CN116663058A - Nuclear emergency monitoring image searchable encryption retrieval method based on alliance chain - Google Patents
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Abstract
The invention discloses a nuclear emergency monitoring image searchable encryption retrieval method based on a alliance chain, which comprises the following steps: step 1, constructing an image feature vector; step 2, establishing an index; step 3, obtaining a new hash value; step 4, constructing a table by using a multi-bucket strategy; step 5, uploading; step 6, searchable encryption; step 7, exchanging images; step 8, acquiring a digital fingerprint and a fingerprint ID; step 9, watermark embedding; step 10, protecting privacy; step 11, segmentation; step 12, downloading; and step 13, performing responsibility tracking. The method has high security, realizes searchable encryption, has good privacy in the nuclear emergency encryption process, and has high security in the access control process.
Description
Technical Field
The invention relates to the technical field of nuclear emergency images and data security, in particular to a nuclear emergency monitoring image searchable encryption retrieval method based on a alliance chain.
Background
Along with the continuous acceleration of the nuclear power industry in China, the following emergency monitoring level of nuclear accidents is also urgently needed to be improved, and in nuclear emergency monitoring, compared with the situation of reaching the scene, more importantly, the accident cause is rapidly found through big data analysis, so that the scientific application of monitoring images is an effective way for solving the problem. However, the existing nuclear emergency monitoring image is not considered for searching safety in the process of comparison searching, all searching processes cannot be marked, and even if a centralized server is used for management, the risk of tampering exists, so that a set of off-center safety monitoring method is set up for the nuclear emergency monitoring image work with high safety requirements.
Disclosure of Invention
Aiming at the problems of security retrieval and trusted memory of the nuclear emergency monitoring image, the invention provides a nuclear emergency monitoring image searchable encryption retrieval method based on a alliance chain. The method has high security, realizes searchable encryption, has good privacy in the nuclear emergency encryption process, and has high security in the access control process.
The technical scheme for realizing the aim of the invention is as follows:
a nuclear emergency monitoring image searchable encryption retrieval method based on a alliance chain comprises the following steps:
step 1, constructing an image feature vector: inputting an image from a data set, extracting feature vectors of the image by using a deep convolutional neural network, pre-training an image feature vector extraction model by using a resnet 50 to obtain 2048-dimensional feature vectors, and encoding and compressing the feature vectors by using PCA;
step 2, establishing an index: in order to realize the secondary linear search efficiency, the local sensitive hash is improved, a bucket table is constructed for similar feature vectors, and the purpose is to collect similar images into the same bucket table so as to search quickly; in addition, to enhance the accuracy of the locality sensitive hashing, i.e., reduce the false similarity, while similar images are mapped into different bucket tables, by using more locality sensitive hashing functions in one hash table;
step 3, in order to reduce the complexity of the hash table in step 2, the hash values obtained by a plurality of local sensitive hash functions are required to be combined together to obtain a new hash value;
step 4, constructing a table by using a multi-bucket strategy, wherein the feature vector of each image can enter a bucket table pocket similar to the feature vector;
step 5, uploading the encrypted image by the nuclear emergency staff to the alliance chain intelligent contract through the intelligent contract;
step 6, the nuclear emergency staff needing to search the monitoring images searches the images meeting the requirements by submitting a query request and using an intelligent contract, wherein the intelligent contract is a program for executing key steps in a scheme on a blockchain, can help the nuclear emergency staff to complete the whole searching process, comprises storing a search token and an encryption index of the images, performs searchable encryption operation on the intelligent combined date according to the search token, and finally returns a search result to the nuclear emergency staff;
step 7, in an actual application scene, the data sharing can train more diversified models, the safety of the nuclear emergency monitoring image sharing process is considered, after the retrieval step of the step 6, the two sharing parties exchange images, and an image owner firstly invokes a collusion attack resistant code to generate a digital fingerprint;
step 8, the image owner obtains the encrypted digital fingerprint and the ID of the fingerprint from the intelligent contract;
step 9, embedding collusion attack resistant fingerprint codes into the original image by using the exchange password watermark by the image owner to obtain a processed image;
step 10, adopting homomorphic encryption and digital fingerprint to protect privacy of image demander, wherein even if data is shared, the sharing participant cannot know fingerprint information existing in the shared image;
step 11, the image owner uses a Shamir secret sharing scheme to segment the hash value returned by the IPFS, and uploads the segmentation information to the intelligent contract;
step 12, the sharing requester initiates a request for acquiring an image, the image owner sends a public key to the sharing requester through an intelligent contract after requesting, and the sharing requester reconstructs the hash of the IPFS address through intelligent contract and successfully downloads the image required by the sharing requester from the IPFS;
and 13, once the image owner finds that the monitoring image of the image owner is released to the Internet, effective responsibility is pursued through intelligent contracts and information embedded in the image.
Compared with the prior art, the technical scheme has the following characteristics:
1. the technical scheme realizes the safe retrieval of the nuclear emergency monitoring image based on the improved local sensitive hash, and supports the similarity search and updating of the encrypted data. In order to ensure traceability of a security core of retrieval, searchable encryption is realized in a alliance chain intelligent contract, and a retrieval scheme with privacy protection and verifiability is designed.
2. And a data copyright protection model is realized by combining a collusion attack resistant code BIBD and a password exchange watermarking technology. The privacy in the nuclear emergency encryption process is protected through homomorphic encryption optimization symmetric fingerprint scheme, and the right confirmation process is completed through intelligent contracts.
3. According to the technical scheme, the secure access right control is carried out on the storage hash returned by the IPFS by using the secret sharing scheme, and compared with the existing scheme that the direct plaintext or ciphertext storage address hash value is different, the technical scheme can realize a safer access control process.
Drawings
FIG. 1 is a schematic diagram of an embodiment;
fig. 2 is a schematic diagram of download access control in an embodiment.
Detailed Description
The invention will now be described in further detail with reference to the drawings and specific examples, which are not intended to limit the invention thereto.
Examples:
referring to fig. 1 and 2, a nuclear emergency monitoring image searchable encryption retrieval method based on a coalition chain comprises the following steps:
step 1, constructing an image feature vector: inputting an image from a Caltech256 data set containing 256 kinds of objects, namely about 30307 images, extracting feature vectors of the image by using a deep convolutional neural network, pre-training an image feature vector extraction model by using a resnet 50 to obtain 2048-dimensional feature vectors, and encoding and compressing the feature vectors by PCA; firstly, inputting an image, and giving an output of a W X J X M dimensional vector, wherein M is the number of feature mapping of the last layer, the output of a convolution layer consists of an active set, and the feature vector extracted from the image is obtained under the condition of traditional global maximum pooling:
f is the set of feature vectors, f is set to 2048 dimensions, Δ in the training network m Is a feature map of w×j active layers, ρ is an activation function;
step 2, establishing an index: in order to realize the secondary linear search efficiency, the embodiment improves the local sensitive hash, constructs a bucket table for similar feature vectors, and aims to collect as many similar images as possible into the same bucket table so as to search quickly; in addition, to enhance the accuracy of the locality sensitive hashing, i.e., reduce the false similarity (similar images are mapped into different bucket tables), by using more locality sensitive Ha Xiha hash functions in one hash table, all feature vectors extracted for the CNN using the hash function family ψHash to obtain H (f) i )＝(h 1 (f 1 ),h 2 (f 2 ),…,h m (f n ) I.e. k LSH functions are selected from the same local sensitive hash LSH function family, when H k (x)＝H k When the k functions of (y) are all satisfied, H (x) =h (y) is true, in other words, only when the k hash values of the two images correspond to the same socket, the two images are mapped into the same socket, if the hash value does not satisfy 1/k, i.e. the two images will not be projected into the same socket, the operation can improve the p of finding similar images 1 Probability of simultaneously decreasing p 2 Probability (p) 1 And p 2 Included in the locally sensitive hash definition);
step 3, in order to reduce the complexity of the hash table in step 2, the hash values obtained by the plurality of locality sensitive hash functions need to be combined together to obtain a new hash value H (f) i )＝(h 1 (f 1 ),g 2 (f 2 ),…,h m (f n )；
Step 4, constructing a table by using a multi-bucket strategy, wherein the feature vector of each image can enter a bucket table pocket similar to the feature vector, and ALSH represents the final form of the index uploaded to the blockchain by the improved locality sensitive hash:
| Bucket | Index of ALSH |
| bucket1 | ALSH 1 ALSH 5 ALSH 2 … |
| bucket2 | ALSH 3 ALSH 7 … |
| bucket3 | ALSH 4 ALSH 9 … |
| … | … |
| bucket n | ALSH 50 ALSH 6 ALSH 10 … |
；
step 5, the nuclear emergency staff uploads the encrypted image through the intelligent contract to the alliance chain intelligent contract, and the image demander submits keywords to search, and the step e is that G 1 ×G 1 →G 2 As bilinear pair, function H 1 :{0,1} * →G 1 And H 2 :G 2 →{0,1} logp As a hash function, p is the order of the group, and the SSE process on the blockchain is specifically as follows:
Setup(1 λ ) Input of a security parameter lambda, which determines the group G 1 And G 2 Is randomly selected from the order p ofAnd G 1 The generator g of (1), the output pk: = [ g, h=g α ]And sk: =α.
Inputting a public key and an image to be searched by an image demander, and randomly selecting a number +.>Calculate t=e (H 1 (w),h r ) Output c= [ g ] r ,H 2 (t)]I.e. ciphertext and encryption index gamma corresponding to the keywords in the image;
TdGen (sk, w) → (token_qand token_DO); input the private key and image to be retrieved by the image requester, output token=H) 1 (w) α ；
Search (token_q, γ) → (hash, ∈j)) by inputting γ and token, outputting the hash value of the top-k picture stored in IPFS with the highest similarity, if equation H 2 (e (token, γ)) = is true, then the search is successful, and SU can download the corresponding encrypted image ∈from IPFS through hash;
update (token_DO, gamma) to (gamma')) input token DO Gamma, output: gamma ′ The method comprises the steps of carrying out a first treatment on the surface of the Nuclear emergency detection staff sends token DO Adding or deleting intelligent contracts to update the index, and when the index is added, mapping new feature vectors into a bucket table similar to the new feature vectors according to ALSH by a nuclear emergency detection staff;
step 6, the nuclear emergency staff needing to search the monitoring images searches the images meeting the requirements by submitting a query request and using an intelligent contract, wherein the intelligent contract is a program for executing key steps in the example on a blockchain, can help the nuclear emergency staff to complete the whole searching process, comprises storing a search token and an encryption index of the images, performs searchable encryption operation according to the search token, and finally returns a search result to the nuclear emergency staff;
step 7, in an actual application scene, the data sharing can train more diversified models, the security of the nuclear emergency monitoring image sharing process is considered, after the retrieval step of step 6, the two sharing parties exchange images, and an image owner firstly invokes a collusion attack resistant code to generate a digital fingerprint; first, a collusion attack resistant code intelligent contract is called to generate a code word, and the parameters v= 7,k =3 and lambda are given e An example of a symmetric BIBD-ACC (7, 3, 1) correlation matrix of =1, each column of matrix a corresponds to the fingerprint code FP assigned to each user for one image SUi (i=1, 2, …, 7), e.g. user i (i=1, 2, …, 7) purchasing image P i Will pass through SC and FP i Match, then FP i The user name encFP will be used DC Encryption by public key of (a), this example may support a total of n=λ e (v 2 -v)/(k 2 -k)＝1(7 2 -7)/(3 2 -3) =7 users, at most against collusion attacks of k-1=2 users;
step 8, the image owner can obtain the encrypted digital fingerprint and the ID of the fingerprint from the intelligent contract;
step 9, embedding collusion attack resistant fingerprint codes into the original image by using the exchange password watermark by the image owner, and obtaining the processed image:
step 10, the privacy of the image demander is protected by homomorphic encryption and digital fingerprint in this example, so that even if data is shared, the sharing participant cannot know fingerprint information existing in the shared image:
step 11, the image owner uses a Shamir secret sharing scheme to segment the hash value returned by the IPFS, and uploads the segmentation information to the intelligent contract;
step 12, reconstructing hash of the IPFS address through intelligent reduction by the image owners meeting the requirements, and successfully downloading the images required by the image owners from the IPFS;
and 13, once the image owner finds that the monitoring image of the image owner is released to the Internet, effective responsibility can be pursued through intelligent contracts and information embedded in the image.
To illustrate how collusion attack detection is performed, in this example 7 users, the fingerprint code assigned to each user is a column in matrix a, assuming that the fingerprint code extracted from pirated works is P, "1" in P is determined, assuming that user 1 and user 6 have collusion attacks, 1/3/5 and 7 of the column vectors are visible bits according to the principle of embedding assumption, and therefore their codewords are "? "column vectors 2/4/6 are invisible bits, so their codeword is unchanged, the extracted fingerprint is (010), and the whole process can be understood from the following table.
；
The block chain technology is utilized to have the technical characteristics of decentralization, traceability and tamper resistance, particularly, the characteristic that the alliance chain can construct the alliance to realize image sharing retrieval is utilized, and the whole process of searching, encrypting and retrieving aiming at the nuclear emergency monitoring image is realized on the intelligent contract of the alliance chain, namely the chain code. The method is suitable for deep convolutional neural networks to extract image feature vectors, introduces more hash functions into hash families on the basis of traditional local sensitive hashes, improves retrieval accuracy in a union mode, stores improved local sensitive hash indexes on intelligent contracts, and encrypts the indexes by using searchable encryption. Moreover, the method also considers the sharing safety and the right-confirming problem of the nuclear emergency monitoring image, and realizes the copyright protection process by using the same encryption combined with the secret watermark exchange technology, thereby ensuring that the intelligent contract can be utilized to carry out effective responsibility following on the premise of not leaking the right-confirming information.
Claims (1)
1. The nuclear emergency monitoring image searchable encryption retrieval method based on the alliance chain is characterized by comprising the following steps of:
step 1, constructing an image feature vector: inputting an image from a data set, extracting feature vectors of the image by using a deep convolutional neural network, pre-training a feature vector extraction model of the image by using a resnet 50 to obtain 2048-dimensional feature vectors, and encoding and compressing the feature vectors by using PCA;
step 2, establishing an index: in order to realize the secondary linear search efficiency, the local sensitive hash is improved, a bucket table is constructed for similar feature vectors, and the purpose is to collect similar images into the same bucket table so as to search quickly; in addition, to enhance the accuracy of the locality sensitive hashing, i.e., reduce the false similarity, while similar images are mapped into different bucket tables, by using more locality sensitive hashing functions in one hash table;
step 3, in order to reduce the complexity of the hash table in step 2, the hash values obtained by a plurality of local sensitive hash functions are required to be combined together to obtain a new hash value;
step 4, constructing a table by using a multi-bucket strategy, wherein the feature vector of each image can enter a bucket table pocket similar to the feature vector;
step 5, uploading the encrypted image by the nuclear emergency staff to the alliance chain intelligent contract through the intelligent contract;
step 6, the nuclear emergency staff needing to search the monitoring images searches the images meeting the requirements by using the intelligent contract by submitting the query request, the intelligent combined date performs the searchable encryption operation according to the search token, and finally the search result is returned to the nuclear emergency staff;
step 7, in an actual application scene, the data sharing can train more diversified models, the safety of the nuclear emergency monitoring image sharing process is considered, after the retrieval step of the step 6, the two sharing parties exchange images, and an image owner firstly invokes a collusion attack resistant code to generate a digital fingerprint;
step 8, the image owner obtains the encrypted digital fingerprint and the ID of the fingerprint from the intelligent contract;
step 9, embedding collusion attack resistant fingerprint codes into the original image by using the exchange password watermark by the image owner to obtain a processed image;
step 10, adopting homomorphic encryption and digital fingerprint to protect privacy of image demander, wherein even if data is shared, the sharing participant cannot know fingerprint information existing in the shared image;
step 11, the image owner uses a Shamir secret sharing scheme to segment the hash value returned by the IPFS, and uploads the segmentation information to the intelligent contract;
step 12, the sharing requester initiates a request for acquiring an image, the image owner sends a public key to the sharing requester through an intelligent contract after requesting, and the sharing requester reconstructs the hash of the IPFS address through intelligent contract and successfully downloads the image required by the sharing requester from the IPFS;
and 13, once the image owner finds that the monitoring image of the image owner is released to the Internet, effective responsibility is pursued through intelligent contracts and information embedded in the image.
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| CN117113385A (en) * | 2023-10-25 | 2023-11-24 | 成都乐超人科技有限公司 | Data extraction method and system applied to user information encryption |
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| CN117113385A (en) * | 2023-10-25 | 2023-11-24 | 成都乐超人科技有限公司 | Data extraction method and system applied to user information encryption |
| CN117113385B (en) * | 2023-10-25 | 2024-03-01 | 成都乐超人科技有限公司 | Data extraction method and system applied to user information encryption |
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