CN116342151B - Monetary payment device amount tampering detection system - Google Patents
Monetary payment device amount tampering detection system Download PDFInfo
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- CN116342151B CN116342151B CN202310389777.0A CN202310389777A CN116342151B CN 116342151 B CN116342151 B CN 116342151B CN 202310389777 A CN202310389777 A CN 202310389777A CN 116342151 B CN116342151 B CN 116342151B
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- 238000001514 detection method Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 claims abstract description 11
- 230000003203 everyday effect Effects 0.000 claims abstract description 4
- 230000000875 corresponding effect Effects 0.000 claims description 26
- 238000003062 neural network model Methods 0.000 claims description 13
- 238000013507 mapping Methods 0.000 claims description 8
- 230000002596 correlated effect Effects 0.000 claims description 7
- 238000009825 accumulation Methods 0.000 claims description 6
- 238000013528 artificial neural network Methods 0.000 claims description 4
- 238000012549 training Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 abstract description 3
- 238000013461 design Methods 0.000 abstract description 2
- 230000002354 daily effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 6
- 230000008901 benefit Effects 0.000 description 5
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 230000010076 replication Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
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- 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
- G06Q30/00—Commerce
- G06Q30/018—Certifying business or products
- G06Q30/0185—Product, service or business identity fraud
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
Abstract
The invention relates to a financial payment device amount tampering detection system, comprising: the tamper analysis mechanism is used for sending a tamper early warning signal when the absolute value of the difference value between the income amount value in the set time interval accumulated by the financial payment device and the predicted income amount in the set time interval is larger than or equal to a set absolute value threshold value, and the financial payment device executes the account reporting of the total daily income amount at the set time every day; and the information analysis component is used for intelligently identifying the predicted income amount in the set time interval of the financial payment device. The monetary amount tampering detection system of the financial payment device is reliable in design and stable in operation. The method can identify the predicted financial payment data of the financial payment device in each time interval, and execute corresponding tamper early warning processing when the financial payment data of the actually reported time interval is matched with the predicted financial payment data, thereby ensuring the authenticity of the detail financial payment data reported by the financial payment device.
Description
Technical Field
The invention relates to the field of financial payment, in particular to a system for detecting the amount tampering of a financial payment device.
Background
Unmanned vending devices are favored by merchants because of the following advantages:
1) Unattended operation: the unmanned vending device is generally unattended for 24 hours, so that the unmanned vending device has two benefits, namely, the unmanned vending device can be operated without rest all the year round, the sales amount is enlarged, and the unmanned vending device has the other benefit of saving labor cost and staff wages.
2) Small occupation area and low rent: the unmanned vending device is smaller than the machine, and generally occupies 2 square and 3 square, so that the selectable placement positions can be quite large, the occupied area is small, and the renting of a plurality of stores is saved.
3) Fast replication: owing to the first two advantages, the unmanned vending device can be quickly copied, and related industries can also quickly copy. For example, the unmanned vending device can be placed in each office, or in each underground garage, foreground hall and the like.
However, the unmanned vending apparatus as the financial payment apparatus brings the advantages, and meanwhile, the unmanned financial payment environment brings the problems that, for example, since the unmanned vending apparatus often adopts an operation mechanism of time interval accounting and once reporting of sales amount throughout the day, the possibility of tampering sales data by staff on site or remotely exists, the staff can obtain considerable income every day without tampering the sales amount throughout the day, and only the financial payment data of a single or a plurality of time intervals is tampered.
Disclosure of Invention
In order to overcome the technical problems in the prior art, the invention provides a system for detecting the amount tampering of a financial payment device, which can intelligently identify predicted financial payment data of the financial payment device in a set time interval according to financial payment data of each historical time interval of the set time interval and multiple items of configuration information of the financial payment device in an unmanned vending environment, and execute corresponding tampering early warning processing when the actually reported financial payment data in the set time interval is in mismatch with the predicted financial payment data in the set time interval, thereby ensuring the authenticity of detail financial payment data reported by the financial payment device and reducing economic losses of sellers and managers.
According to an aspect of the present invention, there is provided a financial payment device amount tamper detection system, the system comprising:
an amount accumulation mechanism, which is arranged in the financial payment device and is used for accumulating the income amount value of the financial payment device in a set time interval, wherein the financial payment device is arranged in an unmanned vending place and executes account reporting of the total number of income amounts per day at a set time per day;
the tampering analysis mechanism is connected with the money accumulation mechanism and is used for sending a tampering early warning signal and marking the set time interval as a suspected tampering interval when the absolute value of the difference value between the income money value in the accumulated set time interval and the predicted income money in the set time interval is larger than or equal to a set absolute value threshold;
the content input mechanism is arranged in the financial payment device and is used for inputting a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set by the financial payment device before the set time interval;
the data detection mechanism is used for acquiring the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number of the financial payment device, the number of the resident personnel in the unmanned vending place, the distance from the financial payment device to the nearest other financial payment devices and the historical time interval of the financial payment device;
an information analysis unit, which is respectively connected with the tampering analysis mechanism and the data detection mechanism, and is used for intelligently identifying the predicted income amount in the set time interval of the financial payment device by adopting a feedforward neural network model based on a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total number set by the financial payment device before the set time interval, the number of commodity types in sale of the financial payment device, the number of normal living people in an unmanned vending place, the distance from the nearest other financial payment device and the maximum value and the minimum value of sales amount in the historical time interval of the financial payment device;
wherein, entering a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set before the set time interval of the financial payment device comprises: the value of the set total number is monotonically and positively correlated with the number of the on-sale commodity types of the financial payment device.
The monetary amount tampering detection system of the financial payment device is reliable in design and stable in operation. The method can identify the predicted financial payment data of the financial payment device in each time interval, and execute corresponding tamper early warning processing when the financial payment data of the actually reported time interval is matched with the predicted financial payment data, thereby ensuring the authenticity of the detail financial payment data reported by the financial payment device.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings, in which:
fig. 1 is a schematic diagram showing an internal configuration of a financial payment device amount tamper detection system according to embodiment a of the present invention.
Fig. 2 is a schematic diagram showing an internal configuration of a financial payment device amount tamper detection system according to embodiment B of the present invention.
Fig. 3 is a schematic diagram showing an internal configuration of a financial payment device amount tamper detection system according to embodiment C of the present invention.
Detailed Description
An embodiment of the money tamper detection system for a financial payment device according to the present invention will be described in detail with reference to the accompanying drawings.
Example 1
Fig. 1 is a schematic diagram showing an internal configuration of a system for detecting tampering with an amount of a financial payment device according to embodiment a of the present invention, the system comprising:
an amount accumulation mechanism, which is arranged in the financial payment device and is used for accumulating the income amount value of the financial payment device in a set time interval, wherein the financial payment device is arranged in an unmanned vending place and executes account reporting of the total number of income amounts per day at a set time per day;
the tampering analysis mechanism is connected with the money accumulation mechanism and is used for sending a tampering early warning signal and marking the set time interval as a suspected tampering interval when the absolute value of the difference value between the income money value in the accumulated set time interval and the predicted income money in the set time interval is larger than or equal to a set absolute value threshold;
for example, different marking processes may be performed for the set time interval with different binary values;
the content input mechanism is arranged in the financial payment device and is used for inputting a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set by the financial payment device before the set time interval;
the content input mechanism is internally provided with a dynamic storage chip for storing a plurality of income amount values corresponding to a plurality of historical time intervals of the total set number of the financial payment device before the set time interval;
the data detection mechanism is used for acquiring the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number of the financial payment device, the number of the resident personnel in the unmanned vending place, the distance from the financial payment device to the nearest other financial payment devices and the historical time interval of the financial payment device;
an information analysis unit, which is respectively connected with the tampering analysis mechanism and the data detection mechanism, and is used for intelligently identifying the predicted income amount in the set time interval of the financial payment device by adopting a feedforward neural network model based on a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total number set by the financial payment device before the set time interval, the number of commodity types in sale of the financial payment device, the number of normal living people in an unmanned vending place, the distance from the nearest other financial payment device and the maximum value and the minimum value of sales amount in the historical time interval of the financial payment device;
wherein, entering a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set before the set time interval of the financial payment device comprises: the value of the set total number is monotonically and positively correlated with the number of the on-sale commodity types of the financial payment device.
It can be seen that the present invention has at least the following three important inventions:
firstly, facing a financial payment device arranged at an unmanned vending place, intelligently predicting the predicted accumulated sales amount of the financial payment device set time interval according to the accumulated sales amounts of the financial payment device corresponding to the past time intervals of the financial payment device set time interval and the payment environment data of the financial payment device;
secondly, the executed intelligent prediction is based on a feedforward neural network, and the value of the number of each past time interval is monotonically and positively correlated with the number of the on-sale commodity types of the financial payment device, so that the reliability of an intelligent prediction result is ensured;
and when the absolute value of the difference value between the actual sales amount of the financial payment device in the set time interval and the predicted accumulated sales amount of the financial payment device in the set time interval is larger than or equal to the set absolute value threshold, a tamper early warning signal is sent out, and the set time interval is marked as a suspected tamper interval, so that the effective verification of the authenticity of the sales amount of each set time interval in each day is realized, and the probability of occurrence of the financial payment data tamper phenomenon is reduced.
Example 2
Fig. 2 is a schematic diagram showing an internal configuration of a financial payment device amount tamper detection system according to embodiment B of the present invention.
Unlike fig. 1, the financial payment device amount tamper detection system of fig. 2 may further include the following components:
the real-time display component is connected with the tampering analysis mechanism and is used for acquiring marks corresponding to each time interval and respectively executing mark type display operation on each time interval on a time axis;
the real-time display part may be a liquid crystal display screen or a touch display screen, for example;
the method for obtaining the marks corresponding to each time interval and respectively executing the mark type display operation on each time interval on the time axis comprises the following steps: when a certain time interval on the time axis has a mark of a suspected falsified interval, carrying out red highlighting on the time interval on the time axis;
the method for obtaining the marks corresponding to each time interval and respectively executing the mark type display operation on each time interval on the time axis comprises the following steps: when a certain time interval has a mark of a money reliable interval on the time axis, blue low-brightness display is carried out on the time interval on the time axis.
Example 3
Fig. 3 is a schematic diagram showing an internal configuration of a financial payment device amount tamper detection system according to embodiment C of the present invention.
Unlike fig. 1, the financial payment device amount tamper detection system of fig. 3 may further include the following components:
the time division communication part is connected with the tampering analysis mechanism and is used for wirelessly transmitting a tampering early warning signal and simultaneously wirelessly transmitting a set time interval marked as a suspected tampering interval;
and the parameter storage component is connected with the information analysis component and used for storing various model parameters of the feedforward neural network model.
Next, a specific configuration of the system for detecting tampering with an amount of money in a financial payment device according to the present invention will be further described.
In the financial payment device amount falsification detection system according to various embodiments of the present invention:
intelligently identifying the predicted income amount in the set time interval of the financial payment device based on a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set number of the financial payment device before the set time interval, the number of commodity types sold by the financial payment device, the number of resident people in the unmanned vending place, the distance to other financial payment devices recently, and the maximum value and minimum value of sales amount of the historical time interval of the financial payment device by adopting a feedforward neural network model comprises: the feedforward neural network model is a feedforward neural network after training for a plurality of times, and the training times are positively correlated with the number of people in the unmanned vending place.
In the financial payment device amount falsification detection system according to various embodiments of the present invention:
intelligently identifying the predicted income amount in the set time interval of the financial payment device based on a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set number of the financial payment device before the set time interval, the number of commodity types sold by the financial payment device, the number of resident people in the unmanned vending place, the distance to other financial payment devices recently, and the maximum value and minimum value of sales amount of the historical time interval of the financial payment device by adopting a feedforward neural network model comprises: and the financial payment device sets a plurality of income amount values corresponding to a plurality of historical time intervals of the total number before the set time interval, the number of commodity types in sale of the financial payment device, the number of resident personnel in the unmanned vending place, the distance from the nearest other financial payment devices and the maximum value and minimum value of sales amount of the historical time intervals of the financial payment device as item-by-item input data of the feedforward neural network model.
In the financial payment device amount falsification detection system according to various embodiments of the present invention:
the entering of a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set by the financial payment device before the set time interval comprises the following steps: setting a time interval, wherein the time duration occupied by each time interval in a plurality of historical time intervals of the set total number before the set time interval is the same;
wherein, entering a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set before the set time interval of the financial payment device comprises: setting a time interval and setting a plurality of historical time intervals of total number before the time interval to jointly occupy a complete time segment;
wherein the monotonic forward association of the value of the set total number and the number of the on-sale commodity types of the financial payment device comprises: and adopting a numerical mapping formula to represent the numerical mapping relation of monotonically and positively correlated value of the set total number and the number of commodity types in sale of the financial payment device, wherein the value of the set total number is an input item of the numerical mapping formula, and the number of commodity types in sale of the financial payment device is an output item of the numerical mapping formula.
In the financial payment device amount falsification detection system according to various embodiments of the present invention:
the method for obtaining the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number, the number of resident personnel in the unmanned vending place, the distance from the financial payment device to the nearest other financial payment devices and the historical time interval of the financial payment device comprises the following steps: when the sales amount value of a single time interval exists before the set time interval, taking the sales amount value of the single time interval as the sales amount maximum value;
the method for obtaining the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number, the resident personnel number in the unmanned vending place, the distance to other financial payment devices recently and the financial payment device history time interval comprises the following steps: and when the sales amount value of the single time interval exists before the set time interval, taking the sales amount value of the single time interval as the sales amount minimum value.
And in a financial payment device amount tamper detection system according to various embodiments of the present invention:
the tamper analysis mechanism is further used for marking the set time interval as an amount reliable interval when the absolute value of the difference value between the accumulated income amount value in the set time interval and the predicted income amount in the set time interval is smaller than the set absolute value threshold;
wherein, accumulate the income amount value of the financial payment device in the settlement time interval, the financial payment device sets up in unmanned place of sale and carries out the account of reporting of income amount total number of each day every day settlement time includes: the setting time of each day is twelve hours per day in the early morning.
In addition, in the system for detecting the tampering of the amount of money of the financial payment device, intelligently identifying the predicted amount of income in the set time interval of the financial payment device based on a plurality of amount of income corresponding to a plurality of historical time intervals of the total set number of time intervals before the set time interval of the financial payment device, the number of sales personnel in the sales location of the financial payment device, the distance to the nearest other financial payment device, and the maximum value and the minimum value of sales amount of the historical time interval of the financial payment device by using a feedforward neural network model includes: and the financial payment device sets the predicted income amount in the time interval as single output data of the feedforward neural network model.
While examples of embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various other modifications may be made, and equivalents may be substituted, without departing from the true scope of the invention. In addition, many modifications may be made to adapt a particular situation to the teachings of the invention without departing from the inventive concepts described herein. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (6)
1. A financial payment device amount tamper detection system, the system comprising:
an amount accumulation mechanism, which is arranged in the financial payment device and is used for accumulating the income amount value of the financial payment device in a set time interval, wherein the financial payment device is arranged in an unmanned vending place and executes account reporting of the total number of income amounts per day at a set time per day;
the tampering analysis mechanism is connected with the money accumulation mechanism and is used for sending a tampering early warning signal and marking the set time interval as a suspected tampering interval when the absolute value of the difference value between the income money value in the accumulated set time interval and the predicted income money in the set time interval is larger than or equal to a set absolute value threshold;
the content input mechanism is arranged in the financial payment device and is used for inputting a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set by the financial payment device before the set time interval;
wherein, the time interval is set and the time duration occupied by each time interval in the plurality of historical time intervals of the set total number before the time interval is set is the same;
wherein, the set time interval and a plurality of history time intervals of the set total number before the set time interval together occupy a complete time segment;
the data detection mechanism is used for acquiring the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number of the financial payment device, the number of the resident personnel in the unmanned vending place, the distance from the financial payment device to the nearest other financial payment devices and the historical time interval of the financial payment device;
an information analysis unit, which is respectively connected with the tampering analysis mechanism and the data detection mechanism, and is used for intelligently identifying the predicted income amount in the set time interval of the financial payment device by adopting a feedforward neural network model based on a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total number set by the financial payment device before the set time interval, the number of commodity types in sale of the financial payment device, the number of normal living people in an unmanned vending place, the distance from the nearest other financial payment device and the maximum value and the minimum value of sales amount in the historical time interval of the financial payment device;
wherein, entering a plurality of income amount values respectively corresponding to a plurality of historical time intervals of the total set before the set time interval of the financial payment device comprises: the value of the set total number is monotonically and positively associated with the number of the on-sale commodity types of the financial payment device;
the feedforward neural network model is a feedforward neural network after the feedforward neural network is trained for a plurality of times, and the training times are positively correlated with the number of people in the unmanned vending place;
and setting a plurality of income amount values corresponding to a plurality of historical time intervals of the total number before the set time interval, the number of commodity types in sale of the financial payment device, the number of resident personnel in the unmanned vending place, the distance from the nearest other financial payment devices and the maximum value and minimum value of sales amount of the historical time interval of the financial payment device as item-by-item input data of the feedforward neural network model.
2. A financial payment device amount tamper detection system as recited in claim 1, wherein the system further comprises:
the real-time display component is connected with the tampering analysis mechanism and is used for acquiring marks corresponding to each time interval and respectively executing mark type display operation on each time interval on a time axis;
the method for obtaining the marks corresponding to each time interval and respectively executing the mark type display operation on each time interval on the time axis comprises the following steps: when a certain time interval on the time axis has a mark of a suspected falsified interval, carrying out red highlighting on the time interval on the time axis;
the method for obtaining the marks corresponding to each time interval and respectively executing the mark type display operation on each time interval on the time axis comprises the following steps: when a certain time interval has a mark of a money reliable interval on the time axis, blue low-brightness display is carried out on the time interval on the time axis.
3. A financial payment device amount tamper detection system as recited in claim 1, wherein the system further comprises:
the time division communication part is connected with the tampering analysis mechanism and is used for wirelessly transmitting a tampering early warning signal and simultaneously wirelessly transmitting a set time interval marked as a suspected tampering interval;
and the parameter storage component is connected with the information analysis component and used for storing various model parameters of the feedforward neural network model.
4. A financial payment device amount tamper detection system as recited in claim 3, wherein:
the monotonic forward association of the value of the set total number and the number of the on-sale commodity types of the financial payment device comprises the following steps: and adopting a numerical mapping formula to represent the numerical mapping relation of monotonically and positively correlated value of the set total number and the number of commodity types in sale of the financial payment device, wherein the value of the set total number is an input item of the numerical mapping formula, and the number of commodity types in sale of the financial payment device is an output item of the numerical mapping formula.
5. A financial payment device amount tamper detection system as recited in any one of claims 1-3, wherein:
the method for obtaining the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number, the number of resident personnel in the unmanned vending place, the distance from the financial payment device to the nearest other financial payment devices and the historical time interval of the financial payment device comprises the following steps: when the sales amount value of a single time interval exists before the set time interval, taking the sales amount value of the single time interval as the sales amount maximum value;
the method for obtaining the sales amount maximum value and the sales amount minimum value of the financial payment device in the commodity type number, the resident personnel number in the unmanned vending place, the distance to other financial payment devices recently and the financial payment device history time interval comprises the following steps: and when the sales amount value of the single time interval exists before the set time interval, taking the sales amount value of the single time interval as the sales amount minimum value.
6. A financial payment device amount tamper detection system as recited in any one of claims 1-3, wherein:
the tamper analysis mechanism is further used for marking the set time interval as an amount reliable interval when the absolute value of the difference value between the accumulated income amount value in the set time interval and the predicted income amount in the set time interval is smaller than the set absolute value threshold;
wherein, accumulate the income amount value of the financial payment device in the settlement time interval, the financial payment device sets up in unmanned place of sale and carries out the account of reporting of income amount total number of each day every day settlement time includes: the setting time of each day is twelve hours per day in the early morning.
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