A random number key generation method based on surface enhanced fluorescence effect

Abstract

The present invention relates to a random number key generation method based on surface enhanced fluorescence effect, including preparing a dense monolayer ordered plasmon metal nanoparticle film; preparing a randomly patterned dielectric layer by a dewetting method to generate a nanoparticle film composite layer with a randomly patterned dielectric layer; preparing a luminescent quantum dot layer on the dielectric layer to generate a fluorescent composite layer; a protective layer is encapsulated on the top of the fluorescent composite layer to form a surface enhanced fluorescence PUF device; performing fluorescence image acquisition and life image acquisition and preprocessing on the surface enhanced fluorescence PUF device to obtain an enhanced optical image; performing frequency domain feature extraction on the preprocessed enhanced optical image by an image hash algorithm or performing feature detection and feature dimension reduction by a CNN network to form a random number key. The present invention extracts the intrinsic entropy of the surface enhanced fluorescence PUF device, effectively solving the problem of small key storage capacity of the PUF device.

Description

Technical Field

[0001] The invention relates to the research field of PUF devices, and in particular to a random number key generation method based on surface enhanced fluorescence effect. Background Art

[0002] Modern cryptography attributes the security of cryptographic systems to the security of key systems through cryptographic algorithms and cryptographic protocols. Therefore, key management is the basic project of information security, and its technical level determines the security and benefits of the entire cryptographic system. The generation and distribution of keys have always been a bottleneck problem in key management. The use of cryptographic technology based on physical entities to generate and distribute keys to reduce key management risks and improve security is one of the hot directions in the development of information security technology in the world. Typical representatives of cryptographic technology include quantum key distribution technology and physical unclonable functions (PUF) technology. Among them, PUF has the characteristics of easy use, low cost, and low power consumption. The United States and European countries have invested a lot of money to research and develop PUF and its application technology in the fields of cryptography and network information security.

[0003] Drawing on the idea of ​​human biometric authentication (fingerprints and irises, etc.), Pappu proposed the idea of ​​using the intrinsic structural differences of hardware as hardware identification in 2001, and proposed the concept of physically unclonable functions. PUF achieves the unique function between the challenge signal (input) and the response signal (output) through the inevitable process parameter deviation or deliberately introduced random factors in the chip manufacturing process. The fundamental intention of the PUF idea is to use physical entities to realize the random function (ideal cryptographic function) that is difficult to achieve in cryptography. Its application has revolutionary significance for cryptography.

[0004] The more mature applications of PUF are mainly in the following directions: (1) Acting as a pseudo-random function or hash function for data and entity authentication. (2) As a random number generator for key production. Since PUF is random, it can be used to generate random numbers and then encapsulate various keys. (3) As a key management device for key distribution. Since each PUF device is unique and cannot be cloned, it is functionally equivalent to a cryptographic algorithm with a "key" (black box). Although neither the legitimate user nor the attacker can detect this "key", the party that owns the device can exclusively use the black box function to achieve key deployment. (4) As an anti-counterfeiting mark. The uniqueness and non-cloning of the PUF device make it a natural anti-counterfeiting mark.

[0005] For example, the publication number is CN110784312A, "A method for preparing a PUF device and a method for generating a key therefor: A method for preparing a PUF device and a method for generating a key therefor are disclosed. PbS quantum dots are synthesized by using existing cheap basic chemical substances such as sulfur S, lead dichloride PbCl2, oleylamine OLA, methanol, toluene, etc., and basic chemical experimental instruments are used in the process of synthesizing the PbS quantum dots. The distribution of the PbS quantum dots in the PUF device is derived from the Brownian motion of nanoparticles in the solution. The distribution of the PbS quantum dots has high uniqueness and randomness. The graythresh function and im2bw function in the MATLAB software are used to convert the distribution map of the PbS quantum dots inside the PUF device into a black and white image by TEM, and then the pixels are identified to obtain the initial key. The initial key is subjected to von Neumann processing and then grouped to obtain the final key. The advantage is that the raw materials for preparing the PUF device are easy to obtain, and a key with high randomness and uniqueness can be generated."

[0006] Existing optical unclonable encryption methods all perform optical imaging on the random spatial patterns of intrinsic materials (unclonable optical speckles or artificial fingerprint patterns), which can theoretically achieve extremely high encoding capacity or key space size. However, due to the light diffraction limit of ordinary optical components, the key storage capacity of PUF devices is much less than 1 Tbit / mm 3 .

[0007] Therefore, there is an urgent need for a PUF device preparation method and a key production method that can meet the requirements of large key storage capacity, high randomness of PUF devices, and strong robustness. Summary of the invention

[0008] In order to solve the problem of small key storage capacity of existing PUF devices, the present invention provides a random number key generation method based on surface enhanced fluorescence effect. The surface enhanced fluorescence PUF device has a great spatial distribution uncertainty within the sub-diffraction limit range through plasmon enhanced fluorescence effect. The intrinsic entropy of the surface enhanced fluorescence PUF device is extracted to effectively solve the problem of small key storage capacity of the PUF device.

[0009] In order to achieve the above object, the present invention proposes a random number key generation method based on surface enhanced fluorescence effect, comprising:

[0010] Step 1: Prepare a dense monolayer of ordered plasmonic metal nanoparticle film by liquid-air interface self-assembly;

[0011] Step 2: preparing a randomly patterned ultra-thin film by a dewetting method, and using the ultra-thin film as a dielectric layer of the nanoparticle film to generate a nanoparticle film composite layer with a randomly patterned dielectric layer;

[0012] Step 3: preparing a luminescent quantum dot layer on the dielectric layer, and combining the nanoparticle film, the dielectric layer and the luminescent quantum dot layer to generate a fluorescent composite layer;

[0013] Step 4: A protective layer is encapsulated on the top of the fluorescent composite layer to form a surface enhanced fluorescent PUF device;

[0014] Step 5: collecting a fluorescence image of the surface enhanced fluorescence PUF device through a fluorescence microscope;

[0015] The lifetime image of the surface enhanced fluorescence PUF device is collected by fluorescence lifetime imaging microscopy;

[0016] Step 6: preprocessing the fluorescence image and lifetime image to obtain an enhanced optical image;

[0017] Step 7: The preprocessed enhanced optical image is subjected to frequency domain feature extraction through an image hash algorithm or feature detection and feature dimension reduction through a CNN network, and is compressed and quantized into a binary string of limited length to form a random number key.

[0018] Among them, liquid-gas interface self-assembly, also known as gas-liquid interface self-assembly, is a technology for preparing large-area metal nanoparticle films by evaporating metal nanoparticle dispersions and depositing them on a smooth glass substrate. The device often uses LB (Langmuir-Blodgett) film technology. In the LB tank, the monolayer film is compressed by moving the barrier to obtain a tightly packed LB monolayer film. The LB monolayer film is transferred to the glass substrate to obtain a monolayer colloidal crystal, which is a dense monolayer ordered plasmon metal nanoparticle film.

[0019] Random number key generation principle:

[0020] The fluorescence intensity and fluorescence lifetime of the surface-enhanced fluorescence PUF device are very sensitive to the distance between the metal and the quantum dots, that is, the thickness of the dielectric layer. Therefore, dewetting is used to generate a dielectric layer with random thickness (random pattern) to realize the preparation of non-clonable devices based on metal-enhanced fluorescence. The thickness of the dielectric layer undergoes highly random changes through the dewetting process, which causes the fluorescence image and fluorescence lifetime image to be highly random as well. The "fingerprint" of the surface-enhanced fluorescence PUF device is then extracted to generate random number keys with high storage capacity.

[0021] The surface plasmon enhanced fluorescence effect has great spatial distribution uncertainty within the sub-diffraction limit range. Extracting the intrinsic entropy of surface-enhanced fluorescence PUF devices will effectively break through the application barrier of low key storage capacity of traditional optical PUF. In the process of constructing surface-enhanced fluorescence PUF devices, the inevitable process deviations introduce the relative position, direction and distance between molecules and plasmon nanostructures, the spectral overlap between molecules and plasmon nanostructures, and the near-field uncertainty of plasmon dark modes. These will together serve as a source of intrinsic entropy to give each coupled nanostructure a unique, unclonable and unpredictable "fingerprint".

[0022] Furthermore, the metal in step 1 includes one of Ag, Au, Cu, Al, Pd or Pt elements.

[0023] Furthermore, the step 2 comprises:

[0024] Step 2.1: Spin-coating a hydroxyl-terminated polystyrene (PS) film with a thickness of 2.9-3 nm on the nanoparticle film to obtain a first nanoparticle film composite layer, wherein the solvent is toluene and the spin-coating concentration is 0.5 wt %;

[0025] Step 2.2: Spin-coat a layer of poly 2-vinyl pyrrolidone (P2VP) film on the first nanoparticle film composite layer to obtain a second nanoparticle film composite layer, wherein the solvent is chlorobenzene and the spin-coating concentration is 1wt%;

[0026] Step 2.3: Place the second nanoparticle thin film composite layer in a glove box for thermal annealing at 250° C. for 5 minutes to generate a nanoparticle thin film composite layer with a randomly patterned dielectric layer.

[0027] Furthermore, the step 2 also includes:

[0028] Step 2.4: depositing a 2 nm thick parylene film on the nanoparticle film, and spin coating a 10 nm thick poly 4-vinylpyridine (P4VP) film on the surface of the parylene film;

[0029] Step 2.5: The nanoparticle film with the parylene film and the poly (4-vinylpyridine) film was placed in an empty drying oven for thermal annealing at 220 ◦ C for 4 h to generate a nanoparticle film composite layer with a randomly patterned dielectric layer.

[0030] Furthermore, the step 3 comprises:

[0031] A 1 mg / mL ZnCdSe@ZnS quantum dot chlorobenzene solution was spin-coated on the surface of the dielectric layer treated by a wet method.

[0032] Furthermore, the preprocessing in step 6 includes segmenting, standardizing and enhancing the fluorescence image:

[0033] The image is normalized and enhanced using an edge-preserving Gaussian curvature filter;

[0034] A global search algorithm is used to determine the common threshold of digitization, and a two-value coarse-grained encoding method is used to map each pixel value to the corresponding element of the set {0, 1} to form a black-and-white binary matrix.

[0035] Furthermore, the step 7 comprises:

[0036] Step 7.1: Extract features from the enhanced optical image through the frequency domain transform of the discrete cosine transform in the image hash algorithm, and quantize the numerical value representing the image feature by comparing each coefficient with the average value of the coefficient to form a random number key.

[0037] Furthermore, the step 7 comprises:

[0038] Step 7.2: Train the CNN model based on the AlexNet architecture, input the enhanced optical image output feature layer, activate the generated 4096-dimensional feature vector, and form the random number key.

[0039] Through the above technical solution, the beneficial effects of the present invention are:

[0040] 1. The entropy source of the present invention comes from the randomness of the metal enhanced fluorescence modulated by the dielectric layer thickness, and the "fingerprint" is highly unpredictable.

[0041] 2. The fluorescence intensity and fluorescence lifetime of the surface-enhanced fluorescence PUF device of the present invention vary greatly, have a strong contrast with background photons, have a high image signal-to-noise ratio, and have high key generation robustness.

[0042] 3. The present invention extracts entropy at the nanoscale and can generate keys with high storage capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the structure of a surface enhanced fluorescence PUF device of a random number key generation method based on surface enhanced fluorescence effect of the present invention;

[0044] Figure 2 It is a fluorescent image of a random number key generation method based on surface enhanced fluorescence effect of the present invention;

[0045] Figure 3 It is an enhanced optical image of a random number key generation method based on surface enhanced fluorescence effect of the present invention;

[0046] Figure 4It is a transformation image of a random number key generation method based on surface enhanced fluorescence effect of the present invention;

[0047] Figure 5 The Hamming distance distribution diagram in Example 1 of the random number key generation method based on surface enhanced fluorescence effect of the present invention is

[0048] Figure 6 It is a CNN model framework diagram of a random number key generation method based on surface enhanced fluorescence effect of the present invention;

[0049] Figure 7 It is a feature layer image outputted by five labels of a random number key generation method based on surface enhanced fluorescence effect of the present invention after CNN training;

[0050] Figure 8 yes Figure 7 4096-dimensional feature vector image;

[0051] Fig. 9 The present invention is a flow chart of the steps of a method for generating a random number key based on surface enhanced fluorescence effect. DETAILED DESCRIPTION

[0052] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments:

[0053] Example 1

[0054] like Figure 1 As shown, a random number key generation method based on surface enhanced fluorescence effect includes:

[0055] Step 1: Prepare a dense monolayer of ordered plasmonic metal nanoparticle film by liquid-air interface self-assembly;

[0056] Step 2: preparing a randomly patterned ultra-thin film by a dewetting method, and using the ultra-thin film as a dielectric layer of the nanoparticle film to generate a nanoparticle film composite layer with a randomly patterned dielectric layer;

[0057] Step 3: preparing a luminescent quantum dot layer on the dielectric layer, and combining the nanoparticle film, the dielectric layer and the luminescent quantum dot layer to generate a fluorescent composite layer;

[0058] Step 4: A protective layer is encapsulated on the top of the fluorescent composite layer to form a surface enhanced fluorescent PUF device;

[0059] Step 5: collecting a fluorescence image of the surface enhanced fluorescence PUF device through a fluorescence microscope;

[0060] The lifetime image of the surface enhanced fluorescence PUF device is collected by fluorescence lifetime imaging microscopy;

[0061] Step 6: preprocessing the fluorescence image and lifetime image to obtain an enhanced optical image;

[0062] Step 7: The preprocessed enhanced optical image is subjected to frequency domain feature extraction through an image hash algorithm or feature detection and feature dimension reduction through a CNN network, and is compressed and quantized into a binary string of limited length to form a random number key.

[0063] Figure 1 Among them, A is a protective layer, B is a luminescent quantum dot layer, C is a dielectric layer, D is a nanoparticle film, and E is a glass substrate.

[0064] Preferably, the metal in step 1 includes one of Ag, Au, Cu, Al, Pd or Pt elements.

[0065] Preferably, the step 2 comprises:

[0066] Step 2.1: Spin-coating a hydroxyl-terminated polystyrene (PS) film with a thickness of 2.9-3 nm on the nanoparticle film to obtain a first nanoparticle film composite layer, wherein the solvent is toluene and the spin-coating concentration is 0.5 wt %;

[0067] Step 2.2: Spin-coat a layer of poly(2-vinylpyrrolidone) (P2VP) film on the first nanoparticle film composite layer to obtain a second nanoparticle film composite layer, wherein the solvent is chlorobenzene and the spin-coating concentration is 1 wt %;

[0068] Step 2.3: Place the second nanoparticle thin film composite layer in a glove box for thermal annealing at 250° C. for 5 minutes to generate a nanoparticle thin film composite layer with a randomly patterned dielectric layer.

[0069] Preferably, the step 2 further comprises:

[0070] Step 2.4: depositing a 2 nm thick parylene film on the nanoparticle film, and spin coating a 10 nm thick poly 4-vinylpyridine (P4VP) film on the surface of the parylene film;

[0071] Step 2.5: The nanoparticle film with the parylene film and the poly (4-vinylpyridine) film was placed in an empty drying oven for thermal annealing at 220 ◦ C for 4 h to generate a nanoparticle film composite layer with a randomly patterned dielectric layer.

[0072] Preferably, step 3 comprises:

[0073] A 1 mg / mL ZnCdSe@ZnS quantum dot chlorobenzene solution was spin-coated on the surface of the dielectric layer treated by a wet method.

[0074] Preferably, the preprocessing in step 6 includes segmenting, standardizing and enhancing the fluorescence image and the lifetime image:

[0075] The image is normalized and enhanced using an edge-preserving Gaussian curvature filter;

[0076] A global search algorithm is used to determine the common threshold of digitization, and a two-value coarse-grained encoding method is used to map each pixel value to the corresponding element of the set {0, 1} to form a black-and-white binary matrix.

[0077] Preferably, the step 7 comprises:

[0078] Step 7.1: Extract features from the enhanced optical image through the frequency domain transform of the discrete cosine transform in the image hash algorithm, and quantize the numerical value representing the image feature by comparing each coefficient with the average value of the coefficient to form a random number key.

[0079] Preferably, the step 7 comprises:

[0080] Step 7.2: Train the CNN model based on the AlexNet architecture, input the enhanced optical image output feature layer, activate the generated 4096-dimensional feature vector, and form the random number key.

[0081] Example 2

[0082] Based on the above embodiments, in this embodiment, silver nanoparticles are taken as an example to prepare a nanoparticle film using an oil-water interface assembly method, and a surface enhanced fluorescent PUF device is prepared.

[0083] like Figure 1 As shown, silver nanoparticles with a diameter of 55 nm were used to prepare nanoparticle films using the oil-water interface assembly method, a 2 nm thick parylene film was deposited using atomic layer deposition, and then a 10 nm thick poly 4-vinylpyridine (P4VP) film was spin-coated on the surface of the parylene film.

[0084] The dewetted randomly patterned dielectric layer was formed by thermal annealing at 220 ◦C in a vacuum oven for 4 h.

[0085] A 1 mg / mL ZnCdSe@ZnS quantum dot chlorobenzene solution was spin-coated on the surface of the dewetting layer and dried. A polydimethylsilane (PDMS) protective layer was encapsulated on the top to obtain a surface-enhanced fluorescent PUF device.

[0086] The surface enhanced fluorescence PUF device was imaged using a fluorescence microscope to obtain a fluorescence image of the surface enhanced fluorescence PUF device ( Figure 2 , Figure 2 There are green fluorescent spots in the original image). The fluorescent image is grayed to obtain a grayscale image ( Figure 3 ), scaled to 32x32 pixels to obtain the scaled image, and the transformed image is obtained after discrete cosine transformation ( Figure 4 ), select the 16x16 matrix in the upper left corner, and then generate a 256-bit key. The key space storage capacity reaches 2.5 Tbit / mm3. The robustness and uniqueness of the generated key are measured using the Hamming distance distribution. By ( Figure 5 ) shows that the intra-chip Hamming distance is about 0.2, and the inter-chip Hamming distance is about 0.5.

[0087] Example 3

[0088] Based on the above embodiment, a dense silver nano-island film was prepared by using the silver mirror reaction, and a 10 nm thick polymethyl methacrylate (PMMA) film was first spin-coated on the surface of the silver mirror, and then a 10 nm thick polyvinyl pyrrolidone (PVP) film was spin-coated on the surface of the PMMA film. The film was then annealed for 30 minutes using solvent vapor in a sealed container filled with ethanol and water to form a dewetting randomly patterned dielectric layer.

[0089] A 1 mg / mL red light carbon dot toluene solution was spin-coated on the surface of the dewetting layer and dried. A polydimethylsilane (PDMS) protective layer was encapsulated on the top to obtain a surface-enhanced fluorescent PUF device.

[0090] Fluorescence lifetime imaging microscopy (FLIM) is used to collect images of surface-enhanced fluorescent PUF devices to obtain lifetime images of surface-enhanced fluorescent PUF devices. The lifetime image is binary segmented to form a black-and-white binary matrix, which is then scaled and von Neumann correction is performed to remove blanks and generate a 128-bit key. The key space storage capacity reaches 1.2 Tbit / mm 3 .

[0091] Example 4

[0092] like Figure 7 and 8 As shown, the enhanced optical image of Example 3 is input to the CNN, and the tail and output are adjusted starting from the eighth fully connected layer. Each network is trained for 50 cycles, and the minimum batch size is 100. After the CNN training is completed, each label will output the last feature layer (fully connected layer) and activate to generate a 4096-dimensional feature vector, which is stored in the database for subsequent authentication.

[0093] in, Figure 7 and 8 When generated, it is a color image.

[0094] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, any equivalent changes or modifications made according to the structures, features and principles described in the patent scope of the present invention should be included in the scope of the patent application of the present invention.

Claims

1. A random number key generation method based on surface enhanced fluorescence effect, characterized in that: include Step 1: Prepare a dense monolayer of ordered plasmonic metal nanoparticle film by liquid-air interface self-assembly; Step 2: preparing a randomly patterned ultra-thin film by a dewetting method, and using the ultra-thin film as a dielectric layer of the nanoparticle film to generate a nanoparticle film composite layer with a randomly patterned dielectric layer; Step 3: preparing a luminescent quantum dot layer on the dielectric layer, and combining the nanoparticle film, the dielectric layer and the luminescent quantum dot layer to generate a fluorescent composite layer; Step 4: A protective layer is encapsulated on the top of the fluorescent composite layer to form a surface enhanced fluorescent PUF device; Step 5: collecting a fluorescence image of the surface enhanced fluorescence PUF device through a fluorescence microscope; The lifetime image of the surface enhanced fluorescence PUF device is collected by fluorescence lifetime imaging microscopy; Step 6: preprocessing the fluorescence image and lifetime image to obtain an enhanced optical image; Step 7: extracting frequency domain features of the preprocessed enhanced optical image through an image hash algorithm or performing feature detection and feature dimension reduction through a CNN network, and compressing and quantizing the preprocessed enhanced optical image into a binary string of limited length to form a random number key; The step 2 comprises: Step 2.1: Spin-coating a hydroxyl-terminated polystyrene (PS) film with a thickness of 2.9-3 nm on the nanoparticle film to obtain a first nanoparticle film composite layer, wherein the solvent is toluene and the spin-coating concentration is 0.5 wt %; Step 2.2: Spin-coat a layer of poly 2-vinyl pyrrolidone (P2VP) film on the first nanoparticle film composite layer to obtain a second nanoparticle film composite layer, wherein the solvent is chlorobenzene and the spin-coating concentration is 1wt%; Step 2.3: placing the second nanoparticle thin film composite layer in a glove box for thermal annealing at 250° C. for 5 min to generate a nanoparticle thin film composite layer with a randomly patterned dielectric layer; Step 2.4: depositing a 2 nm thick parylene film on the nanoparticle film, and spin coating a 10 nm thick poly 4-vinylpyridine (P4VP) film on the surface of the parylene film; Step 2.5: The nanoparticle film with the parylene film and the poly (4-vinyl pyridine) film was placed in an empty drying oven for thermal annealing at 220 °C for 4 hours to generate a nanoparticle film composite layer with a randomly patterned dielectric layer.

2. A method for generating a random number key based on surface enhanced fluorescence effect according to claim 1, characterized in that: The metal in step 1 includes one of Ag, Au, Cu, Al, Pd or Pt elements.

3. The method for generating a random number key based on surface enhanced fluorescence effect according to claim 1, characterized in that: The step 3 comprises: A 1 mg / mL ZnCdSe@ZnS quantum dot chlorobenzene solution was spin-coated on the surface of the dielectric layer treated by a wet method.

4. The method for generating a random number key based on surface enhanced fluorescence effect according to claim 1, characterized in that: The preprocessing in step 6 includes segmenting, standardizing and enhancing the fluorescence image and the lifetime image: The image is normalized and enhanced using an edge-preserving Gaussian curvature filter; A global search algorithm is used to determine the common threshold of digitization, and a two-value coarse-grained encoding method is used to map each pixel value to the corresponding element of the set {0, 1} to form a black-and-white binary matrix.

5. The method for generating a random number key based on surface enhanced fluorescence effect according to claim 1, characterized in that: The step 7 comprises: Step 7.1: Extract features from the enhanced optical image through the frequency domain transform of the discrete cosine transform in the image hash algorithm, and quantize the numerical value representing the image feature by comparing each coefficient with the average value of the coefficient to form a random number key.

6. The method for generating a random number key based on surface enhanced fluorescence effect according to claim 1, characterized in that: The step 7 comprises: Step 7.2: Train the CNN model based on the AlexNet architecture, input the enhanced optical image output feature layer, activate the generated 4096-dimensional feature vector, and form the random number key.

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