CN107273467A - A kind of Security Index structure and its building method for supporting to can search for encryption - Google Patents
A kind of Security Index structure and its building method for supporting to can search for encryption Download PDFInfo
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- CN107273467A CN107273467A CN201710418493.4A CN201710418493A CN107273467A CN 107273467 A CN107273467 A CN 107273467A CN 201710418493 A CN201710418493 A CN 201710418493A CN 107273467 A CN107273467 A CN 107273467A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/13—File access structures, e.g. distributed indices
- G06F16/137—Hash-based
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/2107—File encryption
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Abstract
The invention discloses a kind of Security Index structure and its building method for supporting to can search for encryption, the Security Index structure includes four file structures, respectively sys files, bf files, doc files and seg files, four files contain all index informations and document information.The present invention based on trapdoor individual event function and with pseudo-random function be combined construct one have high security cryptograph index structure, the document of encryption is can search for based on the Security Index structure, the present invention meets security and the demand of search efficiency simultaneously, is adapted to can search for encryption and searching ciphertext based on keyword under cloud computing background.
Description
Technical field
The present invention relates to field of computer information security, and in particular to a kind of Security Index structure for supporting to can search for encryption
And its building method.
Background technology
There is the developing history of 50 years or so information retrieval technique to today, method for information retrieval is also from initial letter
Single boolean queries, developed into it is present employ the mathematical modelings such as vector space, probabilistic method, and also introduce weighting
With the concept such as relevance ranking, the appearance of these new technologies significantly improves the quality of information retrieval.Information retrieval technique
Most commonly used undoubtedly search engine is applied to obtain in internet, many outstanding search engines have been generated both at home and abroad public
Department, such as Google, Baidu, Yahoo, they are that people provide great convenience in terms of information retrieval.Search engine is main
It is made up of five parts, is searcher, analyzer, index, searcher and user interface respectively.One can be included in index
Concordance list is used for file retrieval, and the concordance list of current main flow search engine is generally inverted entry in the form of, arranges text
The index structure of shelves has the advantages that efficiency high, accuracy rate are high, occupied little space, thus this be also in current information retrieval the most
A kind of conventional index structure, and be widely used in Internet technology.
The people that develop into of information retrieval technique provide a great convenience, but with the flourishing hair of Internet technology
Exhibition, the security threat that information is subject on network is also in increase, and network security problem becomes increasingly conspicuous.In some scenes, we
For security reasons, it may be necessary to safe handling is first carried out to information and is retrieved again or in transmission over networks, to prevent
The only leakage of information.But the index file of common plaintext retrieval does not carry out any encryption, and all information
All it is to be handled with plaintext version and in transmission over networks, attacker can be very after index file or interception Query Information is obtained
Easily attacked, it is clear that such indexed mode is that can not meet its security requirement under the scene for having demand for security
's.Therefore, we need to carry out a series of security processing to index file and indexed mode in such scene, such as right
Index information is encrypted or changes the modes such as index structure, to cause it to have a certain degree of security, reaches that protection information is pacified
Full purpose.
There are many scholars to propose the scheme and safer index structure of many kinds of encrypted indexes both at home and abroad,
The problem of to solve Security Index, Eu-Jin Goh proposed a kind of Security Index for employing trap door onr way function in 2004
Mechanism, the mechanism is to adapting to Sexual behavior mode keyword attack safety（IND-CKA）, he has constructed a kind of referred to as Z- accordingly
IDX Security Index.Dan Boneh etc. propose it is a kind of support the public key encryption pattern of keyword query, and contain base
In identity ciphering（IBE）Algorithm.But the space-time expense of the above-mentioned Security Index based on trap door onr way function is very big, it is impossible to suitable
With.
A kind of ciphertext rope based on blocking organization is disclosed in Chinese invention patent specification CN 200910063738.1
Guiding structure and its management method and disclosed in Chinese invention patent specification 200910061325.X and a kind of be based on ciphertext
Safe full-text index and searching system.Both the above patent refer to set up cryptograph index structure, and its index structure is based on
Arrange document mode, it is impossible to resist statistical analysis, lack security.
The content of the invention
The purpose of the present invention is in view of the deficienciess of the prior art, providing a kind of Security Index for being adapted to can search for encryption
Structure and its building method.
The present invention the used technical scheme that solves the above problems is：
A kind of cryptograph index structure for supporting to can search for encryption, including sys files, bf files, doc files and seg files, it is described
Sys files, bf files, doc files and seg files include all index informations and document information；Wherein：
Sys files include the number of documents in the Big prime to be used of pseudo-random function during generation index, index, the word of bf files
Length, the byte length of doc files etc. are saved, a document information list, each of which bar document are further comprises in sys files
Information includes the document ID, seg reference number of a document, deviant of the corresponding BloomFilter strings in bf files, document and existed
The byte length of deviant and the document in doc files, deviant of the BloomFilter string in bf files with
Deviant of the document in doc files serves the effect of pointer when inquiry, can help quickly to navigate to correspondence
Index information position；
Doc files preserve document information, each document packet include the domain number that document id, document title, document included,
The domain information list that the byte length and document of document are included, each domain information in the domain information list includes the domain
Title and the deviant in seg files, deviant of the domain in seg files be used for quick searching domain content；
Seg files are the files that storage is indexed content, include the content in the domain of all documents, seg files are divided into multiple limits
The file of measured length is stored separately, and each file is named in the way of " seg_x ", and x numbers for slicing files, in seg files
Domain information includes the title in domain, weights, if be indexed, if stored, if carry out tokenization, and domain text
This content, when domain is marked as not storing, then the domain content is sky；
Bf files save the Bloom Filter strings corresponding to each document, and single Bloom Filter strings are a series of 01
Combination, when being inquired about, index finds the corresponding Bloom Filter strings institute in bf files of document by sys files
The position at place, is extracted and completes to verify and inquire about in the way of 01 examines.
A kind of building method for supporting to can search for the cryptograph index structure of encryption, comprises the following steps：
1. pair each document sets up a Bloom Filter structure, by N number of cryptographic Hash of each keyword w in document
As trapdoor, it is respectively mapped on N number of point of the dot matrix of m length, and the value of N number of point is all set to 1；By in a document
After keyword is all disposed, Bloom Filter are stored as index file；
2. a list for including all domains is preserved in a document object, then each domain in traversal of lists, to need
Index is set up in the domain for setting up index, is specifically comprised the following steps：
2.1) thresholding is analyzed and processed first, obtains its token streams, each token in being flowed for token leads to
Cross a pseudo-random function f (token) and calculate its functional value S；
2.2) calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash h1 (S),
h2(S), h3(S), … hn(S)；
2.3) calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash h1 (S),
h2(S), h3(S), … hn(S)；
2.4) 2.2）In n cryptographic Hash be mapped to n in [0, M] value, wherein M is the BloomFilter of the document
The length of string, this n value is exactly the trapdoor corresponding to the token；
2.5）By 2.3）In n [0, M] in the range of the corresponding BloomFilter displacements of value be set to 1, if being 1
Position is not processed then；
After 3. all domains are all finished according to above-mentioned steps index, the corresponding BloomFilter strings of document are protected as index file
Exist in disk, and by document information and need the content in the domain preserved to write index file.
Beneficial effect：The present invention is based on trapdoor individual event function and is combined with pseudo-random function to construct one with Gao An
The cryptograph index structure of full property, can search for the document of encryption based on the Security Index structure, the present invention meet simultaneously security with
The demand of search efficiency, is adapted to can search for encryption and searching ciphertext based on keyword under cloud computing background.
Brief description of the drawings
Fig. 1 is the structural representation for the cryptograph index structure that support provided in an embodiment of the present invention can search for encryption；
Fig. 2 is the building method for the cryptograph index structure that support provided in an embodiment of the present invention can search for encryption；
Fig. 3 is the querying method for the cryptograph index structure that support provided in an embodiment of the present invention can search for encryption.
Embodiment
Below in conjunction with the accompanying drawings and specific embodiment, the present invention is furture elucidated, and the present embodiment is with technical solution of the present invention
Premised on lower implemented, it should be understood that these embodiments are only illustrative of the invention and is not intended to limit the scope of the invention.
As shown in figure 1, the embodiment of the invention discloses a kind of cryptograph index structure and its construction for supporting to can search for encryption
Method, the cryptograph index structure includes four file structures, is respectively：Sys files, bf files, doc files and seg files,
This 4 files contain all index informations and document information.The specifying information of this four files is as follows：
Sys files include the number of documents in the Big prime to be used of pseudo-random function during generation index, index, the word of bf files
Save length, byte length of doc files etc..A document information list, each of which bar document are further comprises in sys files
Information includes the document ID, seg reference number of a document, deviant of the corresponding BloomFilter strings in bf files, document and existed
The byte length of deviant and the document in doc files.Two deviants serve the work of pointer when inquiry
With can help quickly to navigate to corresponding index information position.
Doc files preserve document information, and each document packet includes the domain that document id, document title, document are included
The domain information list that number, the byte length of document and document are included, each domain information in domain information list includes should
The title in domain and the deviant in seg files, wherein, deviant of the domain in seg files is used for quick lookup domain content；
Seg files are the files that storage is indexed content, include the content in the domain of all documents.Seg files are divided into multiple limits
The file of measured length is stored separately, and each file is named in the way of " seg_x ", and x numbers for slicing files.In seg files
Domain information includes the title in domain, weights, if be indexed, if stored, if carry out tokenization, and domain text
This content, the domain content is sky if certain domain is marked as not storing.
Bf files save the Bloom Filter strings corresponding to each document.Single Bloom Filter strings are a series of
01 combination, when being inquired about, index finds the corresponding Bloom Filter of document by sys files and gone here and there in bf files
It is the location of middle, extracted and complete to verify and inquire about in the way of 01 examines.
The building method that above-mentioned support can search for the cryptograph index structure of encryption is specifically comprised the following steps：
Step 1, a Bloom Filter structure is set up to each document, by N number of Kazakhstan of each keyword w in document
Uncommon value is respectively mapped on N number of point of the dot matrix of m length, and the value of N number of point is all set into 1 as trapdoor.By a document
In keyword be all disposed after, Bloom Filter are stored as index file.
Step 2, a list for including all domains is preserved in a document object, then each in traversal of lists
Domain, to need the domain for setting up index to set up index.Described step 2, is specifically comprised the following steps：
Step 2.1, thresholding is analyzed and processed first, obtains its token streams, each in being flowed for token
Token, its functional value S is calculated by a pseudo-random function f (token).
Step 2.2, calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash
h1(S), h2(S), h3(S), … hn(S)。
Step 2.3, calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash
h1(S), h2(S), h3(S), … hn(S)。
Step 2.4, handled for the n cryptographic Hash calculated in step 2.2, be allowed to that [0, M] can be mapped to respectively
In n value, wherein M is the length of the BloomFilter strings of the document, and this n value is actually corresponding to the token
Trapdoor.
Step 2.5, the corresponding BloomFilter displacements of value in the range of the n calculated in step 2.3 [0, M] are put
1 is set to, is not processed if being 1 position.
Step 3, after all domains are all finished according to above-mentioned steps index, we go here and there the corresponding Bloom Filter of this document
It is stored in as index file in disk, and by document information and needs the content in the domain preserved to write index file.
Pseudo-random function in the present invention uses the one-way function used in the makers of FIPS 186, function to employ and is based on
The DES one-way functions of FIPS 186.Hash function in system uses BKDRHash, APHash, DJBHash, JSHash,
5 functions such as RSHash, are respectively intended to produce a different set of cryptographic Hash.
Specifically, the present invention constructs the index structure of sky first, and the structure includes 4 parts, respectively sys files, bf
File, doc files and seg files.
Then start to initialize sys files, generate largest index prime number, initialization number of documents is 0, bf byte numbers, tool
Body is as shown in figure 1, for the new document for adding directory system, generate document id, document id, document title, these information
It is inserted into Doc files, while the sys files that document information is inserted, and in the document in sys files and doc files
Document associations are got up；With the lists of keywords of post analysis document, i.e. domain information, information is set up to each domain and is inserted into seg texts
In part；Then domain information in doc documents and seg file associations are got up；Ultimately produce BloomFilter information and be inserted into bf texts
In part, and bf files are associated with doc files.
Above-mentioned association is to rely on those offset address in Fig. 1 to complete.In addition during index structure is set up,
Often increasing a file will be corresponding number of documents, document byte length, doc file byte length, bf file byte longs
Degree information is updated.It is crucial that wherein the domain information of document, which is set up, and its basic skills is as shown in Figure 2：
Its keyword domain quantity and information are obtained to each document, for each keyword domain, its index is obtained and obtains
Its token streams, each token in being flowed for token calculates its functional value by a pseudo-random function f (token)
S.Calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash h1 (S), h2 (S),
h3(S), … hn(S).This n cryptographic Hash is mapped to n value in [0, M], wherein M is the Bloom of the document
The length of Filter strings, this n value is actually the trapdoor corresponding to the token.Then by above-mentioned n [0, M] scopes
The corresponding Bloom Filter displacements of interior value are set to 1, are not processed if being 1 position.Generated after being disposed
Bloom Filter indexes are stored in bf files.
After user initiates cipher text searching request, its search routine is as shown in figure 3, be described in detail below：
When ciphertext index is constructed, in order that same keyword trapdoor can according to the difference of document area
Not, trapdoor is regenerated as new keyword after system is handled the document id where keyword and its, therefore is being entered
During row inquiry, we are also required to calculate the trapdoor of searching keyword respectively according to the difference of document id in each index.Entirely
Querying flow can generally be divided into two stages：Processing stage and trapdoor matching stage to query statement.
The processing procedure of query statement with set up index it is similar, be the pretreatment to query statement first, mainly participle,
Duplicate removal, filtering etc., ultimately form the stream of a tokenization, and generate a query tree according to query grammar.It is right after Tokenization
It is consistent when token processing is indexed with setting up in token streams, it is the letter that token is obtained by a pseudo-random function f first
Numerical value w=f (token), then carries out hash conversion with N number of hash function { h1, h2 ... ..., hN } by w and obtains comprising N number of
The set H of cryptographic Hash={ h1 (w), h2 (w) ... ..., hN (w) }, H are mapped element therein by a transforming function transformation function T
To interval [0, M], obtain a position value set P=T (H) herein in interval=p1, p2 ... ..., pN | for appointing
Anticipate 0≤i≤N, there is 0≤pi≤M }, wherein M is the BloomFilter string length corresponding to the document, then by P according to inquiry
Tree rule is merged with result position value set S, obtains a new position value set.All Token have been handled
The final position value set S inquired about can be obtained after finishing.
Trapdoor matching stage is put into after obtaining position value set S.This stage is actually the process of an order matching,
The list L of a Bloom Filter string is read first from index file, gradually to each Bloom in list L
Filter strings B is compared, if for any p ∈ S, having Bit, (B, p)=1, (B p) represents 01 string B pth to wherein Bit
Individual bit value, then B meet querying condition.By the document corresponding to B, document is added in results set R as a result；Conversely,
As long as there is a p ∈ S so that (B, p) ≠ 1, then the document corresponding to B is just unsatisfactory for querying condition to Bit.Will be all
BloomFilter is checked finish after, final results set R can be obtained, and return to inquiry user.
The present invention based on trapdoor individual event function and with pseudo-random function be combined construct one have high security it is close
Literary index structure, the document of encryption is can search for based on the Security Index structure, and the present invention meets security and search efficiency simultaneously
Demand, be adapted to can search for encryption and searching ciphertext based on keyword under cloud computing background.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (2)
1. a kind of cryptograph index structure for supporting to can search for encryption, it is characterised in that including sys files, bf files, doc files
With seg files, the sys files, bf files, doc files and seg files include all index informations and document information；Wherein：
Sys files include the number of documents in the Big prime to be used of pseudo-random function during generation index, index, the word of bf files
Length, the byte length of doc files etc. are saved, a document information list, each of which bar document are further comprises in sys files
Information includes the document ID, seg reference number of a document, deviant of the corresponding BloomFilter strings in bf files, document and existed
The byte length of deviant and the document in doc files, deviant of the BloomFilter string in bf files with
Deviant of the document in doc files serves the effect of pointer when inquiry, can help quickly to navigate to correspondence
Index information position；
Doc files preserve document information, each document packet include the domain number that document id, document title, document included,
The domain information list that the byte length and document of document are included, each domain information in the domain information list includes the domain
Title and the deviant in seg files, deviant of the domain in seg files be used for quick searching domain content；
Seg files are the files that storage is indexed content, include the content in the domain of all documents, seg files are divided into multiple limits
The file of measured length is stored separately, and each file is named in the way of " seg_x ", and x numbers for slicing files, in seg files
Domain information includes the title in domain, weights, if be indexed, if stored, if carry out tokenization, and domain text
This content, when domain is marked as not storing, then the domain content is sky；
Bf files save the Bloom Filter strings corresponding to each document, and single Bloom Filter strings are a series of 01
Combination, when being inquired about, index finds the corresponding Bloom Filter strings institute in bf files of document by sys files
The position at place, is extracted and completes to verify and inquire about in the way of 01 examines.
2. a kind of building method for supporting to can search for the cryptograph index structure of encryption according to claim 1, its feature exists
In comprising the following steps：
1. pair each document sets up a Bloom Filter structure, by N number of cryptographic Hash of each keyword w in document
As trapdoor, it is respectively mapped on N number of point of the dot matrix of m length, and the value of N number of point is all set to 1, by a document
After keyword is all disposed, Bloom Filter are stored as index file；
2. a list for including all domains is preserved in a document object, then each domain in traversal of lists, to need
Index is set up in the domain for setting up index, is specifically comprised the following steps：
2.1) thresholding is analyzed and processed first, obtains its token streams, each token in being flowed for token leads to
Cross a pseudo-random function f (token) and calculate its functional value S；
2.2) calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash h1 (S),
h2(S), h3(S), … hn(S)；
2.3) calculate S cryptographic Hash respectively by one group of hash function h1, h2, h3 ... hn, obtain n cryptographic Hash h1 (S),
h2(S), h3(S), … hn(S)；
2.4) 2.2）In n cryptographic Hash be mapped to n in [0, M] value, wherein M is the BloomFilter of the document
The length of string, this n value is exactly the trapdoor corresponding to the token；
2.5）By 2.3）In n [0, M] in the range of the corresponding BloomFilter displacements of value be set to 1, if being 1
Position is not processed then；
After 3. all domains are all finished according to above-mentioned steps index, the corresponding BloomFilter strings of document are protected as index file
Exist in disk, and by document information and need the content in the domain preserved to write index file.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108768651A (en) * | 2018-04-20 | 2018-11-06 | 南京搜文信息技术有限公司 | That supports the inquiry of multidimensional interval range can search for public key encryption method |
| CN109783441A (en) * | 2018-12-24 | 2019-05-21 | 南京中新赛克科技有限责任公司 | Mass data inquiry method based on Bloom Filter |
| CN113420679A (en) * | 2021-06-26 | 2021-09-21 | 南京搜文信息技术有限公司 | Artificial intelligent cross-camera multi-target tracking system and tracking algorithm |
| CN113626554A (en) * | 2021-08-17 | 2021-11-09 | 北京计算机技术及应用研究所 | Method for calculating hash value of Chinese document |
| CN116628721A (en) * | 2023-06-06 | 2023-08-22 | 北京大学 | Searchable encryption method and system for digital object |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101694672A (en) * | 2009-10-16 | 2010-04-14 | 华中科技大学 | Distributed safe retrieval system |
| KR101476039B1 (en) * | 2013-06-19 | 2014-12-23 | 세명대학교 산학협력단 | Method for encrypting database and method for real-time search thereof |
| CN104765848A (en) * | 2015-04-17 | 2015-07-08 | 中国人民解放军空军航空大学 | Symmetrical searchable encryption method for supporting result high-efficiency sequencing in hybrid cloud storage |
| CN105069358A (en) * | 2015-07-13 | 2015-11-18 | 西安理工大学 | Keyword searchable encryption method based on Bloom filter with storage structure |
| CN106127075A (en) * | 2016-06-27 | 2016-11-16 | 湖南大学 | The encryption method of can search for based on secret protection under a kind of cloud storage environment |
-
2017
- 2017-06-06 CN CN201710418493.4A patent/CN107273467A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101694672A (en) * | 2009-10-16 | 2010-04-14 | 华中科技大学 | Distributed safe retrieval system |
| KR101476039B1 (en) * | 2013-06-19 | 2014-12-23 | 세명대학교 산학협력단 | Method for encrypting database and method for real-time search thereof |
| CN104765848A (en) * | 2015-04-17 | 2015-07-08 | 中国人民解放军空军航空大学 | Symmetrical searchable encryption method for supporting result high-efficiency sequencing in hybrid cloud storage |
| CN105069358A (en) * | 2015-07-13 | 2015-11-18 | 西安理工大学 | Keyword searchable encryption method based on Bloom filter with storage structure |
| CN106127075A (en) * | 2016-06-27 | 2016-11-16 | 湖南大学 | The encryption method of can search for based on secret protection under a kind of cloud storage environment |
Non-Patent Citations (1)
| Title |
|---|
| 陈锐: "基于全文检索系统的安全索引技术研究与实现", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108768651A (en) * | 2018-04-20 | 2018-11-06 | 南京搜文信息技术有限公司 | That supports the inquiry of multidimensional interval range can search for public key encryption method |
| CN109783441A (en) * | 2018-12-24 | 2019-05-21 | 南京中新赛克科技有限责任公司 | Mass data inquiry method based on Bloom Filter |
| CN113420679A (en) * | 2021-06-26 | 2021-09-21 | 南京搜文信息技术有限公司 | Artificial intelligent cross-camera multi-target tracking system and tracking algorithm |
| CN113420679B (en) * | 2021-06-26 | 2024-04-26 | 南京搜文信息技术有限公司 | Artificial intelligence cross-camera multi-target tracking system and tracking method |
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