Robustness improvement method based on optical PUF authentication and related device

Abstract

The invention discloses a robustness improvement method based on optical PUF authentication and a related device, and the method comprises the steps: determining a matched feature point set between a first response speckle and a standard speckle based on a feature point matching algorithm, and obtaining a first coordinate value set of the feature point set in the first response speckle, obtaining a second coordinate value group of the feature point set in the standard speckle; determining a displacement mean value according to the first coordinate value group and the second coordinate value group; translating all pixel points in the first response speckle to the target coordinate point according to the displacement mean value to obtain a second response speckle; the second response speckle and the first response speckle have an overlapping region; and performing authentication based on the picture with the second response speckle located in the overlapping region and the picture with the standard speckle located in the corresponding region. The offset degree of the response speckle is determined by calculating the displacement mean value, then the response speckle is corrected, and then user identification is performed based on the corrected response speckle and the standard speckle, so that the robustness of user identification can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of optical PUF authentication, and particularly to a method for improving the robustness of optical PUF authentication, a device for improving the robustness of optical PUF authentication, a device for improving the robustness of optical PUF authentication, and a computer-readable storage medium. Background Art

[0002] Authentication systems based on optical Physical Unclonable Functions (PUFs) have received extensive attention in the field of hardware security. However, due to factors such as unstable authentication systems and repeated plugging and unplugging of PUFs by users, positioning device failures often occur, and the obtained authentication speckle patterns are likely to deviate. Eventually, legitimate users are rejected by the system. However, traditional speckle comparison methods cannot effectively solve the problem of authentication speckle pattern deviation, thus reducing the usability and robustness of the optical PUF authentication system. Therefore, how to provide an effective method to improve the robustness of the optical PUF authentication system is an urgent problem for those skilled in the art. Summary of the Invention

[0003] The object of the present invention is to provide a method for improving the robustness of optical PUF authentication, which has higher stability and robustness; another object of the present invention is to provide a device for improving the robustness of optical PUF authentication, a device for improving the robustness of optical PUF authentication, and a computer-readable storage medium, which have higher stability and robustness.

[0004] To solve the above technical problems, the present invention provides a method for improving the robustness of optical PUF authentication, including:

[0005] Obtaining a first response speckle pattern; the first response speckle pattern is a speckle image obtained by irradiating a user PUF with an excitation code, and the excitation code also corresponds to a standard speckle pattern;

[0006] Based on a feature point matching algorithm, determining a set of feature points that match between the first response speckle pattern and the standard speckle pattern, obtaining a first coordinate value group of the set of feature points in the first response speckle pattern, and a second coordinate value group of the set of feature points in the standard speckle pattern;

[0007] Determining a displacement mean value according to the first coordinate value group and the second coordinate value group;

[0008] Translating all pixel points in the first response speckle pattern to target coordinate points according to the displacement mean value to obtain a second response speckle pattern; the second response speckle pattern and the first response speckle pattern have an overlapping area;

[0009] Authenticate the image where the second response speckle is located in the overlapping area and the image where the standard speckle is located in the corresponding area to identify the user.

[0010] Optionally, determining the set of feature points that match each other between the first response speckle and the standard speckle based on the feature point matching algorithm includes:

[0011] Detect the set of feature points of the first response speckle and the set of feature points of the standard speckle based on the feature point matching algorithm;

[0012] Extract the set of feature points detected in the first response speckle and the set of feature points detected in the standard speckle;

[0013] Match the set of feature points extracted from the first response speckle with the set of feature points extracted from the standard speckle, and screen out the set of feature points that match each other.

[0014] Optionally, determining the displacement mean value according to the first coordinate value group and the second coordinate value group includes:

[0015] Determine the horizontal coordinate displacement mean value and the vertical coordinate displacement mean value according to the first coordinate value group and the second coordinate value group;

[0016] Translating all pixel points in the first response speckle to the target coordinate points according to the displacement mean value includes:

[0017] Translate all pixel points in the first response speckle to the target coordinate points according to the horizontal coordinate displacement mean value and the vertical coordinate displacement mean value.

[0018] Optionally, translating all pixel points in the first response speckle to the target coordinate points according to the displacement mean value to obtain the second response speckle includes:

[0019] Generate a blank image of the same size as the first response speckle; the pixel value of the pixel points in the blank image is 0;

[0020] Determine the target coordinate values corresponding to each pixel point in the first response speckle according to the displacement mean value and the current coordinate values of each pixel point in the first response speckle;

[0021] Fill the pixel values of each pixel point in the first response speckle into the pixel points with the corresponding target coordinate values in the blank image to obtain the second response speckle.

[0022] Optionally, authenticating based on the image where the second response speckle is located in the overlapping area and the image where the standard speckle is located in the corresponding area includes:

[0023] Crop the second response speckle and the standard speckle based on the displacement mean value to obtain a final response speckle that does not exceed the overlapping area, and a final standard speckle whose position corresponds to the final response speckle;

[0024] Perform authentication according to the final response speckle and the final standard speckle.

[0025] Optionally, performing authentication according to the final response speckle and the final standard speckle includes:

[0026] Based on an image filtering algorithm, determine a first binary texture feature image corresponding to the final response speckle, and a second binary texture feature image corresponding to the final standard speckle;

[0027] Determine the consistency parameter between the first binary texture feature image and the second binary texture feature image;

[0028] Determine whether the user authentication passes according to the consistency parameter.

[0029] Optionally, the activation code is a randomly selected activation code.

[0030] The present invention also provides a device for enhancing the robustness of optical PUF authentication, including:

[0031] An acquisition module for acquiring a first response speckle; the first response speckle is a speckle image obtained by irradiating a user PUF with an activation code, and the activation code also corresponds to a standard speckle;

[0032] A feature point module for determining a set of feature points that match each other between the first response speckle and the standard speckle based on a feature point matching algorithm, acquiring a first coordinate value group of the set of feature points in the first response speckle, and a second coordinate value group of the set of feature points in the standard speckle;

[0033] A displacement mean value module for determining the displacement mean value according to the first coordinate value group and the second coordinate value group;

[0034] A correction module for translating all pixel points in the first response speckle to target coordinate points according to the displacement mean value to obtain a second response speckle; the second response speckle and the first response speckle have an overlapping area;

[0035] An authentication module for performing authentication based on the image of the second response speckle in the overlapping area and the image of the standard speckle in the corresponding area to enhance the robustness of user identification based on optical PUF authentication.

[0036] The present invention also provides a device for enhancing the robustness of optical PUF authentication, and the device includes:

[0037] Memory: for storing computer programs;

[0038] Processor: for implementing the steps of the method for enhancing the robustness based on optical PUF authentication as described in any one of the above when executing the computer program.

[0039] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method for enhancing the robustness based on optical PUF authentication as described in any one of the above are implemented.

[0040] A method for enhancing the robustness based on optical PUF authentication provided by the present invention includes: obtaining a first response speckle; the first response speckle is a speckle image obtained by irradiating a user PUF with an excitation code, and the excitation code also corresponds to a standard speckle; determining a set of feature points that match each other between the first response speckle and the standard speckle based on a feature point matching algorithm, obtaining a first coordinate value group of the feature points in the first response speckle, and a second coordinate value group of the feature points in the standard speckle; determining a displacement mean value according to the first coordinate value group and the second coordinate value group; translating all pixel points in the first response speckle to target coordinate points according to the displacement mean value to obtain a second response speckle; the second response speckle and the first response speckle have an overlapping area; performing authentication based on the picture of the second response speckle located in the overlapping area and the picture of the standard speckle located in the corresponding area to identify the user.

[0041] Through feature point matching, the corresponding positions between the response speckle and the standard speckle can be determined, and the offset degree of the response speckle can be determined by calculating the displacement mean value. After that, the response speckle is corrected first, and then user identification is performed based on the corrected response speckle and the standard speckle, which can greatly improve the robustness of user identification.

[0042] The present invention also provides a device for enhancing the robustness based on optical PUF authentication, a device for enhancing the robustness based on optical PUF authentication, and a computer-readable storage medium, which also have the above beneficial effects and will not be elaborated here. Description of the Drawings

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0044] Figure 1 It is a flowchart of a method for enhancing the robustness based on optical PUF authentication provided by an embodiment of the present invention;

[0045] Figure 2 Flow chart of a specific method for enhancing the robustness of optical PUF authentication provided by an embodiment of the present invention;

[0046] Figure 3 Schematic diagram of the generation of the second response speckle;

[0047] Figure 4 Structural block diagram of a device for enhancing the robustness of optical PUF authentication provided by an embodiment of the present invention;

[0048] Figure 5 Structural block diagram of a device for enhancing the robustness of optical PUF authentication provided by an embodiment of the present invention. Detailed implementation manners

[0049] The core of the present invention is to provide a method for enhancing the robustness of optical PUF authentication. In the prior art, traditional solutions usually rely on simple measurement methods to compare user speckles, and cannot effectively solve the problem of the offset of the authentication speckles, thereby reducing the stability and robustness of the optical PUF authentication system.

[0050] A method for enhancing the robustness of optical PUF authentication provided by the present invention includes: obtaining a first response speckle; the first response speckle is a speckle image obtained by irradiating a user PUF with an excitation code, and the excitation code also corresponds to a standard speckle; determining a set of feature points that match each other between the first response speckle and the standard speckle based on a feature point matching algorithm, obtaining a first coordinate value group of the feature points in the first response speckle, and a second coordinate value group of the feature points in the standard speckle; determining a displacement mean value according to the first coordinate value group and the second coordinate value group; translating all pixel points in the first response speckle to target coordinate points according to the displacement mean value to obtain a second response speckle; the second response speckle and the first response speckle have an overlapping area; authenticating based on the picture of the second response speckle located in the overlapping area and the picture of the standard speckle located in the corresponding area to identify the user.

[0051] Enhancing the robustness of optical PUF authentication can determine the corresponding positions between the response speckle and the standard speckle through feature point matching, and determine the offset degree of the response speckle by calculating the displacement mean value. After correcting the response speckle first and then performing user identification based on the corrected response speckle and the standard speckle, the robustness of user identification can be greatly improved.

[0052] To enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0053] Embodiment 1

[0054] Please refer to Figure 1 , Figure 1 which is a flowchart of a method for improving the robustness of optical PUF authentication provided by an embodiment of the present invention.

[0055] See Figure 1 , in the embodiment of the present invention, the method for improving the robustness of optical PUF authentication includes:

[0056] S101: Obtain the first response speckle.

[0057] In this embodiment, the first response speckle is a speckle image obtained by irradiating the user's PUF with an excitation code, and the excitation code also corresponds to a standard speckle. The PUF of the above user is usually a device with a fixed entity, which may have a structure similar to a card or any other structure, and is not specifically limited herein. The above excitation code (challenge) refers to a specific optical signal incident on the optical PUF. This optical signal is usually emitted by a light source and undergoes a certain modulation or coding. Irradiating the encoded light onto the PUF key will generate a speckle response. Different excitation codes, that is, different encoded optical signals irradiating the PUF will obtain different speckle responses. In this embodiment, the specific modulation content of the excitation code is not specifically limited and depends on the specific situation. The excitation code used in this embodiment can be a randomly selected excitation code to ensure the accuracy of authentication. The random algorithm used in this random selection process can be determined according to the actual situation and is not specifically limited herein.

[0058] The above excitation code is a pre-set specific optical signal used to stimulate the user's PUF to generate a speckle image, and the excitation code also corresponds to a standard speckle. The standard speckle is a speckle image obtained by irradiating the user's PUF with the same excitation code under ideal conditions or pre-set conditions, and can be used as a reference benchmark in the subsequent authentication process.

[0059] In this step, specifically, the speckle image generated after irradiating the user's PUF with the excitation code, that is, the first response speckle, will be obtained. This acquisition process can be set according to the actual situation and is not specifically limited herein. In this embodiment, the response speckle generated based on the inserted PUF is usually obtained after the user inserts the PUF.

[0060] For example, in a specific application scenario, the user's PUF can be a card with specific optical properties. When a laser with a specific wavelength and intensity is used as the excitation code to irradiate the card, due to the non-uniformity of the internal microstructure of the card, a unique speckle image will be generated, which is the first response speckle. At the same time, during the system initialization phase, the same excitation code has been used to irradiate the card, and the generated standard speckle has been recorded for comparison during the subsequent authentication process.

[0061] S102: Determine the set of feature points that match each other between the first response speckle and the standard speckle based on the feature point matching algorithm, and obtain the first coordinate value group of the feature point set in the first response speckle and the second coordinate value group of the feature point set in the standard speckle.

[0062] In this step, first, the feature points that match each other between the first response speckle and the standard speckle are determined based on the feature point matching algorithm. Usually, multiple sets of matching feature points are determined at this time, thus forming a set of feature points, and this set of feature points includes multiple feature points; then, the coordinate values of each feature point in its respective speckle image are determined, thus forming the corresponding coordinate value group, and this coordinate value group usually includes multiple coordinate values. Of course, for the first response speckle and the standard speckle, the coordinate system needs to be established according to the same standard. For example, the xy coordinate system is established with the first pixel point in the lower left corner as the origin, etc., which will not be specifically limited here.

[0063] The feature point matching algorithm usually includes at least three processes. The first process is to detect the feature points in the image, the second process is to extract the descriptors of each feature point, and the third process is to perform the matching between two sets of feature points based on the descriptors. When performing feature point detection, usually, the feature point detection algorithm is used to detect the feature points of the first response speckle and the standard speckle respectively, and the detected feature points are usually described as a feature vector or descriptor (descriptor). Feature points represent the key information in the image, and they usually have invariance to rotation, scale, and illumination changes, so that they can be accurately detected at different positions and angles of the image. Common feature point detection algorithms include the Harris corner detection algorithm, the FAST (Features from Accelerated Segment Test) algorithm, etc., and the appropriate algorithm can be selected according to the actual application requirements and the characteristics of the speckle image (such as noise type, perspective change, etc.).

[0064] After feature point detection and descriptor extraction, a set of feature points of the first response speckle and a set of feature points of the standard speckle are usually obtained. When performing feature point matching, the similarity between feature point descriptors is calculated to find similar feature point pairs in two images. That is, similar feature points are found from the two sets of feature points to form feature point pairs, and the two feature points constituting the feature point pair are the mutually matching feature points in the first response speckle and the standard speckle.

[0065] After that, in this step, it is also necessary to record the coordinates of the mutually matching feature points in their respective speckle images. Denote the coordinate values of the above-mentioned feature points in the first response speckle as the first coordinate values to form a first coordinate value group; each first coordinate value in this first coordinate value group can represent the position of each feature point in the feature point set in the first response speckle; denote the coordinate values of the above-mentioned feature points in the standard speckle as the second coordinate values to form a second coordinate value group; each second coordinate value in this second coordinate value group can represent the position of each feature point in the feature point set in the standard speckle. For example, assume that a feature point is detected and matched in the first response speckle, and its coordinate value is (100, 200), while the coordinate value of the corresponding matching feature point in the standard speckle is (95, 195).

[0066] S103: Determine the displacement mean value according to the first coordinate value group and the second coordinate value group.

[0067] The above displacement mean value is the value determined by taking the mean after the coordinate values of the mutually matching feature point pairs are subtracted in their respective images, which characterizes the overall offset degree of the first response speckle relative to the standard speckle. In this step, the displacement value corresponding to each feature point is calculated according to each first coordinate value in the first coordinate value group obtained above and the second coordinate value corresponding to the mutually matching feature point in the second coordinate value group, and finally the displacement mean value is calculated according to multiple displacement values. Specifically, for each group of mutually matching feature point pairs, the difference between its coordinate value in the first response speckle and its coordinate value in the standard speckle can be calculated, that is, the displacement vector. Taking the xy coordinate system as an example, the displacement vector can be expressed as (Δx, Δy), where Δx is the displacement difference in the horizontal coordinate direction and Δy is the displacement difference in the vertical coordinate direction.

[0068] Then, the displacement vectors of all mutually matching feature points are averaged to obtain the displacement mean value. The displacement mean value reflects the overall offset degree of the first response speckle relative to the standard speckle, and in the xy coordinate system, it usually includes the average offset amounts in the horizontal coordinate direction and the vertical coordinate direction.

[0069] For example, assume that there are two groups of mutually matching feature point pairs. The displacement vector of the first group of feature point pairs is (5, 3), and the displacement vector of the second group of feature point pairs is (3, 5). Then the displacement mean value is ((5 + 3) / 2, (3 + 5) / 2), that is, (4, 4).

[0070] S104: Translate all pixel points in the first response speckle to the target coordinate points according to the displacement mean value to obtain the second response speckle.

[0071] In this embodiment, the second response speckle and the first response speckle have an overlapping area. The essence of this step is to correct the first response speckle. Therefore, in this step, each pixel point in the first response speckle will be translated from the current coordinate point to the target coordinate point according to the above displacement mean value, or in other words, the pixel value of the target coordinate point will be replaced with the pixel value corresponding to the current coordinate point, so as to obtain the second response speckle. Obviously, in this embodiment, the second response speckle and the first response speckle usually share the coordinate system. The image of the second response speckle is similar to that of the first response speckle but is translated as a whole. After translation in this embodiment, the second response speckle and the first response speckle have overlapping and non-overlapping areas in terms of coordinates.

[0072] For example, assume that there is a pixel point in the first response speckle, its coordinate is (150, 250), its pixel value is 128, and the displacement mean value is (4, 4). Then the target coordinate value of this pixel point can be (150 + 4, 250 + 4), that is, (154, 254). Correspondingly, the pixel value of the pixel point located at (154, 254) in the second response speckle is 128. This step performs translational correction on the first response speckle, making the image features of the second response speckle and the standard speckle more consistent within the overlapping area, which is beneficial to improving the robustness of the subsequent authentication process.

[0073] S105: Perform authentication based on the picture of the second response speckle located in the overlapping area and the picture of the standard speckle located in the corresponding area to identify the user.

[0074] The picture of the standard speckle located in the corresponding area has the same coordinates as the picture of the second response speckle located in the overlapping area. That is, in this step, the picture of the second response speckle located in the above overlapping area will be used for authentication with the part of the picture of the standard speckle that has the same coordinates as the above overlapping area to identify the user. The specific process of authentication will be introduced in detail in the following embodiments of the invention and will not be elaborated here.

[0075] A method for improving the robustness of optical PUF authentication provided by the embodiment of the present invention can determine the corresponding positions between the response speckle and the standard speckle through feature point matching, and determine the offset degree of the response speckle by calculating the displacement mean value. Then, the response speckle is corrected first, and then user identification is performed based on the corrected response speckle and the standard speckle, which can greatly improve the robustness of user identification.

[0076] The specific content of a method for enhancing the robustness of optical PUF authentication provided by the present invention will be described in detail in the following invention embodiments, and will not be elaborated here.

[0077] Embodiment 2

[0078] Please refer to Figure 2 and Figure 3 , Figure 2 which is a flowchart of a specific method for enhancing the robustness of optical PUF authentication provided by the embodiments of the present invention; Figure 3 is a schematic diagram of the generation principle of the second response speckle.

[0079] See Figure 2 , in the embodiments of the present invention, the method for enhancing the robustness of optical PUF authentication includes:

[0080] S201: Obtain the first response speckle.

[0081] This step is basically the same as S101 in the above embodiment. For the detailed content, please refer to the above embodiment and will not be elaborated here.

[0082] S202: Detect the feature point sets of the first response speckle and the standard speckle based on the feature point matching algorithm.

[0083] In this step, all the feature points of the first response speckle will be specifically detected to form a feature point set, and all the feature points of the standard speckle will be detected to form a feature point set.

[0084] S203: Extract the feature point set detected in the first response speckle and the feature point set detected in the standard speckle.

[0085] In this step, the descriptors corresponding to each feature point in the feature point set detected in the first response speckle will be extracted, and the descriptors corresponding to each feature point in the feature point set detected in the standard speckle will be extracted.

[0086] S204: Match the feature point set extracted from the first response speckle with the feature point set extracted from the standard speckle, and screen out the mutually matching feature point sets.

[0087] The specific content of the above feature point matching algorithm can be set according to the actual situation and is not specifically limited here. In this step, each feature point in the two extracted feature point sets will be matched. For example, by comparing the descriptors of the feature points extracted from different speckle images, the mutually matching feature points in the two sets of feature points will be screened out to form a mutually matching feature point set.

[0088] After this step, it is necessary to record the coordinates of the mutually matching feature points in their respective speckle images. The specific content has been introduced in detail in the above embodiments and will not be elaborated here. In this embodiment, it is assumed that the set of feature points in the first response speckle is R, and the set of feature points R includes each feature point R 1 , R 2 ... R k . Then, the first coordinate values of each feature point in the set of feature points R are respectively recorded as (M 1 , N 1 ), (M 2 , N 2 )... (M k , N k ), forming a first coordinate value group; it is assumed that the set of feature points in the standard speckle is S, and the set of feature points S includes each feature point S 1 , S 2 ... S k . Then, the second coordinate values of each feature point in the set of feature points S are respectively recorded as (P 1 , Q 1 ), (P 2 , Q 2 )... (P k , Q k ), forming a second coordinate value group.

[0089] S205: Determine the average horizontal displacement and the average vertical displacement according to the first coordinate value group and the second coordinate value group.

[0090] In this step, the average horizontal displacement m1 of each feature point in the set of feature points R relative to each feature point in the set of feature points S, and the average vertical displacement m2 will be calculated, where:

[0091] m1 = [(P 1 - M 1 ) + (P 2 - M 2 ) + (P 3 - M 3 ) +...... + (P k - M k )] / k;

[0092] m2 = [(Q 1 - N 1 ) + (Q 2 - N 2 ) + (Q 3 - N 3 ) +...... + (Q k - N k )] / k.

[0093] See Figure 3, correspondingly, in subsequent steps, all pixel points in the first response speckle are translated to target coordinate points according to the abscissa displacement mean value and the ordinate displacement mean value to form a second response speckle. For example, for the pixel point (i, j) in the first response speckle, its corresponding target coordinate point is (i + m1, j + m2), that is, the pixel value of the pixel point (i, j) in the first response speckle is the same as the pixel value of the pixel point (i + m1, j + m2) in the second response speckle.

[0094] S206: Generate a blank picture with the same size as the first response speckle.

[0095] In this embodiment, the pixel value of the pixel point in the blank picture is 0. That is, in this step, a picture with all pixel points being 0 will be generated first, and the size of this blank picture is usually the same as that of the first response speckle.

[0096] S207: Determine the target coordinate values corresponding to all pixel points in the first response speckle according to the displacement mean value and the current coordinate values of each pixel point in the first response speckle.

[0097] In this step, the displacement mean value calculated in the above step is added to the current coordinate values of each pixel point in the first response speckle to obtain the target coordinate values corresponding to each pixel point. For example, for the pixel point (i, j) in the first response speckle, its corresponding target coordinate point is (i + m1, j + m2).

[0098] S208: Fill the pixel values of all pixel points in the first response speckle into the pixel points with corresponding target coordinate values in the blank picture to obtain a second response speckle.

[0099] See Figure 3 , in this step, the pixel value V of the pixel point (i, j) in the first response speckle ij is filled into the pixel point (i + m1, j + m2) in the blank picture, that is, the pixel value of the pixel point (i + m1, j + m2) in the blank picture is also V ij , thereby obtaining a second response speckle.

[0100] S209: Crop the second response speckle and the standard speckle based on the displacement mean value to obtain a final response speckle that does not exceed the overlapping area, and a final standard speckle whose position corresponds to the final response speckle.

[0101] See Figure 3, in this step, the second response speckle and the standard speckle are cropped. When cropping, the above displacement mean value needs to be specifically referred to. When the first response speckle is translated to obtain the second response speckle, there is usually an overlapping area between the first response speckle and the second response speckle in the same coordinate system. In this step, the second response speckle needs to be cropped so that the coordinates corresponding to each pixel point in the final response speckle do not exceed the range of the above overlapping area. For example, when cropping the second response speckle, only the pixel area with the abscissa range of (1 + m1, i - m1) and the ordinate range of (1 + m2, j - m2) is retained. This pixel area does not exceed the above overlapping area, so that the cropped final response speckle does not exceed the above overlapping area. Correspondingly, in this step, the standard speckle also needs to be cropped to obtain the final standard speckle. The pixel area corresponding to the final standard speckle needs to correspond to the pixel area of the final response speckle. Therefore, when cropping, only the pixel area with the abscissa range of (1 + m1, i - m1) and the ordinate range of (1 + m2, j - m2) can be retained to obtain the final standard speckle. Of course, in this embodiment, the cropped area is not specifically limited. For example, it can be further reduced based on the above coordinate range, which is not specifically limited here. Correspondingly, in the subsequent steps, authentication needs to be performed according to the final response speckle and the final standard speckle.

[0102] S210: Based on the image filtering algorithm, determine the first binary texture feature picture corresponding to the final response speckle and the second binary texture feature picture corresponding to the final standard speckle.

[0103] In this step, image filtering algorithms such as the Gabor filtering algorithm can be used to process the above two speckle images. The specific content of image filtering algorithms such as the Gabor filtering algorithm can refer to the prior art and will not be elaborated here. In this step, the Gabor filtering algorithm can be used to process the final response speckle and the final standard speckle respectively, so as to obtain the first binary texture feature picture corresponding to the final response speckle and the second binary texture feature picture corresponding to the final standard speckle.

[0104] S211: Determine the consistency parameter between the first binary texture feature picture and the second binary texture feature picture.

[0105] In this step, the consistency parameter of the above two binary texture feature pictures can be determined. This consistency parameter is used to characterize the degree of consistency or similarity of the above two binary texture feature pictures. The first parameter can be the Pearson correlation coefficient or the Hamming distance, etc. The specific calculation process of the Hamming distance or the Pearson correlation coefficient can refer to the prior art and will not be elaborated here. This consistency parameter can characterize the degree of difference between the first binary texture feature picture and the second binary texture feature picture.

[0106] S212: Determine whether the user authentication passes according to the consistency parameter.

[0107] Taking the Hamming distance as an example, the smaller the Hamming distance, the higher the similarity between the two images. In this step, when the Hamming distance is less than the target threshold, it means that there is a high similarity between the first response speckle and the standard speckle, and correspondingly, it can be determined that the user authentication passes at this time. On the contrary, when the Hamming distance is greater than or equal to the target threshold, it means that there is a large difference between the first response speckle and the standard speckle, and correspondingly, it can be determined that the user authentication fails at this time. Taking the Pearson correlation coefficient as an example, the larger the Pearson correlation coefficient, the higher the similarity between the two images. In this step, when the Pearson correlation coefficient is greater than the target threshold, it means that there is a high similarity between the first response speckle and the standard speckle, and correspondingly, it can be determined that the user authentication passes at this time. On the contrary, when the Pearson correlation coefficient is less than or equal to the target threshold, it means that there is a large difference between the first response speckle and the standard speckle, and correspondingly, it can be determined that the user authentication fails at this time.

[0108] The above target threshold needs to be determined according to the type of the consistency parameter. For example, corresponding to the Hamming distance, the target threshold can be 0.3; corresponding to the Pearson correlation coefficient, the target threshold can be 0.7. The specific value of the above target threshold can be set according to the actual situation and will not be specifically limited here.

[0109] A method for improving the robustness of optical PUF authentication provided by an embodiment of the present invention can effectively solve the problem of authentication speckle offset caused by factors such as unstable authentication systems and repeated plugging and unplugging of PUFs by users during the optical PUF authentication process, improve the stability and robustness of the optical PUF authentication system, ensure that legitimate users can pass the authentication smoothly, prevent illegal access by illegal users at the same time, and enhance the security of the system.

[0110] Embodiment III

[0111] Next, a device for improving the robustness of optical PUF authentication provided by an embodiment of the present invention will be introduced. The device for improving the robustness of optical PUF authentication described below can be correspondingly referred to the method for improving the robustness of optical PUF authentication described above.

[0112] Please refer to Figure 4 , Figure 4 which is a structural block diagram of a device for improving the robustness of optical PUF authentication provided by an embodiment of the present invention.

[0113] See Figure 4 , in an embodiment of the present invention, the device for improving the robustness of optical PUF authentication may include:

[0114] An acquisition module 100 for acquiring a first response speckle; the first response speckle is a speckle image obtained by irradiating a user PUF with an excitation code, and the excitation code also corresponds to a standard speckle;

[0115] A feature point module 200 for determining a set of feature points that match each other between the first response speckle and the standard speckle based on a feature point matching algorithm, obtaining a first coordinate value group of the set of feature points in the first response speckle, and a second coordinate value group of the set of feature points in the standard speckle;

[0116] A displacement mean module 300 for determining a displacement mean according to the first coordinate value group and the second coordinate value group;

[0117] A correction module 400 for translating all pixel points in the first response speckle to target coordinate points according to the displacement mean to obtain a second response speckle; the second response speckle and the first response speckle have an overlapping area;

[0118] An authentication module 500 for authenticating based on the picture of the second response speckle located in the overlapping area and the picture of the standard speckle located in the corresponding area to identify the user.

[0119] Preferably, in an embodiment of the present invention, the feature point module 200 includes:

[0120] A detection unit for detecting a set of feature points of the first response speckle and a set of feature points of the standard speckle based on a feature point matching algorithm;

[0121] An extraction unit for extracting the set of feature points detected in the first response speckle and extracting the set of feature points detected in the standard speckle;

[0122] A matching unit for matching the set of feature points extracted from the first response speckle with the set of feature points extracted from the standard speckle, and screening out the set of feature points that match each other.

[0123] Preferably, in an embodiment of the present invention, the displacement mean module 300 is specifically configured to:

[0124] Determine a horizontal displacement mean and a vertical displacement mean according to the first coordinate value group and the second coordinate value group;

[0125] The correction module 400 is specifically configured to:

[0126] Translate all pixel points in the first response speckle to target coordinate points according to the horizontal displacement mean and the vertical displacement mean.

[0127] Preferably, in an embodiment of the present invention, the correction module 400 includes:

[0128] A blank image unit for generating a blank image of the same size as the first response speckle; the pixel value of each pixel point in the blank image is 0;

[0129] A target coordinate value unit for determining the target coordinate value corresponding to each pixel point in the first response speckle according to the displacement mean value and the current coordinate value of each pixel point in the first response speckle;

[0130] A filling unit for filling the pixel value of each pixel point in the first response speckle into the pixel point corresponding to the target coordinate value in the blank image to obtain a second response speckle.

[0131] Preferably, in the embodiment of the present invention, the authentication module 500 includes:

[0132] A cropping unit for cropping the second response speckle and the standard speckle based on the displacement mean value to obtain a final response speckle that does not exceed the overlapping area, and a final standard speckle whose position corresponds to the final response speckle;

[0133] An authentication unit for performing authentication according to the final response speckle and the final standard speckle.

[0134] Preferably, in the embodiment of the present invention, the authentication unit includes:

[0135] A filtering sub-unit for determining a first binary texture feature image corresponding to the final response speckle and a second binary texture feature image corresponding to the final standard speckle based on an image filtering algorithm;

[0136] A consistency parameter sub-unit for determining the consistency parameter between the first binary texture feature image and the second binary texture feature image;

[0137] An authentication sub-unit for determining whether user authentication is passed according to the consistency parameter.

[0138] Preferably, in the embodiment of the present invention, the excitation code is a randomly selected excitation code.

[0139] The robustness improvement device based on optical PUF authentication in this embodiment is used to implement the aforementioned robustness improvement method based on optical PUF authentication. Therefore, the specific implementation manners in the robustness improvement device based on optical PUF authentication can be seen in the embodiment part of the robustness improvement method based on optical PUF authentication in the previous text. For example, the acquisition module 100, the feature point module 200, the displacement mean module 300, the correction module 400, and the authentication module 500 are respectively used to implement steps S101 to S105 in the aforementioned robustness improvement method based on optical PUF authentication. Therefore, the specific implementation manners can refer to the descriptions of the corresponding individual part embodiments and will not be elaborated here.

[0140] Embodiment 4

[0141] Next, a robustness improvement device based on optical PUF authentication provided by an embodiment of the present invention will be introduced. The robustness improvement device based on optical PUF authentication described below can be correspondingly referred to the robustness improvement method based on optical PUF authentication and the robustness improvement device based on optical PUF authentication described above.

[0142] Please refer to Figure 5 , Figure 5 , which is a structural block diagram of a robustness improvement device based on optical PUF authentication provided by an embodiment of the present invention.

[0143] Referring to Figure 5 , the robustness improvement device based on optical PUF authentication may include a processor 11 and a memory 12.

[0144] The memory 12 is used to store a computer program; the processor 11 is used to implement the robustness improvement method based on optical PUF authentication described in the above-mentioned embodiment of the invention when executing the computer program.

[0145] In the robustness improvement device based on optical PUF authentication in this embodiment, the processor 11 is used to install the robustness improvement device based on optical PUF authentication described in the above-mentioned embodiment of the invention. At the same time, the combination of the processor 11 and the memory 12 can implement the robustness improvement method based on optical PUF authentication described in any of the above-mentioned embodiments of the invention. Therefore, the specific implementation manners in the robustness improvement device based on optical PUF authentication can be seen in the embodiment part of the robustness improvement method based on optical PUF authentication in the previous text. The specific implementation manners can refer to the descriptions of the corresponding individual part embodiments and will not be elaborated here.

[0146] Embodiment 5

[0147] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a method for enhancing the robustness of optical PUF authentication introduced in any of the above-described inventive embodiments. The remaining content can be referred to the prior art and will not be elaborated herein.

[0148] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the various embodiments, reference can be made to each other. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple. For the relevant parts, reference can be made to the description in the method section.

[0149] Those skilled in the art can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of the examples have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0150] The steps of the methods or algorithms described in combination with the embodiments disclosed herein can be directly implemented by hardware, software modules executed by a processor, or a combination of the two. The software modules can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0151] Finally, it should also be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0152] The above has introduced in detail a method for enhancing the robustness of optical PUF authentication provided by the present invention and related devices. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

Claims

1. A robustness improvement method based on optical PUF authentication, characterized in that: include: Acquire a first response speckle; the first response speckle is a speckle image obtained by irradiating the user PUF with an excitation code, and the excitation code also corresponds to a standard speckle; Determine a feature point set that matches the first response speckle and the standard speckle based on a feature point matching algorithm, and obtain a first coordinate value group of the feature point set in the first response speckle and a second coordinate value group of the feature point set in the standard speckle; Determine a displacement mean value according to the first coordinate value group and the second coordinate value group; All pixel points in the first response speckle are translated to the target coordinate point according to the displacement mean value to obtain a second response speckle; the second response speckle has an overlapping area with the first response speckle; Authentication is performed based on the picture in which the second response speckle is located in the overlapping area and the picture in which the standard speckle is located in the corresponding area to identify the user.

2. The method according to claim 1, characterized in that Determining a feature point set that matches the first response speckle with the standard speckle based on a feature point matching algorithm includes: Detecting a feature point set of the first response speckle and a feature point set of the standard speckle based on a feature point matching algorithm; extracting a feature point set detected in the first response speckle and extracting a feature point set detected in the standard speckle; The feature point set extracted from the first response speckle is matched with the feature point set extracted from the standard speckle, and mutually matching feature point sets are screened out.

3. The method according to claim 1, characterized in that Determining the displacement mean according to the first coordinate value group and the second coordinate value group comprises: Determine a mean value of abscissa displacement and a mean value of ordinate displacement according to the first coordinate value group and the second coordinate value group; The step of translating all pixel points in the first response speckle to a target coordinate point according to the displacement mean value comprises: All pixel points in the first response speckle are translated to the target coordinate point according to the mean value of the horizontal coordinate displacement and the mean value of the vertical coordinate displacement.

4. The method according to claim 1, characterized in that According to the displacement mean, all pixel points in the first response speckle are translated to the target coordinate point to obtain the second response speckle, which includes: Generate a blank image with the same size as the first response speckle; the pixel value of the pixel point in the blank image is 0; Determine the target coordinate value corresponding to each pixel point in the first response speckle according to the displacement mean and the current coordinate value of each pixel point in the first response speckle; The pixel value of each pixel point in the first response speckle pattern is filled into the pixel point corresponding to the target coordinate value in the blank image to obtain a second response speckle pattern.

5. The method according to claim 1, characterized in that: Authentication based on the picture in which the second response speckle is located in the overlapping area and the picture in which the standard speckle is located in the corresponding area includes: The second response speckle and the standard speckle are clipped based on the displacement mean value to obtain a final response speckle that does not exceed the overlapping area and a final standard speckle whose position corresponds to the final response speckle; Authentication is performed according to the final response speckle and the final standard speckle.

6. The method according to claim 5, characterized in that Authentication according to the final response speckle and the final standard speckle includes: Determine, based on an image filtering algorithm, a first binary texture feature image corresponding to the final response speckle and a second binary texture feature image corresponding to the final standard speckle; Determining a consistency parameter between the first binarized texture feature picture and the second binarized texture feature picture; Determine whether the user authentication is successful based on the consistency parameter.

7. The method according to claim 1, characterized in that The excitation code is a randomly selected excitation code.

8. A robustness improvement device based on optical PUF authentication, characterized in that: include: An acquisition module, used to acquire a first response speckle; the first response speckle is a speckle image obtained by irradiating the user PUF with an excitation code, and the excitation code also corresponds to a standard speckle; a feature point module, configured to determine a feature point set matching between the first response speckle and the standard speckle based on a feature point matching algorithm, and obtain a first coordinate value group of the feature point set in the first response speckle and a second coordinate value group of the feature point set in the standard speckle; A displacement mean module, configured to determine a displacement mean according to the first coordinate value group and the second coordinate value group; a correction module, configured to translate all pixel points in the first response speckle to a target coordinate point according to the displacement mean value, so as to obtain a second response speckle; wherein the second response speckle has an overlapping area with the first response speckle; The authentication module is used to perform authentication based on the picture in which the second response speckle is located in the overlapping area and the picture in which the standard speckle is located in the corresponding area, so as to identify the user.

9. A robustness enhancement device based on optical PUF authentication, characterized in that: The device comprises: Memory: used to store computer programs; Processor: used to implement the steps of the robustness improvement method based on optical PUF authentication as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the robustness improvement method based on optical PUF authentication are implemented as claimed in any one of claims 1 to 7.

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