CN113936313A - Method, device, equipment and storage medium for detecting account number lending of website employees - Google Patents
Method, device, equipment and storage medium for detecting account number lending of website employees Download PDFInfo
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Abstract
The invention relates to an artificial intelligence technology, and discloses a method for detecting the loan of an account number of a website employee, which comprises the following steps: acquiring a website employee monitoring video shot by monitoring equipment, analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot is located; carrying out snapshot face recognition by utilizing a pre-constructed network point staff face feature library to obtain staff information corresponding to the snapshot face; determining a matching time period according to the snapshot time, and inquiring account use data of the employee in different network areas in the matching time period; and matching the using data of the account with the network point region where the snapshot is located. In addition, the invention also relates to a block chain technology, and the employee face feature library and the snapshot face can be stored in the nodes of the block chain. The invention also provides a detection device, electronic equipment and a storage medium for the check-out of the account numbers of the network employees. The invention can improve the efficiency of employee account borrowing detection.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method and a device for detecting the account number lending of a website employee, electronic equipment and a computer readable storage medium.
Background
For a current business network such as a bank, for a business transaction which needs to be authorized and occurs at a certain network, whether an employee who has the business transaction in the system is really on duty or not and whether the business transaction performed by the employee on duty is operated by the employee or not can not be confirmed, and the situation that the employee illegally borrows an account number may occur.
Disclosure of Invention
The invention provides a method and a device for detecting account number lending of a website employee and a computer readable storage medium, and mainly aims to solve the problem that the account number is lended in violation of employees.
In order to achieve the above object, the invention provides a method for detecting the account number lending of a website employee, which comprises the following steps:
acquiring a monitoring video of a website employee shot by monitoring equipment, and analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot face is located;
carrying out face recognition on the snapshot face by utilizing a pre-constructed network point staff face feature library to obtain staff information corresponding to the snapshot face;
determining a matching time period according to the snapshot time, and inquiring whether account use data corresponding to the employee information exists in the website area or not according to the matching time period;
if account use data corresponding to the employee information is not inquired, judging that the employee account is not lent;
if account use data corresponding to the employee information is inquired, whether a website area where the face to be snapshotted is located is consistent with a website area where the account use data is located is judged;
if the network site area where the face is snapshotted is consistent with the network site area where the account use data is located, judging that the employee account is not lent;
and if the network point region where the face is snapshotted is not consistent with the network point region where the account use data is located, judging that the employee account is lent.
Optionally, before the obtaining of the monitoring video of the website employee captured by the monitoring device, the method further includes:
acquiring transaction data of each counter of a network point, and classifying the transaction data to obtain a plurality of transaction data types;
and carrying out region division on the network points according to the transaction data types to obtain different network point regions.
Optionally, the acquiring a monitoring video of a website employee captured by the monitoring device, analyzing the monitoring video to obtain a snapshot face, snapshot time, and acquiring a website area where the snapshot face is located includes:
shooting a monitoring video in a monitoring range by utilizing monitoring equipment installed in each network point area;
acquiring each frame of monitoring image in the monitoring video, and identifying the face of the staff at the website and the generation time of the monitoring image from the identification of each frame of monitoring image;
judging the time period of each website employee staying in the monitoring range according to the face of each website employee in each monitoring image and the generation time of the monitoring image;
and acquiring the last frame of monitoring image in the time period from the monitoring video, extracting the snapshot face and the snapshot time of the website staff, and acquiring the website area where the snapshot face is located according to the website area where the monitoring equipment is located.
Optionally, the performing face recognition on the snapshot face by using a pre-constructed website employee face feature library includes:
extracting a snapshot face feature set of the snapshot face;
carrying out similarity comparison on the snapshot face feature set and an employee face feature set in a pre-constructed website employee face feature library;
and acquiring the identity of the employee corresponding to the employee face feature set with the maximum similarity to obtain the employee information corresponding to the snapshot face.
Optionally, before the similarity comparison is performed between the snapshot facial feature set and the employee facial feature set in the pre-constructed website employee facial feature library, the method further includes:
acquiring pictures of different angles of the face of each employee of the website to obtain a face picture set of each website employee;
carrying out standardization processing on the face picture set of each website employee to obtain a standardized face picture set;
performing feature extraction on the standardized face picture set to obtain a face feature set of each website employee;
and integrating all the face feature sets to generate a website employee face feature library.
Optionally, the determining a matching time period according to the snapshot time, and querying whether the website area has account usage data corresponding to the employee information according to the matching time period includes:
determining a matching time period according to preset time periods before and after the snapshot time;
and inquiring whether account use data corresponding to the employee information exists in the matching time period.
Optionally, the determining whether the website area where the face of the snapshot is located is consistent with the website area where the account usage data is located includes:
account use data corresponding to the employee information are extracted, and a website area where the account use data are located is determined according to a data transaction type of the account use data;
and comparing the website area where the account use data is located with the website area where the face is snapshotted, and judging whether the website area where the account use data is located is consistent with the website area where the face is snapshotted.
In order to solve the above problem, the present invention further provides a device for detecting account lending of a website employee, wherein the device comprises:
the face snapshot module is used for acquiring the network point staff shot by the monitoring equipment, and analyzing the monitoring video to obtain a snapshot face, snapshot time and a network point area where the snapshot face is located;
the face recognition module is used for carrying out face recognition on the snapshot face by utilizing a pre-constructed website staff face feature library to obtain staff information corresponding to the snapshot face;
the account use data matching module is used for inquiring whether the website area has account use data corresponding to the employee information according to the matching time period;
and the website area matching module is used for judging whether the website area where the face is snapshotted is consistent with the website area where the account use data is located if the account use data corresponding to the employee information is inquired.
In order to solve the above problem, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the website employee account lending detection method described above.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, where at least one computer program is stored, where the at least one computer program is executed by a processor in an electronic device to implement the method for detecting a check-out of an account of an employee of a website.
The embodiment of the invention carries out face snapshot through the monitoring equipment arranged in different website areas, carries out face snapshot recognition by utilizing the constructed website staff face feature library to obtain staff information corresponding to the snapshot face, can timely acquire the website area where the staff is located on the same day, and further improves the efficiency of staff account number lending detection; the account use data of the employee in different website areas are obtained, whether the website area where the face snapshot is located is consistent with the website area where the employee account use data is located in the matching time period is judged, detection of employee account lending can be achieved, and therefore detection efficiency of employee account lending is improved. Therefore, the method, the device, the electronic equipment and the computer readable storage medium for detecting the employee account lending of the website can solve the problem of low employee account lending detection efficiency.
Drawings
Fig. 1 is a schematic flow chart of a method for detecting a loan of an account of an employee of a website according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of snapshot face recognition according to an embodiment of the present invention;
fig. 3 is a functional block diagram of a device for detecting the account number lending of a website employee according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device for implementing the method for detecting employee account lending at a website according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a method for detecting the loan of an account number of a website employee. An executing subject of the network employee account lending detection method includes, but is not limited to, at least one of electronic devices that can be configured to execute the method provided by the embodiment of the present application, such as a server and a terminal. In other words, the website employee account loan detection method may be executed by software or hardware installed in a terminal device or a server device, where the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Fig. 1 is a schematic flow chart of a method for detecting the loan of an account of an employee at a website according to an embodiment of the present invention. In this embodiment, the method for detecting the employee account lending at the website includes:
s1, acquiring a monitoring video of a website employee shot by monitoring equipment, and analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot face is located;
in the embodiment of the invention, different network areas, such as cash register areas, are arranged at the bank network according to different over-the-counter transaction types, so that a customer can autonomously carry out cash transaction; for example, the low cabinet area can be used for the client to carry out the transactions of the company business, various independent investments, financing and other public businesses, and is not specific to the individual user. The monitoring equipment can be arranged in each dot region and embedded with a convolutional neural network, can automatically identify the face and take a snapshot, and marks the snapshot time of the snapshot face and the dot region where the snapshot face monitoring equipment is located.
In an embodiment of the present invention, before the obtaining of the monitoring video of the website employee captured by the monitoring device, the method may further include:
acquiring transaction data of each counter of a network point, and classifying the transaction data to obtain a plurality of transaction data types;
and carrying out region division on the network points according to the transaction data types to obtain different network point regions. Specifically, the transaction data of each counter of the website includes but is not limited to cash transaction, bus transaction and private transaction. The embodiment of the invention classifies the transaction data to obtain a plurality of transaction data subsets, and the network points are divided into regions according to the transaction data subsets. For example, the mesh points may be divided into FB zones, cash register zones, high bay zones, low bay zones, VIP high bay zones, etc., based on the transaction data subsets.
Further, the acquiring of the monitoring video of the website staff shot by the monitoring device, analyzing the monitoring video to obtain the snapshot face, the snapshot time and the website area where the snapshot face is located includes:
shooting a monitoring video in a monitoring range by utilizing monitoring equipment installed in each network point area;
acquiring each frame of monitoring image in the monitoring video, and identifying the face of the staff at the website and the generation time of the monitoring image from the identification of each frame of monitoring image;
judging the time period of each website employee staying in the monitoring range according to the face of each website employee in each monitoring image and the generation time of the monitoring image;
and acquiring the last frame of monitoring image in the time period from the monitoring video, extracting the snapshot face and the snapshot time of the website staff, and acquiring the website area where the snapshot face is located according to the website area where the monitoring equipment is located. In the embodiment of the invention, each monitoring device is utilized to judge the time period of each website employee staying in the monitoring range of the monitoring device, and the snapshot face and the snapshot time of the website employee are extracted from the last frame of monitoring image in the time period, so that the repeated face snapshot of the same website employee is avoided, and the efficiency of subsequent face snapshot recognition can be improved.
S2, carrying out face recognition on the snap-shot face by using a pre-constructed network employee face feature library to obtain employee information corresponding to the network employee;
in detail, referring to fig. 2, the performing face recognition on the captured face by using the pre-constructed website employee face feature library includes:
s21, extracting a snapshot face feature set of the snapshot face;
s22, carrying out similarity comparison on the snapshot face feature set and staff face feature sets in a pre-constructed website staff face feature library;
and S23, acquiring the employee identity corresponding to the employee face feature set with the maximum similarity, and acquiring the employee information corresponding to the snapshot face.
For example, if the similarity between the snapshot face feature set and the face feature set of the pre-constructed website employee a is 80%, the similarity between the snapshot face feature set and the face feature set of the employee B is 75%, and the similarity between the snapshot face feature set and the face feature set of the employee C is 95%, the employee identity corresponding to the face feature set of the employee C is acquired, and the employee information corresponding to the snapshot face is obtained.
In an embodiment of the present invention, before the S2, the method may further include:
acquiring pictures of different angles of the face of each employee of the website to obtain a face picture set of each website employee;
carrying out standardization processing on the face picture set of each website employee to obtain a standardized face picture set;
performing feature extraction on the standardized face picture set to obtain a face feature set of each website employee;
and integrating all the face feature sets to generate a website employee face feature library.
In the embodiment of the present invention, the standardizing the face pictures of the employees to obtain a standardized face picture set includes:
carrying out picture size normalization processing on pictures in the staff face picture set to obtain a first picture set;
and performing picture pixel correction on the pictures in the first picture set to obtain a standardized face picture set.
Further, the performing picture size normalization processing on the pictures in the staff face picture set to obtain a first picture set includes:
acquiring the picture sizes of a plurality of staff picture sets in the network staff face picture set;
respectively calculating the average sizes of the pictures of the plurality of employee picture sets in the website employee picture set;
determining the median of the average sizes of all the pictures in the plurality of employee picture sets to be a target size, and scaling the pictures in the plurality of employee picture sets to the target size.
Further, the performing picture pixel correction on the pictures in the first picture set to obtain a standardized face picture set includes:
traversing all pixel points in the network point employee picture set and acquiring pixel values;
if the pixel value is larger than a first preset threshold value, modifying the pixel value of the pixel point into the first pixel threshold value;
and if the pixel value is smaller than a second pixel value, modifying the pixel value of the pixel point into the second pixel threshold value.
In the embodiment of the invention, because the images in the first image set may have an over-dark or over-exposure condition, which is not beneficial to the subsequent face recognition according to the images, the images in the first image set are subjected to pixel mean value correction, that is, the pixel values of the pixel points in the first image set are limited in a specific range, so that the over-dark or over-exposure condition is avoided, and the accuracy of the subsequent face recognition is improved.
Further, the performing feature extraction on the standardized face picture set includes:
performing convolution processing on the standardized face picture set to obtain a convolution image set;
and carrying out global pooling on the convolution image set to obtain a face feature set.
Because the standardized face picture set contains a large amount of pixel information, the standardized face picture set is directly utilized to carry out face recognition, a large amount of computing time and resources are occupied, and the recognition efficiency is low; however, the convolved pixel features still have multi-dimensional conditions, and the embodiment of the invention can further reduce the dimensions of the pixel features by utilizing global pooling, reduce the occupation of computing resources when subsequently analyzing the face feature set, and improve the analysis efficiency.
In another embodiment of the present invention, the method further comprises: and dynamically updating the network staff face feature library in an incremental manner by adopting the following method:
acquiring a face picture of a newly added employee, and extracting the features of the newly added face in the face picture of the newly added employee;
if staff face features with the similarity exceeding a preset threshold exist in the staff face feature library, staff face features with the similarity exceeding the preset threshold are removed, the new face features are added into the staff face feature library, and an updated staff face feature library is obtained;
and if the employee face features with the similarity exceeding a preset threshold do not exist in the employee face feature library, directly adding the newly added face features into the employee face feature library to obtain an updated employee face feature library.
In the embodiment of the invention, the network station employee face feature library is utilized to carry out face recognition to obtain the employee information corresponding to the snapshot face, so that whether the employee is on duty on the day, the time of the employee on duty on the day and the network station area where the employee is on duty can be confirmed in real time, and the detection efficiency of the employee account number lending condition is improved.
S3, determining a matching time period according to the snapshot time, and inquiring whether the website area has account use data corresponding to the employee information according to the matching time period;
in the embodiment of the present invention, the matching time period is determined according to the snapshot time, and whether account usage data corresponding to the employee information exists in the matching time period may be determined as the matching time period according to a preset time period before and after the snapshot time, for example, the previous 10 minutes and the 10 minutes after the snapshot time, where the preset time period may be determined according to a duration of account usage.
In detail, the determining a matching time period according to the snapshot time, and querying whether the website area has account usage data corresponding to the employee information according to the matching time period includes:
determining a matching time period according to preset time periods before and after the snapshot time;
and inquiring whether account use data corresponding to the employee information exists in the matching time period.
For example, if the snapshot time is 14:21:14 at 11/8/2021, the matching time period is 14:11:14 at 11/8/2021 to 14:31:14 at 11/8/2021, the employee information obtained by matching the snapshot face is an XX account 153xxxxxx, and no account usage data of the account in the matching time period is obtained through query.
If the account use data corresponding to the employee information is not inquired, S4, judging that the employee account is not lent;
in the embodiment of the invention, if account use data corresponding to the employee information is not inquired, that is, the account corresponding to the employee information is not used in the matching time period, the account corresponding to the employee information in the matching time period is an outsourcing account.
If the account use data corresponding to the employee information is inquired, S5, judging whether the website area where the face is snapshotted is consistent with the website area where the account use data is located;
in the embodiment of the present invention, if account usage data corresponding to the employee information is queried, that is, if an account corresponding to the employee information has usage data in the website in the matching time period, it needs to be further determined whether a website area where the face to be snapshotted is located is consistent with a website area where the account is used.
In detail, the determining whether the website area where the face of the snapshot is located is consistent with the website area where the account usage data is located includes:
account use data corresponding to the employee information are extracted, and a website area where the account use data are located is determined according to a data transaction type of the account use data;
and comparing the website area where the account use data is located with the website area where the face is snapshotted, and judging whether the website area where the account use data is located is consistent with the website area where the face is snapshotted.
In the embodiment of the invention, whether the website area where the account use data is located is consistent with the website area where the face is snapshotted is judged by comparing the website area where the account use data is located with the website area where the face is snapshotted, so that the accuracy of employee account borrowing detection can be improved.
If the network point region where the face is snapped is consistent with the network point region where the account use data is located, S4 is executed, and the employee account is judged not to be lent;
in the embodiment of the invention, if the region where the face is snapshotted is inconsistent with the website region where the employee account number transaction data is located, the employee account number transaction data is not generated by the operation of the employee himself, and the employee account number is lent.
And if the network point region where the face is snapped is not consistent with the network point region where the account use data is located, S6, the employee account is judged to be lent.
In the embodiment of the invention, if the area where the face is snapshotted is consistent with the website area where the employee account transaction data is located, the employee account is not lent.
In another embodiment of the invention, if the employee account number lending condition is that the employee does not arrive on duty on the same day, but the website transaction data contains the employee account number transaction data, the employee illegally borrows the account number, the website checks the website transaction data after the daily work is finished, retrieves the employee account number transacted on the same day according to the transaction data and matches the employee face snapshotted on the same day, and if the employee account number use data on the same day is retrieved, but the employee face information is not snapshotted by the monitoring equipment on the same day, the employee does not arrive on duty on the same day, and the account number is lent.
The embodiment of the invention carries out face snapshot through the monitoring equipment arranged in different website areas, carries out face snapshot recognition by utilizing the constructed website staff face feature library to obtain staff information corresponding to the snapshot face, can timely acquire the website area where the staff is located on the same day, and further improves the efficiency of staff account number lending detection; the account use data of the employee in different website areas are obtained, whether the website area where the face snapshot is located is consistent with the website area where the employee account use data is located in the matching time period is judged, detection of employee account lending can be achieved, and therefore detection efficiency of employee account lending is improved. Therefore, the method for detecting the employee account lending of the website can solve the problem of low employee account lending detection efficiency.
Fig. 3 is a functional block diagram of a device for detecting account lending of employees at websites according to an embodiment of the present invention.
The device 100 for detecting the employee account number loan of the website can be installed in electronic equipment. According to the realized functions, the website employee account lending detection device 100 may include a face snapshot module 101, a face recognition module 102, an account usage data matching module 103, and a website region matching module 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the face snapshot module 101 is configured to acquire a monitoring video of a website employee, which is obtained by shooting with a monitoring device, analyze the monitoring video to obtain a snapshot face, snapshot time, and acquire a website area where the snapshot face is located;
the face recognition module 102 is configured to perform face recognition on the snapshot face by using a pre-constructed website employee face feature library to obtain employee information corresponding to the snapshot face;
the account use data matching module 103 is configured to query whether the website area has account use data corresponding to the employee information according to the matching time period;
the website area matching module 104 is configured to determine whether a website area where the snapshot face is located is consistent with a website area where the account usage data is located if account usage data corresponding to the employee information is queried.
In detail, when used, each module in the website employee account lending detection apparatus 100 in the embodiment of the present invention adopts the same technical means as the website employee account lending detection method described in fig. 1 to fig. 2, and can produce the same technical effect, which is not described herein again.
Fig. 4 is a schematic structural diagram of an electronic device for implementing a method for detecting account lending of employees at a website according to an embodiment of the present invention.
The electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may further include a computer program, such as a website employee account lending detection program, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit of the electronic device, connects various components of the whole electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (for example, executing a website employee account loan detection program and the like) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in the electronic device and various data, such as codes of a website employee account loan detection program, but also temporarily store data that has been output or is to be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
Fig. 4 only shows an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 4 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The website employee account lending detection program stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, and when running in the processor 10, can implement:
acquiring a monitoring video of a website employee, which is shot by a monitoring device, analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot face is located;
carrying out face recognition on the snapshot face by utilizing a pre-constructed network point staff face feature library to obtain staff information corresponding to the snapshot face;
determining a matching time period according to the snapshot time, and inquiring whether account use data corresponding to the employee information exists in the website area or not according to the matching time period;
if account use data corresponding to the employee information is not inquired, judging that the employee account is not lent;
if account use data corresponding to the employee information is inquired, whether a website area where the face to be snapshotted is located is consistent with a website area where the account use data is located is judged;
if the network site area where the face is snapshotted is consistent with the network site area where the account use data is located, judging that the employee account is not lent;
and if the network point region where the face is snapshotted is not consistent with the network point region where the account use data is located, judging that the employee account is lent.
Specifically, the specific implementation method of the instruction by the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to the drawings, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring a monitoring video of a website employee, which is shot by a monitoring device, analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot face is located;
carrying out face recognition on the snapshot face by utilizing a pre-constructed network point staff face feature library to obtain staff information corresponding to the snapshot face;
determining a matching time period according to the snapshot time, and inquiring whether account use data corresponding to the employee information exists in the website area or not according to the matching time period;
if account use data corresponding to the employee information is not inquired, judging that the employee account is not lent;
if account use data corresponding to the employee information is inquired, whether a website area where the face to be snapshotted is located is consistent with a website area where the account use data is located is judged;
if the network site area where the face is snapshotted is consistent with the network site area where the account use data is located, judging that the employee account is not lent;
and if the network point region where the face is snapshotted is not consistent with the network point region where the account use data is located, judging that the employee account is lent.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A method for detecting account lending of a website employee is characterized by comprising the following steps:
acquiring a monitoring video of a website employee, which is shot by a monitoring device, analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot face is located;
carrying out face recognition on the snapshot face by utilizing a pre-constructed network point staff face feature library to obtain staff information corresponding to the snapshot face;
determining a matching time period according to the snapshot time, and inquiring whether account use data corresponding to the employee information exists in the website area or not according to the matching time period;
if account use data corresponding to the employee information is not inquired, judging that the employee account is not lent;
if account use data corresponding to the employee information is inquired, whether a website area where the face to be snapshotted is located is consistent with a website area where the account use data is located is judged;
if the network site area where the face is snapshotted is consistent with the network site area where the account use data is located, judging that the employee account is not lent;
and if the network point region where the face is snapshotted is not consistent with the network point region where the account use data is located, judging that the employee account is lent.
2. The method for detecting the debit of the account of the website employee as claimed in claim 1, wherein before the step of obtaining the monitoring video of the website employee captured by the monitoring device, the method further comprises:
acquiring transaction data of each counter of a network point, and classifying the transaction data to obtain a plurality of transaction data types;
and carrying out region division on the network points according to the transaction data types to obtain different network point regions.
3. The website employee account lending detection method according to claim 2, wherein the acquiring of the monitoring video of the website employee captured by the monitoring device, the analyzing of the captured face, the capturing time and the acquiring of the website area where the captured face is located from the monitoring video comprises: shooting a monitoring video in a monitoring range by utilizing monitoring equipment installed in each network point area;
acquiring each frame of monitoring image in the monitoring video, and identifying the face of the staff at the website and the generation time of the monitoring image from the identification of each frame of monitoring image;
judging the time period of each website employee staying in the monitoring range according to the face of each website employee in each monitoring image and the generation time of the monitoring image;
and acquiring the last frame of monitoring image in the time period from the monitoring video, extracting the snapshot face and the snapshot time of the website staff, and acquiring the website area where the snapshot face is located according to the website area where the monitoring equipment is located.
4. The website employee account lending detection method according to claim 1, wherein the face recognition of the face captured by using the pre-constructed website employee face feature library comprises:
extracting a snapshot face feature set of the snapshot face;
carrying out similarity comparison on the snapshot face feature set and an employee face feature set in a pre-constructed website employee face feature library;
and acquiring the identity of the employee corresponding to the employee face feature set with the maximum similarity to obtain the employee information corresponding to the snapshot face.
5. The website employee account lending detection method of claim 4, wherein before the similarity comparison between the snapshot facial feature set and the employee facial feature set in the pre-constructed website employee facial feature library, the method further comprises:
acquiring pictures of different angles of the face of each employee of the website to obtain a face picture set of each website employee;
carrying out standardization processing on the face picture set of each website employee to obtain a standardized face picture set;
performing feature extraction on the standardized face picture set to obtain a face feature set of each website employee;
and integrating all the face feature sets to generate a website employee face feature library.
6. The website employee account lending detection method according to claim 1, wherein the determining a matching time period according to the snapshot time, and querying whether account usage data corresponding to the employee information exists in different website areas according to the matching time period comprises:
determining a matching time period according to preset time periods before and after the snapshot time;
and inquiring whether account use data corresponding to the employee information exists in the matching time period.
7. The method for detecting account lending of a website employee according to claim 1, wherein the step of judging whether the website area where the face snapshot is located is consistent with the website area where the account usage data is located comprises the steps of:
account use data corresponding to the employee information are extracted, and a website area where the account use data are located is determined according to a data transaction type of the account use data;
and comparing the website area where the account use data is located with the website area where the face is snapshotted, and judging whether the website area where the account use data is located is consistent with the website area where the face is snapshotted.
8. A detection device for account number lending of network staff is characterized by comprising:
the face snapshot module is used for acquiring a monitoring video of the website staff, which is shot by the monitoring equipment, analyzing the monitoring video to obtain a snapshot face, snapshot time and a website area where the snapshot face is located;
the face recognition module is used for carrying out face recognition on the snapshot face by utilizing a pre-constructed website staff face feature library to obtain staff information corresponding to the snapshot face;
the account use data matching module is used for inquiring whether the website area has account use data corresponding to the employee information according to the matching time period;
and the website area matching module is used for judging whether the website area where the face is snapshotted is consistent with the website area where the account use data is located if the account use data corresponding to the employee information is inquired.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform a method of website employee account lending detection as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements a method for detecting a check-out of a website employee account loan according to any one of claims 1 to 7.
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