CN117408644B - Comprehensive analysis management system and method based on multidimensional data - Google Patents
Comprehensive analysis management system and method based on multidimensional data Download PDFInfo
- Publication number
- CN117408644B CN117408644B CN202311709724.9A CN202311709724A CN117408644B CN 117408644 B CN117408644 B CN 117408644B CN 202311709724 A CN202311709724 A CN 202311709724A CN 117408644 B CN117408644 B CN 117408644B
- Authority
- CN
- China
- Prior art keywords
- electronic evidence
- electronic
- acquisition
- collection
- characteristic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000004458 analytical method Methods 0.000 title claims abstract description 23
- 238000012544 monitoring process Methods 0.000 claims abstract description 60
- 238000012216 screening Methods 0.000 claims abstract description 25
- 238000009960 carding Methods 0.000 claims abstract description 7
- 238000007726 management method Methods 0.000 claims description 48
- 230000008569 process Effects 0.000 claims description 17
- 238000000605 extraction Methods 0.000 claims description 15
- 230000005856 abnormality Effects 0.000 claims description 10
- 239000000284 extract Substances 0.000 claims description 7
- 238000013475 authorization Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000003247 decreasing effect Effects 0.000 claims description 6
- 238000010219 correlation analysis Methods 0.000 claims description 2
- 230000009471 action Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012351 Integrated analysis Methods 0.000 description 1
- 238000012098 association analyses Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000969 carrier Substances 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/18—Legal services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/49—Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Economics (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Health & Medical Sciences (AREA)
- Technology Law (AREA)
- Operations Research (AREA)
- Computing Systems (AREA)
- Multimedia (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention relates to the technical field of electronic evidence collection and management, in particular to a comprehensive analysis and management system and method based on multidimensional data, comprising the steps of determining whether to adjust an electronic evidence collection program according to the collection condition of electronic evidence, and storing the electronic evidence which finally meets the requirement into an electronic evidence library; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records; extracting all instruction adjustment structures influencing the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures influencing the adjustment of the electronic evidence collection program based on the characteristic indexes; intercepting a target monitoring video sequence with improper operation of the acquisition personnel, generating a supervision operation library, and carrying out real-time monitoring and early warning on the improper operation of the acquisition personnel based on the supervision operation library.
Description
Technical Field
The invention relates to the technical field of electronic evidence collection and management, in particular to a comprehensive analysis and management system and method based on multidimensional data.
Background
With the popularity of computer and network technologies, electronic commerce and trade activities and many other network-based interpersonal interactions have emerged in large numbers, and electronic documents have become important carriers for information transfer and recording facts, in which once disputes or cases occur, related electronic documents become important evidence; electronic evidence is electronic data that has been studied as evidence that can prove relevant facts.
Because of the specificity of the electronic evidence, when the electronic evidence is collected, firstly, a computer operator of a computer providing an evidence unit needs to open a computer to search the evidence to be collected; after evidence collection personnel confirms that the file is evidence to be collected, the evidence collection personnel extracts and fixes the evidence by adopting a corresponding mode; in the evidence searching process, the originality, the authenticity and the legality of the electronic evidence are ensured, so that the performance requirement on the electronic evidence obtaining equipment and the operation compliance requirement of evidence obtaining personnel are also greatly improved.
Disclosure of Invention
The invention aims to provide a comprehensive analysis management system and method based on multidimensional data, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a comprehensive analysis management method based on multidimensional data comprises the following steps:
step S100: each time an electronic evidence collection management terminal receives an electronic evidence collection task, extracting task keywords from the electronic evidence collection task, formulating an electronic evidence collection scheme according to the task keywords and the network operation environment of the target collection electronic equipment, generating an electronic evidence collection program according to the electronic evidence collection scheme, and automatically issuing the electronic evidence collection program to electronic evidence collection terminal equipment by utilizing the Internet of things;
step S200: after the electronic evidence collection terminal equipment completes the connection authorization with the electronic equipment for target collection, the electronic evidence collection terminal equipment extracts electronic evidence from electronic information stored or transmitted in the electronic equipment for target collection by executing corresponding operation instructions; monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence;
step S300: the electronic evidence collection management terminal receives and analyzes the electronic evidence uploaded by the electronic evidence collection terminal equipment in real time by utilizing the Internet of things, decides whether to adjust an electronic evidence collection program according to the collection condition of the electronic evidence, and stores the electronic evidence which finally meets the requirement into an electronic evidence library; the adjustment comprises the steps of modifying the content of the operation instruction in the program and increasing or decreasing the operation instruction in the program;
step S400: setting a historical electronic evidence storage record which is subjected to adjustment of an electronic evidence collection program executed by electronic evidence collection end equipment as a first characteristic storage record, and setting a historical electronic evidence storage record which is not subjected to adjustment of the electronic evidence collection program executed by the electronic evidence collection end equipment as a second characteristic storage record; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records;
step S500: extracting all instruction adjustment structures influencing the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures influencing the adjustment of the electronic evidence collection program based on the characteristic indexes;
step S600: according to the distribution condition of the characteristic instruction adjusting structure in each historical electronic evidence storage record, intercepting a target monitoring video sequence with improper operation of the acquisition personnel, generating a supervision operation library, and carrying out real-time monitoring and early warning on the improper operation of the acquisition personnel based on the supervision operation library.
Further, step S300 includes:
step S301: extracting characteristic information from each preprocessed electronic evidence, and expanding association analysis between the characteristic information and task keywords of an electronic evidence acquisition task by using an association rule analysis method; carrying out information integrity judgment on each preprocessed electronic evidence; the preprocessing comprises the steps of processing unstructured electronic evidences such as pictures, videos and sounds acquired by electronic evidence acquisition end equipment by utilizing character recognition, image recognition or audio recognition;
step S302: when the extracted characteristic information of all the electronic evidences and the task keywords of the electronic evidence collection task meet the relevance, and the information contained in all the electronic evidences is complete, in the application, the complete information contained in the electronic evidences means that no semantic deletion exists in the information or the information is ambiguous; judging that the correspondingly executed electronic evidence acquisition program does not need to be adjusted; when the relevance is not met between the characteristic information of any electronic evidence and the task keyword of the electronic evidence collection task, or when information is missing in any electronic evidence, in the application, the fact that the information is missing in the electronic evidence means that the semantics are missing or the information is ambiguous in the information, the electronic evidence collection program which is correspondingly executed is judged to need to be adjusted until the relevance is met between the extracted characteristic information of all the electronic evidence and the task keyword of the electronic evidence collection task, and the electronic evidence collection task is stopped when the phenomenon of information missing does not exist in all the electronic evidence; wherein, the premise is to follow the acquisition strategy when the electronic evidence acquisition scheme is adjusted.
Further, step S400 includes:
step S401: if the electronic evidence collection program which is executed by the electronic evidence collection terminal equipment at the most initial time is in a certain first feature storage record, the electronic evidence collection program is the same as the electronic evidence collection program which is executed by the electronic evidence collection terminal equipment in a certain second feature storage record, and a certain first feature storage record and a certain second feature storage record form a group of reference storage records;
step S402: a first feature storage record is a, a second feature storage record is b, and the first feature storage record a is captured, and an electronic evidence acquisition program sequence L (a) = { P which is executed by an electronic evidence acquisition end device according to time sequence is formed in the first feature storage record a 1 →P 2 →...→P n -a }; wherein P is 1 、P 2 、...、P n Respectively representing the electronic evidence collection end equipment in the first feature storage record a, and sequentially executing 1 st, 2 nd and n electronic evidence collection programs; wherein, pass through P n The obtained electronic evidence is the electronic evidence which is correspondingly stored in the first characteristic storage record a and enters the electronic evidence library; setting every two adjacent electronic evidence acquisition programs in L (a) to form an acquisition program adjustment node;
step S403: set in the electronic evidence collection program sequence L (a) = { P 1 →P 2 →...→P n Some acquisition procedure adjustment node U is present }: p (P) i →P i+1 Acquiring the execution completion P i Post-extraction of the obtained electronic evidence S (P i ) And execute P n Post-extraction of the obtained electronic evidence S (P n ) Similarity f between 1 Acquiring the execution completion P i+1 Post-extraction of the obtained electronic evidence S (P j ) And execute P n Post-extraction of the obtained electronic evidence S (P n ) Similarity betweenf 2 ；
Step S404: when f 1 ≥f 2 Judging a certain acquisition program adjusting node U: p (P) i →P i+1 Is a first feature node; description of the electronic evidence collection procedure from P i Adjusted to P i+1 After that, the extracted electronic proof is not closer to the standard electronic proof S (P n ) (II), (III), (V), (; when f 1 <f 2 Judging a certain acquisition program adjusting node U: p (P) i →P i+1 Is a second feature node; description of the electronic evidence collection procedure from P i Adjusted to P i+1 The closer the extracted electronic proof is to the standard electronic proof S (P n )；
And analyzing whether the continuous adjustment process of the acquisition program is a process of continuously acquiring standard electronic evidence, if so, reasonably judging that the adjustment of the acquisition program currently made is based on the influence of objective factors in the aspect of target acquisition equipment, and thus, adjusting the necessity.
Further, step S500 includes:
step S501: the method comprises the steps that a certain characteristic node extracted from a certain reference storage record group formed by a first characteristic storage record x and a second characteristic storage record y is set as U: p (P) j →P j+1 Extracted at P j The set of operation instructions H (P j ) At P j+1 The set of operation instructions H (P j+1 ) The method comprises the steps of carrying out a first treatment on the surface of the Extraction set R 1 =H(P j )-H(P j )∩H(P j+1 ) Set R 2 =(P j+1 )-H(P j )∩H(P j+1 ) Will be set R 1 Any one of the operation instructions r 1 One by one with set R 2 Any one of the operation instructions r 2 Establishing an association adjustment relationship;
step S502: comparing the electronic equipment acquired by the target of the first characteristic storage record x with the operation data of the electronic equipment acquired by the target of the second characteristic storage record y on each network operation environment parameter item, and extracting the operation environment parameter item with operation data deviation to obtain an operation environment parameter item set E;sequentially combining each operation environment parameter item E in the operation environment parameter item set E with each operation instruction pair with an association adjustment relation: r is (r) 1 →r 2 Establishing an association relation between the two to obtain a plurality of instruction adjustment structures corresponding to each operation environment parameter item e: g (e) =r 1 →r 2 ；
Step S503: acquiring all instruction adjustment structures extracted from all reference storage record groups; setting the total number of certain instruction adjusting structures extracted to obtain a certain running environment parameter item as k1, wherein the total number of second characteristic nodes extracted to obtain a certain instruction adjusting structure is m1, the total number of first characteristic nodes extracted to obtain a certain instruction adjusting structure is m2, and m1+m2=k1; calculating the characteristic index of a certain instruction adjusting structure as beta= (m 1-m 2)/m 2, and judging beta>β Threshold value The instruction adjusting structure of (2) is a characteristic instruction adjusting structure; wherein beta is Threshold value Is a characteristic index threshold.
Further, step S600 includes:
step S601: calculating an abnormality index α=d1/D for each first feature node in each reference storage record group; wherein D1 represents the total number of feature instruction adjustment structures included in each first feature node, and D represents the total number of instruction adjustment structures included in each first feature node; alpha Threshold value Is an abnormality index threshold;
step S602: when capturing a certain first characteristic node P g →P g+1 Satisfy alpha>α Threshold value Intercepting the operation of an electronic evidence acquisition end device by an electronic evidence acquisition personnel from a corresponding monitoring video sequence to execute P g+1 When the corresponding monitoring video sequence is used as a target monitoring video sequence, the target monitoring video sequence is fed back to a manager port, and improper operation of an electronic evidence acquisition person in the target monitoring video sequence is marked;
if the proportion of the feature instruction adjusting structure contained in a certain first feature node to the total number of the total instruction adjusting structures is large, the operation instruction executed by the acquisition personnel in the first feature node is moved towards the direction of acquiring more standard electronic evidence, because the adjustment is carried out to adapt to the current network operation environment, but the finally obtained electronic evidence is far from the standardized electronic evidence, on the other hand, the situation that the corresponding operation is performed by the acquisition personnel in the process of executing the corresponding acquisition instruction can exist in an inappropriate place is reflected, so that the acquired electronic evidence is not satisfactory;
for example, a first characteristic node P g →P g+1 The total number of the existing instruction adjusting structures is 30, network operation environment information of the electronic equipment acquired by the target is acquired in a history electronic evidence storage record corresponding to a certain first characteristic node, if the situation that 24 characteristic instruction adjusting structures exist in the 30 electronic evidence storage records is recognized, the abnormality index corresponding to the certain first characteristic node is alpha=24/30=4/5 and is larger than an abnormality index threshold value 3/5, and if the abnormality index is larger than the abnormality index threshold value 3/5, the electronic evidence acquisition end equipment operated by an electronic evidence acquisition personnel is judged to be executing P g+1 When there is improper behavior;
step S603: extracting all marked improper operations, and simultaneously acquiring acquisition environments corresponding to the improper operations to generate a supervision operation library; the acquisition environment comprises a corresponding electronic evidence acquisition task and a network operation environment of the electronic equipment for target acquisition.
In order to better realize the method, the comprehensive analysis management system is also provided, and comprises an electronic evidence acquisition management module, an electronic evidence information management module, an acquisition program adjustment rule analysis module, an instruction adjustment structure screening module and an acquisition monitoring and early warning module;
the electronic evidence collection management module is used for extracting task keywords from the electronic evidence collection task every time the electronic evidence collection management terminal receives an electronic evidence collection task, making an electronic evidence collection scheme according to the task keywords and the network operation environment of the target collection electronic equipment, generating an electronic evidence collection program according to the electronic evidence collection scheme, and automatically issuing the electronic evidence collection program to electronic evidence collection terminal equipment by utilizing the Internet of things; the electronic evidence collection terminal device extracts electronic evidence from electronic information stored or transmitted in the electronic device collected by the target by executing a corresponding operation instruction; monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence;
the electronic evidence information management module is used for receiving and analyzing the electronic evidence uploaded by the electronic evidence collection terminal equipment in real time by utilizing the Internet of things by the electronic evidence collection management terminal, determining whether to adjust an electronic evidence collection program according to the collection condition of the electronic evidence, and storing the electronic evidence which finally meets the requirement into an electronic evidence library; the adjustment comprises the steps of modifying the content of the operation instruction in the program and increasing or decreasing the operation instruction in the program;
the acquisition program adjustment rule analysis module is used for setting a historical electronic evidence storage record which is subjected to adjustment of the electronic evidence acquisition program executed by the electronic evidence acquisition end equipment as a first characteristic storage record, and setting a historical electronic evidence storage record which is not subjected to adjustment of the electronic evidence acquisition program executed by the electronic evidence acquisition end equipment as a second characteristic storage record; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records;
the instruction adjustment structure screening module is used for extracting all instruction adjustment structures affecting the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures affecting the adjustment of the electronic evidence collection program based on the characteristic indexes;
and the acquisition monitoring and early warning module is used for intercepting a target monitoring video sequence with improper operation of acquisition personnel according to the distribution condition of the characteristic instruction adjustment structure in each historical electronic evidence storage record, generating a monitoring operation library and carrying out real-time monitoring and early warning on the improper operation of the acquisition personnel based on the monitoring operation library.
Further, the electronic evidence collection management module comprises a collection execution unit and an information capturing unit;
the system comprises an acquisition execution unit, an electronic evidence acquisition management terminal, an electronic evidence acquisition terminal and an electronic evidence acquisition terminal, wherein the acquisition execution unit is used for extracting task keywords for the electronic evidence acquisition task every time the electronic evidence acquisition management terminal receives an electronic evidence acquisition task, making an electronic evidence acquisition scheme according to the task keywords and the network operation environment of target acquisition electronic equipment, generating an electronic evidence acquisition program according to the electronic evidence acquisition scheme, and automatically issuing the electronic evidence acquisition program to the electronic evidence acquisition terminal equipment by utilizing the Internet of things;
the information capturing unit is used for extracting electronic evidence from electronic information stored or transmitted in the electronic equipment collected by the target after the electronic evidence collection end equipment completes connection authorization with the electronic equipment collected by the target; and monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence.
Further, the instruction adjustment structure screening module comprises a characteristic index calculation unit and a characteristic instruction adjustment structure screening unit;
the characteristic index calculation unit is used for extracting all instruction adjustment structures affecting the adjustment of the electronic evidence collection program and calculating the characteristic index of each instruction adjustment structure;
and the characteristic instruction adjusting structure screening unit is used for receiving the data in the characteristic index calculating unit and screening the characteristic instruction adjusting structure which influences the adjustment of the electronic evidence acquisition program.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, the collection rule capturing is carried out on the electronic evidence collection process in each historical electronic evidence storage record, the adjustment rules presented on the electronic evidence collection program in all the historical electronic evidence storage records are combed, the collection program setting of the network operation environment of the electronic equipment which takes account of the electronic evidence collection task and the target collection in the electronic evidence collection process is extracted, the supervision operation library of the electronic evidence collection is constructed, the real-time monitoring of the collection operation of the electronic evidence collection personnel is realized, and the phenomenon of reduced electronic evidence collection efficiency caused by improper collection execution operation is reduced.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a comprehensive analysis management method based on multidimensional data;
fig. 2 is a schematic structural diagram of an integrated analysis management system based on multidimensional data according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: a comprehensive analysis management method based on multidimensional data comprises the following steps:
step S100: each time an electronic evidence collection management terminal receives an electronic evidence collection task, extracting task keywords from the electronic evidence collection task, formulating an electronic evidence collection scheme according to the task keywords and the network operation environment of the target collection electronic equipment, generating an electronic evidence collection program according to the electronic evidence collection scheme, and automatically issuing the electronic evidence collection program to electronic evidence collection terminal equipment by utilizing the Internet of things;
step S200: after the electronic evidence collection terminal equipment completes the connection authorization with the electronic equipment for target collection, the electronic evidence collection terminal equipment extracts electronic evidence from electronic information stored or transmitted in the electronic equipment for target collection by executing corresponding operation instructions; monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence;
step S300: the electronic evidence collection management terminal receives and analyzes the electronic evidence uploaded by the electronic evidence collection terminal equipment in real time by utilizing the Internet of things, decides whether to adjust an electronic evidence collection program according to the collection condition of the electronic evidence, and stores the electronic evidence which finally meets the requirement into an electronic evidence library; the adjustment comprises the steps of modifying the content of the operation instruction in the program and increasing or decreasing the operation instruction in the program;
wherein, step S300 includes:
step S301: extracting characteristic information from each preprocessed electronic evidence, and developing correlation analysis between the characteristic information and task keywords of an electronic evidence acquisition task; carrying out information integrity judgment on each preprocessed electronic evidence;
step S302: when the feature information of all the extracted electronic evidences and the task keywords of the electronic evidence collection task meet the relevance, and the information contained in all the electronic evidences is complete, judging that the electronic evidence collection program which is correspondingly executed does not need to be adjusted; when the relevance is not met between the characteristic information of any electronic evidence and the task keyword of the electronic evidence collection task, or when information is missing in any electronic evidence, judging that the electronic evidence collection program which is required to be correspondingly executed is required to be adjusted until the relevance is met between the extracted characteristic information of all the electronic evidence and the task keyword of the electronic evidence collection task, and stopping when the information missing phenomenon does not exist in all the electronic evidence;
step S400: setting a historical electronic evidence storage record which is subjected to adjustment of an electronic evidence collection program executed by electronic evidence collection end equipment as a first characteristic storage record, and setting a historical electronic evidence storage record which is not subjected to adjustment of the electronic evidence collection program executed by the electronic evidence collection end equipment as a second characteristic storage record; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records;
wherein, step S400 includes:
step S401: if the electronic evidence collection program which is executed by the electronic evidence collection terminal equipment at the most initial time is in a certain first feature storage record, the electronic evidence collection program is the same as the electronic evidence collection program which is executed by the electronic evidence collection terminal equipment in a certain second feature storage record, and a certain first feature storage record and a certain second feature storage record form a group of reference storage records;
step S402: a first feature storage record is a, a second feature storage record is b, and the first feature storage record a is captured, and an electronic evidence acquisition program sequence L (a) = { P which is executed by an electronic evidence acquisition end device according to time sequence is formed in the first feature storage record a 1 →P 2 →...→P n -a }; wherein P is 1 、P 2 、...、P n Respectively representing the electronic evidence collection end equipment in the first feature storage record a, and sequentially executing 1 st, 2 nd and n electronic evidence collection programs; wherein, pass through P n The obtained electronic evidence is the electronic evidence which is correspondingly stored in the first characteristic storage record a and enters the electronic evidence library; setting every two adjacent electronic evidence acquisition programs in L (a) to form an acquisition program adjustment node;
step S403: set in the electronic evidence collection program sequence L (a) = { P 1 →P 2 →...→P n Some acquisition procedure adjustment node U is present }: p (P) i →P i+1 Acquiring the execution completion P i Post-extraction of the obtained electronic evidence S (P i ) And execute P n Post-extraction of the obtained electronic evidence S (P n ) Similarity f between 1 Acquiring the execution completion P i+1 Post-extraction of the obtained electronic evidence S (P j ) And execute P n Post-extraction of the obtained electronic evidence S (P n ) Similarity f between 2 ；
Step S404: when f 1 ≥f 2 Judging a certain acquisition program adjusting node U: p (P) i →P i+1 Is a first feature node; when f 1 <f 2 Judging a certain acquisition program adjusting node U: p (P) i →P i+1 Is a second feature node;
step S500: extracting all instruction adjustment structures influencing the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures influencing the adjustment of the electronic evidence collection program based on the characteristic indexes;
wherein, step S500 includes:
step S501: the method comprises the steps that a certain characteristic node extracted from a certain reference storage record group formed by a first characteristic storage record x and a second characteristic storage record y is set as U: p (P) j →P j+1 Extracted at P j The set of operation instructions H (P j ) At P j+1 The set of operation instructions H (P j+1 ) The method comprises the steps of carrying out a first treatment on the surface of the Extraction set R 1 =H(P j )-H(P j )∩H(P j+1 ) Set R 2 =(P j+1 )-H(P j )∩H(P j+1 ) Will be set R 1 Any one of the operation instructions r 1 One by one with set R 2 Any one of the operation instructions r 2 Establishing an association adjustment relationship;
step S502: comparing the electronic equipment acquired by the target of the first characteristic storage record x with the operation data of the electronic equipment acquired by the target of the second characteristic storage record y on each network operation environment parameter item, and extracting the operation environment parameter item with operation data deviation to obtain an operation environment parameter item set E; sequentially combining each operation environment parameter item E in the operation environment parameter item set E with each operation instruction pair with an association adjustment relation: r is (r) 1 →r 2 Establishing an association relation between the two to obtain a plurality of instruction adjustment structures corresponding to each operation environment parameter item e: g (e) =r 1 →r 2 ；
Step S503: acquiring all instruction adjustment structures extracted from all reference storage record groups; setting the total number of certain instruction adjusting structures extracted to obtain a certain running environment parameter item as k1, wherein the total number of second characteristic nodes extracted to obtain a certain instruction adjusting structure is m1, the total number of first characteristic nodes extracted to obtain a certain instruction adjusting structure is m2, and m1+m2=k1; calculating the characteristic index of a certain instruction adjusting structure as beta= (m 1-m 2)/m 2, and judging beta>β Threshold value The instruction adjusting structure of (2) is a characteristic instruction adjusting structure; wherein beta is Threshold value Is a feature index threshold;
step S600: intercepting a target monitoring video sequence with improper operation of the acquisition personnel according to the distribution condition of a characteristic instruction adjusting structure in each historical electronic evidence storage record, generating a supervision operation library, and carrying out real-time monitoring and early warning on the improper operation of the acquisition personnel based on the supervision operation library;
wherein, step S600 includes:
step S601: calculating an abnormality index α=d1/D for each first feature node in each reference storage record group; wherein D1 represents the total number of feature instruction adjustment structures included in each first feature node, and D represents the total number of instruction adjustment structures included in each first feature node; alpha Threshold value Is an abnormality index threshold;
step S602: when capturing a certain first characteristic node P g →P g+1 Satisfy alpha>α Threshold value Intercepting the operation of an electronic evidence acquisition end device by an electronic evidence acquisition personnel from a corresponding monitoring video sequence to execute P g+1 When the corresponding monitoring video sequence is used as a target monitoring video sequence, the target monitoring video sequence is fed back to a manager port, and improper operation of an electronic evidence acquisition person in the target monitoring video sequence is marked;
step S603: extracting all marked improper operations, and simultaneously acquiring acquisition environments corresponding to the improper operations to generate a supervision operation library; the acquisition environment comprises a corresponding electronic evidence acquisition task and a network operation environment of the electronic equipment for target acquisition.
In order to better realize the method, the comprehensive analysis management system is also provided, and comprises an electronic evidence acquisition management module, an electronic evidence information management module, an acquisition program adjustment rule analysis module, an instruction adjustment structure screening module and an acquisition monitoring and early warning module;
the electronic evidence collection management module is used for extracting task keywords from the electronic evidence collection task every time the electronic evidence collection management terminal receives an electronic evidence collection task, making an electronic evidence collection scheme according to the task keywords and the network operation environment of the target collection electronic equipment, generating an electronic evidence collection program according to the electronic evidence collection scheme, and automatically issuing the electronic evidence collection program to electronic evidence collection terminal equipment by utilizing the Internet of things; the electronic evidence collection terminal device extracts electronic evidence from electronic information stored or transmitted in the electronic device collected by the target by executing a corresponding operation instruction; monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence;
the electronic evidence information management module is used for receiving and analyzing the electronic evidence uploaded by the electronic evidence collection terminal equipment in real time by utilizing the Internet of things by the electronic evidence collection management terminal, determining whether to adjust an electronic evidence collection program according to the collection condition of the electronic evidence, and storing the electronic evidence which finally meets the requirement into an electronic evidence library; the adjustment comprises the steps of modifying the content of the operation instruction in the program and increasing or decreasing the operation instruction in the program;
the acquisition program adjustment rule analysis module is used for setting a historical electronic evidence storage record which is subjected to adjustment of the electronic evidence acquisition program executed by the electronic evidence acquisition end equipment as a first characteristic storage record, and setting a historical electronic evidence storage record which is not subjected to adjustment of the electronic evidence acquisition program executed by the electronic evidence acquisition end equipment as a second characteristic storage record; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records;
the instruction adjustment structure screening module is used for extracting all instruction adjustment structures affecting the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures affecting the adjustment of the electronic evidence collection program based on the characteristic indexes;
and the acquisition monitoring and early warning module is used for intercepting a target monitoring video sequence with improper operation of acquisition personnel according to the distribution condition of the characteristic instruction adjustment structure in each historical electronic evidence storage record, generating a monitoring operation library and carrying out real-time monitoring and early warning on the improper operation of the acquisition personnel based on the monitoring operation library.
The electronic evidence collection management module comprises a collection execution unit and an information capturing unit;
the system comprises an acquisition execution unit, an electronic evidence acquisition management terminal, an electronic evidence acquisition terminal and an electronic evidence acquisition terminal, wherein the acquisition execution unit is used for extracting task keywords for the electronic evidence acquisition task every time the electronic evidence acquisition management terminal receives an electronic evidence acquisition task, making an electronic evidence acquisition scheme according to the task keywords and the network operation environment of target acquisition electronic equipment, generating an electronic evidence acquisition program according to the electronic evidence acquisition scheme, and automatically issuing the electronic evidence acquisition program to the electronic evidence acquisition terminal equipment by utilizing the Internet of things;
the information capturing unit is used for extracting electronic evidence from electronic information stored or transmitted in the electronic equipment collected by the target after the electronic evidence collection end equipment completes connection authorization with the electronic equipment collected by the target; and monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence.
The instruction adjustment structure screening module comprises a characteristic index calculation unit and a characteristic instruction adjustment structure screening unit;
the characteristic index calculation unit is used for extracting all instruction adjustment structures affecting the adjustment of the electronic evidence collection program and calculating the characteristic index of each instruction adjustment structure;
and the characteristic instruction adjusting structure screening unit is used for receiving the data in the characteristic index calculating unit and screening the characteristic instruction adjusting structure which influences the adjustment of the electronic evidence acquisition program.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A comprehensive analysis management method based on multidimensional data, the method comprising:
step S100: each time an electronic evidence collection management terminal receives an electronic evidence collection task, extracting task keywords from the electronic evidence collection task, formulating an electronic evidence collection scheme according to the task keywords and the network operation environment of target collection electronic equipment, generating an electronic evidence collection program according to the electronic evidence collection scheme, and automatically issuing the electronic evidence collection program to electronic evidence collection terminal equipment by utilizing the Internet of things;
step S200: after the electronic evidence collection terminal equipment completes the connection authorization with the electronic equipment for target collection, the electronic evidence collection terminal equipment extracts electronic evidence from electronic information stored or transmitted in the electronic equipment for target collection by executing corresponding operation instructions; monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence;
step S300: the electronic evidence collection management terminal receives and analyzes the electronic evidence uploaded by the electronic evidence collection terminal equipment in real time by utilizing the Internet of things, decides whether to adjust the electronic evidence collection program according to the collection condition of the electronic evidence, and stores the electronic evidence which finally meets the requirement into an electronic evidence library; the adjustment comprises the steps of modifying the content of the operation instruction in the program and increasing or decreasing the operation instruction in the program;
step S400: setting a historical electronic evidence storage record which is subjected to adjustment of an electronic evidence collection program executed by electronic evidence collection end equipment as a first characteristic storage record, and setting a historical electronic evidence storage record which is not subjected to adjustment of the electronic evidence collection program executed by the electronic evidence collection end equipment as a second characteristic storage record; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records;
step S500: extracting all instruction adjustment structures influencing the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures influencing the adjustment of the electronic evidence collection program based on the characteristic indexes;
step S600: according to the distribution condition of the characteristic instruction adjusting structure in each historical electronic evidence storage record, intercepting a target monitoring video sequence with improper operation of the acquisition personnel, generating a supervision operation library, and carrying out real-time monitoring and early warning on the improper operation of the acquisition personnel based on the supervision operation library.
2. The method of claim 1, wherein the step S300 includes:
step S301: extracting characteristic information from each preprocessed electronic evidence, and developing correlation analysis between the characteristic information and task keywords of an electronic evidence acquisition task; carrying out information integrity judgment on each preprocessed electronic evidence;
step S302: when the feature information of all the extracted electronic evidences and the task keywords of the electronic evidence collection task meet the relevance, and the information contained in all the electronic evidences is complete, judging that the electronic evidence collection program which is correspondingly executed does not need to be adjusted; when the relevance is not met between the characteristic information of any electronic evidence and the task keyword of the electronic evidence collection task, or when the information is missing in any electronic evidence, the electronic evidence collection program which is required to be correspondingly executed is judged to be adjusted until the relevance is met between the extracted characteristic information of all the electronic evidence and the task keyword of the electronic evidence collection task, and the electronic evidence collection task is stopped when the information missing phenomenon does not exist in all the electronic evidence.
3. The method of claim 1, wherein the step S400 includes:
step S401: if the electronic evidence collection program which is executed by the electronic evidence collection terminal equipment at the most initial time is in a certain first feature storage record, the electronic evidence collection program is the same as the electronic evidence collection program which is executed by the electronic evidence collection terminal equipment in a certain second feature storage record, and the certain first feature storage record and the certain second feature storage record form a group of reference storage records;
step S402: a first feature storage record is a, a second feature storage record is b, and the first feature storage record a is captured, and an electronic evidence acquisition program sequence L (a) = { P which is executed by an electronic evidence acquisition end device according to time sequence is formed in the first feature storage record a 1 →P 2 →...→P n -a }; wherein P is 1 、P 2 、...、P n Respectively representing the electronic evidence collection end equipment in the first feature storage record a, and sequentially executing 1 st, 2 nd and n electronic evidence collection programs; wherein, pass through P n The obtained electronic evidence is the electronic evidence which is correspondingly stored in the first characteristic storage record a and enters an electronic evidence library; setting every two adjacent electronic evidence acquisition programs in L (a) to form an acquisition program adjustment node;
step S403: set in the electronic evidence collection program sequence L (a) = { P 1 →P 2 →...→P n Some acquisition procedure adjustment node U is present }: p (P) i →P i+1 Acquiring the execution completion P i Post-extraction of the obtained electronic evidence S (P i ) And execute P n Post-extraction of the obtained electronic evidence S (P n ) Similarity f between 1 Acquiring the execution completion P i+1 Post-extraction of the obtained electronic evidence S (P j ) And execute P n Post-extraction of the obtained electronic evidence S (P n ) Similarity f between 2 ；
Step S404: when f 1 ≥f 2 Judging a certain acquisition program adjusting node U: p (P) i →P i+1 Is a first feature node; when f 1 <f 2 Judging a certain acquisition program adjusting node U: p (P) i →P i+1 Is the second feature node.
4. A method of comprehensive analysis management based on multidimensional data according to claim 3, wherein the step S500 comprises:
step S501: the method comprises the steps that a certain characteristic node extracted from a certain reference storage record group formed by a first characteristic storage record x and a second characteristic storage record y is set as U: p (P) j →P j+1 Extracted at P j The set of operation instructions H (P j ) At P j+1 The set of operation instructions H (P j+1 ) The method comprises the steps of carrying out a first treatment on the surface of the Extraction set R 1 =H(P j )-H(P j )∩H(P j+1 ) Set R 2 =(P j+1 )-H(P j )∩H(P j+1 ) Will be set R 1 Any one of the operation instructions r 1 One by one with set R 2 Any one of the operation instructions r 2 Establishing an association adjustment relationship;
step S502: comparing the electronic equipment acquired by the target of the first characteristic storage record x with the operation data of the electronic equipment acquired by the target of the second characteristic storage record y on each network operation environment parameter item, and extracting the operation environment parameter item with operation data deviation to obtain an operation environment parameter item set E; sequentially combining each operation environment parameter item E in the operation environment parameter item set E with each pair of operation instruction pairs with association adjustment relations: r is (r) 1 →r 2 Establishing an association relation between the two to obtain a plurality of instruction adjustment structures corresponding to each operation environment parameter item e: g (e) =r 1 →r 2 ；
Step S503: acquiring all instruction adjustment structures extracted from all reference storage record groups; setting and extracting to obtain a parameter item corresponding to a certain running environmentThe total number of the certain instruction adjusting structure is k1, wherein the total number of the second characteristic nodes of the certain instruction adjusting structure is extracted to be m1, the total number of the first characteristic nodes of the certain instruction adjusting structure is extracted to be m2, and m1+m2=k1; calculating the characteristic index of the certain instruction adjusting structure as beta= (m 1-m 2)/m 2, and judging beta>β Threshold value The instruction adjusting structure of (2) is a characteristic instruction adjusting structure; wherein beta is Threshold value Is a characteristic index threshold.
5. The method of claim 4, wherein the step S600 includes:
step S601: calculating an abnormality index α=d1/D for each first feature node in each reference storage record group; wherein D1 represents the total number of feature instruction adjustment structures included in each first feature node, and D represents the total number of instruction adjustment structures included in each first feature node; alpha Threshold value Is an abnormality index threshold;
step S602: when capturing a certain first characteristic node P g →P g+1 Satisfy alpha>α Threshold value Intercepting the operation of an electronic evidence acquisition end device by an electronic evidence acquisition personnel from a corresponding monitoring video sequence to execute P g+1 When the corresponding monitoring video sequence is used as a target monitoring video sequence, the target monitoring video sequence is fed back to a manager port, and improper operation of an electronic evidence acquisition person in the target monitoring video sequence is marked;
step S603: extracting all marked improper operations, and simultaneously acquiring acquisition environments corresponding to the improper operations to generate a supervision operation library; the acquisition environment comprises a corresponding electronic evidence acquisition task and a network operation environment of the electronic equipment for target acquisition.
6. A comprehensive analysis management system for executing a comprehensive analysis management method based on multidimensional data according to any one of claims 1 to 5, wherein the system comprises an electronic evidence collection management module, an electronic evidence information management module, a collection program adjustment rule analysis module, an instruction adjustment structure screening module and a collection monitoring and early warning module;
the electronic evidence collection management module is used for extracting task keywords from an electronic evidence collection task every time the electronic evidence collection management terminal receives an electronic evidence collection task, making an electronic evidence collection scheme according to the task keywords and the network operation environment of the target collection electronic equipment, generating an electronic evidence collection program according to the electronic evidence collection scheme, and automatically issuing the electronic evidence collection program to electronic evidence collection terminal equipment by utilizing the Internet of things; the electronic evidence collection terminal device extracts electronic evidence from electronic information stored or transmitted in the electronic device collected by the target by executing a corresponding operation instruction; monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence;
the electronic evidence information management module is used for receiving and analyzing the electronic evidence uploaded by the electronic evidence acquisition terminal equipment in real time by utilizing the Internet of things by the electronic evidence acquisition management terminal, determining whether to adjust the electronic evidence acquisition program according to the acquisition condition of the electronic evidence, and storing the electronic evidence which finally meets the requirements into an electronic evidence library; the adjustment comprises the steps of modifying the content of the operation instruction in the program and increasing or decreasing the operation instruction in the program;
the acquisition program adjustment rule analysis module is used for setting a historical electronic evidence storage record which is subjected to adjustment of the electronic evidence acquisition program executed by the electronic evidence acquisition terminal equipment as a first characteristic storage record, and setting a historical electronic evidence storage record which is not subjected to adjustment of the electronic evidence acquisition program executed by the electronic evidence acquisition terminal equipment as a second characteristic storage record; carding the adjustment rules presented on the electronic evidence collection program in all the second feature storage records and the first feature storage records;
the instruction adjustment structure screening module is used for extracting all instruction adjustment structures affecting the adjustment of the electronic evidence collection program, calculating characteristic indexes of the instruction adjustment structures, and screening the characteristic instruction adjustment structures affecting the adjustment of the electronic evidence collection program based on the characteristic indexes;
the acquisition monitoring early warning module is used for intercepting a target monitoring video sequence with improper operation of acquisition personnel according to the distribution condition of a characteristic instruction adjustment structure in each historical electronic evidence storage record, generating a monitoring operation library, and carrying out real-time monitoring early warning on the improper operation of the acquisition personnel based on the monitoring operation library.
7. The comprehensive analysis management system according to claim 6, wherein the electronic evidence collection management module comprises a collection execution unit and an information capturing unit;
the acquisition execution unit is used for extracting task keywords from an electronic evidence acquisition task every time the electronic evidence acquisition management terminal receives the electronic evidence acquisition task, making an electronic evidence acquisition scheme according to the task keywords and the network operation environment of the target acquisition electronic equipment, generating an electronic evidence acquisition program according to the electronic evidence acquisition scheme, and automatically issuing the electronic evidence acquisition program to electronic evidence acquisition terminal equipment by utilizing the Internet of things;
the information capturing unit is used for extracting electronic evidence from electronic information stored or transmitted in the electronic equipment collected by the target after the electronic evidence collection end equipment completes connection authorization with the electronic equipment collected by the target; and monitoring and recording the process of operating the electronic evidence acquisition terminal equipment by an electronic evidence acquisition personnel to obtain a corresponding monitoring video sequence.
8. The comprehensive analysis management system according to claim 6, wherein the instruction adjustment structure screening module comprises a characteristic index calculation unit, a characteristic instruction adjustment structure screening unit;
the characteristic index calculation unit is used for extracting all instruction adjustment structures affecting the adjustment of the electronic evidence collection program and calculating the characteristic index of each instruction adjustment structure;
the characteristic instruction adjusting structure screening unit is used for receiving the data in the characteristic index calculating unit and screening the characteristic instruction adjusting structure which influences the adjustment of the electronic evidence collecting program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311709724.9A CN117408644B (en) | 2023-12-13 | 2023-12-13 | Comprehensive analysis management system and method based on multidimensional data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311709724.9A CN117408644B (en) | 2023-12-13 | 2023-12-13 | Comprehensive analysis management system and method based on multidimensional data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117408644A CN117408644A (en) | 2024-01-16 |
| CN117408644B true CN117408644B (en) | 2024-02-09 |
Family
ID=89489385
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311709724.9A Active CN117408644B (en) | 2023-12-13 | 2023-12-13 | Comprehensive analysis management system and method based on multidimensional data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117408644B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110674534A (en) * | 2019-09-26 | 2020-01-10 | 杭州数蛙科技有限公司 | Remote quality detection technology based on Internet of things electronic evidence chain |
| CN112804310A (en) * | 2020-12-31 | 2021-05-14 | 河南中盾云安信息科技有限公司 | Multi-chain intelligent security gateway for application of Internet of things and implementation method |
| CN113722397A (en) * | 2021-08-25 | 2021-11-30 | 南京审计大学 | Electronic evidence collection system and method for big data audit |
| CN116257420A (en) * | 2023-03-14 | 2023-06-13 | 北京崇迅科技有限公司 | Computer intelligent regulation and control system and method based on data fusion |
| CN116909213A (en) * | 2022-08-29 | 2023-10-20 | 伟康科技机械(无锡)有限公司 | Automatic cable wiring control system and method based on Internet of things |
-
2023
- 2023-12-13 CN CN202311709724.9A patent/CN117408644B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110674534A (en) * | 2019-09-26 | 2020-01-10 | 杭州数蛙科技有限公司 | Remote quality detection technology based on Internet of things electronic evidence chain |
| CN112804310A (en) * | 2020-12-31 | 2021-05-14 | 河南中盾云安信息科技有限公司 | Multi-chain intelligent security gateway for application of Internet of things and implementation method |
| CN113722397A (en) * | 2021-08-25 | 2021-11-30 | 南京审计大学 | Electronic evidence collection system and method for big data audit |
| CN116909213A (en) * | 2022-08-29 | 2023-10-20 | 伟康科技机械(无锡)有限公司 | Automatic cable wiring control system and method based on Internet of things |
| CN116257420A (en) * | 2023-03-14 | 2023-06-13 | 北京崇迅科技有限公司 | Computer intelligent regulation and control system and method based on data fusion |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117408644A (en) | 2024-01-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111460252B (en) | Automatic search engine method and system based on network public opinion analysis | |
| CN110674840A (en) | Multi-party evidence association model construction method based on Bayesian network and evidence chain extraction method and device | |
| CN110287292B (en) | Judgment criminal measuring deviation degree prediction method and device | |
| CN110737821B (en) | Similar event query method, device, storage medium and terminal equipment | |
| WO2022222850A1 (en) | Multimedia content recognition method, related apparatus, device and storage medium | |
| CN111090813A (en) | Content processing method and device and computer readable storage medium | |
| CN112257740B (en) | Knowledge graph-based image hidden danger identification method and system | |
| CN101251857A (en) | Information storage and research | |
| CN117408644B (en) | Comprehensive analysis management system and method based on multidimensional data | |
| CN110532282A (en) | Data query method and device | |
| CN113946710A (en) | Video retrieval method based on multi-mode and self-supervision characterization learning | |
| CN114049508A (en) | Fraud website identification method and system based on picture clustering and manual research and judgment | |
| CN107590233A (en) | A kind of file management method and device | |
| CN111277433B (en) | Network service abnormity detection method and device based on attribute network characterization learning | |
| WO2023093783A1 (en) | Distributed recommendation method for mass digital information | |
| CN111444362A (en) | Malicious picture intercepting method, device, equipment and storage medium | |
| CN111597423A (en) | Performance evaluation method and device of interpretable method of text classification model | |
| JP3692416B2 (en) | Information filtering method and apparatus | |
| CN116069607A (en) | Mobile office user abnormal behavior detection method based on graph convolution neural network | |
| CN113177164A (en) | Multi-platform collaborative new media content monitoring and management system based on big data | |
| CN111428767A (en) | Data processing method and device, processor, electronic equipment and storage medium | |
| CN117274110B (en) | Image optimization method based on generation type artificial intelligence and graph neural network | |
| CN117540176B (en) | Data recovery analysis method and system based on solid state disk | |
| CN114491034B (en) | Text classification method and intelligent device | |
| CN110362703A (en) | A kind of regular processing method of picture and its system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |