used, component separation is required after data preprocessing and before digitization.

10. The PUF-based anti-counterfeiting method according to claim 9, wherein the components are separated into raman spectra that separate different types of surface-enhanced raman nanoparticles.

11. The PUF-based anti-counterfeiting method according to claim 10, wherein the pattern is provided on a substrate layer; and during component separation, after the Raman signal intensity value is obtained, the Raman spectrum and the quadratic term of the base material are added to fit a background signal which cannot be completely removed during data pretreatment.

12. The PUF-based anti-counterfeiting method according to claim 7, wherein the digitization normalizes and segments raman signal intensity values of the surface-enhanced raman nanoparticles to form relative raman signal intensities; and combining the position information of each pixel point, the type information of the surface enhanced Raman nano particles and the relative Raman signal intensity to form anti-counterfeiting coding information.

13. A PUF-based anti-counterfeiting method according to claim 12, wherein the digitization comprises the steps of:

14. A PUF-based anti-counterfeiting method according to claim 1, wherein the pattern is detected by a raman spectrometer to obtain data in the pattern.

15. The PUF-based anti-counterfeiting method according to claim 14, wherein the detection imaging manner is sample stage movement, laser movement, or both movement.

16. The PUF-based anti-counterfeiting method according to claim 1, further comprising verification that the pattern is detected using a raman device and compared to data in a database.

17. Use of a PUF-based anti-counterfeiting method according to claims 1 to 16 in the field of security anti-counterfeiting.

18. A PUF anti-counterfeiting label is characterized by comprising an anti-counterfeiting layer, wherein the anti-counterfeiting layer is a pattern formed by randomly distributed surface enhanced Raman nanoparticles.

19. The PUF security tag of claim 18, wherein said security layer is configured to provide pixel location information, surface enhanced raman nanoparticle species information, and raman signal information.

20. The PUF security tag of claim 19, wherein the raman signal information is the presence and/or strength of a raman signal.

21. The PUF security tag of claim 18, wherein the surface enhanced raman nanoparticles are comprised of a metallic nanomatrix and a characteristic raman molecule.

22. The PUF security tag of claim 21, wherein the metallic nanomatrix structure is selected from one, two or more of a group consisting of a nanoparticle-core shell particle structure, a nanotendrite, a nanostar, a nanosphere, a nanotaper, a nanorod, and a nanoparticle dimer.

23. The PUF security tag of claim 22, wherein the nanocore and shell layers of the nanocore-shell particle structure have a gap therebetween, the characteristic raman molecule being located in the gap.

24. The PUF security tag according to claim 23, wherein a gap is provided between the nanocore and the shell layer of the nanocore-shell particle structure; the shell layer has a first layer and a second layer, the second layer having a gap; the characteristic raman molecule is located in the gap.

25. The PUF security tag according to claim 21, wherein the characteristic raman molecule is selected from one, two or more of p-dimercaptobenzene (1,4-BDT), p-nitrobenzenethiol (4-NBT), o-nitrobenzenethiol (2-NBT), 4-toluenethiol (4-MBT), 2-mercapto-5-nitrobenzimidazole (2-M-5-NBI), 2-mercapto-6-nitrobenzothiazole (2-M-6-NBT), o-chlorothiol (2-CBT), 4-chlorobenzenethiol (4-CBT), biphenyl-4, 4 '-dithiol (4,4' -dt bp), and 2-napthalenethiol (2-NT).

26. The PUF security tag of claim 18, wherein the surface-enhanced raman particle is one, two or more species.

27. The PUF security tag of claim 18, further comprising a substrate layer and a protective layer; the anti-counterfeiting layer is located on the base material layer, and the protective layer is located on the anti-counterfeiting layer.

28. The PUF security tag of claim 27, wherein the substrate layer is made of paper, silicon, glass, metal or polymer; the protective layer is made of silicon chips, plastic films or macromolecules.

29. The preparation method of the PUF anti-counterfeiting label is characterized in that the PUF anti-counterfeiting label comprises a substrate layer, an anti-counterfeiting layer and a protective layer, wherein the anti-counterfeiting layer is a pattern formed by randomly distributed surface enhanced Raman nanoparticles, the anti-counterfeiting layer is positioned on the substrate layer, and the protective layer is positioned on the anti-counterfeiting layer;

the preparation method comprises the following steps: dropping sol of surface-enhanced Raman nanoparticles onto the protective layer, and covering the substrate layer on the sol to form the anti-counterfeiting layer; or dropping the sol of the surface enhanced Raman nano-particles on the substrate layer, and then covering the protective layer on the sol, wherein the anti-counterfeiting layer is formed by the sol.