CN115658014A - Mobile application service method and system based on genetic algorithm - Google Patents

Mobile application service method and system based on genetic algorithm Download PDF

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Publication number
CN115658014A
CN115658014A CN202211672431.3A CN202211672431A CN115658014A CN 115658014 A CN115658014 A CN 115658014A CN 202211672431 A CN202211672431 A CN 202211672431A CN 115658014 A CN115658014 A CN 115658014A
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information
mobile
map
unit
mobile unit
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CN202211672431.3A
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CN115658014B (en
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韩默
保琛
冯东
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Chengdu Esender Technology Co ltd
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Chengdu Esender Technology Co ltd
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Abstract

The application relates to a mobile application service method and a system based on a genetic algorithm, which comprises the steps of responding to acquired information and calculating the length of the information; randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making an autonomous decision of steering, execution and waiting by the mobile unit at each road intersection; selecting a moving result of at least one mobile unit as a true random number after the set time period is ended; inputting a true random number into an encryption information generator to obtain an encryption sequence; the information is encrypted using an encryption sequence, resulting in encrypted information and a codebook and storing the codebook and the encrypted information in two locations. The mobile application service method and system based on the genetic algorithm obtain the true random number through the uncertainty of individuals in the genetic algorithm and the uncertainty of a final result so as to ensure the safety of an encrypted object.

Description

Mobile application service method and system based on genetic algorithm
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a mobile application service method and system based on a genetic algorithm.
Background
In the security field, weak random numbers have inherent defects, and taking the pseudo-random number algorithm of OpenSSL of Debian as an example, the maximum value of a unique random factor pid is 32768, and the range is small, so that all random numbers can be traversed quickly.
Pseudo-random numbers are implemented by mathematical algorithms, which are truly random in the form of "seeds", which once determined, identify the random numbers computed by the same pseudo-random algorithm, whose values are fixed, and the order of the values computed multiple times is also fixed.
If a weak pseudo-random number algorithm is used, very serious security problems may result.
Disclosure of Invention
The application provides a mobile application service method and system based on a genetic algorithm, wherein a true random number is obtained through the uncertainty of an individual in the genetic algorithm and the uncertainty of a final result, and the security of an encrypted object is ensured.
The above object of the present application is achieved by the following technical solutions:
in a first aspect, the present application provides a mobile application service method based on a genetic algorithm, including:
responding to the acquired information, and calculating the length of the information;
randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making an autonomous decision of steering, execution and waiting by the mobile unit at each road intersection;
selecting a moving result of at least one mobile unit as a true random number after the set time period is ended;
inputting the true random number into an encryption information generator to obtain an encryption sequence, wherein the length of the encryption sequence is equal to the length of the information;
encrypting the information by using the encryption sequence to obtain encrypted information and a codebook; and
the codebook and the encryption information are stored in two locations.
In a possible implementation manner of the first aspect, each time information is acquired, a coordinate point in a map is updated, and the updating manner includes:
selecting a coordinate point on a map and recording the coordinate point as a standard coordinate point;
giving a new coordinate value to the standard coordinate point again; and
and updating the coordinates of other coordinate points on the map according to the new coordinate values of the standard coordinate points.
In a possible implementation manner of the first aspect, each time information is acquired, a road connection relationship of a map is updated, and the updating manner includes:
determining the number of roads in the current map;
adjusting the number of roads, wherein the adjustment comprises increasing and decreasing; and
and re-determining the connection relation of the roads, wherein both ends of any road are connected with the non-both ends of other roads.
In a possible implementation manner of the first aspect, a plurality of time points exist in a set time period, at least one mobile unit is selected at the time point, and deletion processing is performed, where the number of the selected mobile units is smaller than the total number of the mobile units.
In one possible implementation form of the first aspect, the selecting the mobile unit at a time includes:
selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
the mobile units located within the selected area are subjected to a deletion process.
In a possible implementation manner of the first aspect, selecting the mobile unit after the set time period is over includes:
selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
selecting a mobile unit located in the selection area;
when the mobile unit is not present in the selected area, the range of the selected area is expanded or the reference point is replaced.
In a possible implementation manner of the first aspect, when a plurality of mobile units exist in the selection area, the coordinates of the plurality of mobile units are accumulated or randomly arranged, so as to obtain a true random number.
In a second aspect, the present application provides a mobile application service device based on a genetic algorithm, comprising:
the processing unit is used for responding to the acquired information and calculating the length of the information;
the system comprises a random processing unit, a control unit and a control unit, wherein the random processing unit is used for randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making autonomous decisions of steering, executing and waiting for each mobile unit at a road intersection;
the selection unit is used for selecting the moving result of at least one mobile unit as a true random number after the set time period is over;
the generating unit is used for inputting the true random number into the encryption information generator to obtain an encryption sequence, and the length of the encryption sequence is equal to that of the information;
the encryption unit is used for encrypting the information by using the encryption sequence to obtain encrypted information and a codebook; and
and the storage unit is used for storing the cipher book and the encrypted information at two positions.
In a third aspect, the present application provides a mobile application service system based on a genetic algorithm, the system comprising:
one or more memories for storing instructions; and
one or more processors configured to call and execute the instructions from the memory, and to execute the method according to the first aspect and any possible implementation manner of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium comprising:
a program for performing the method as described in the first aspect and any possible implementation manner of the first aspect when the program is run by a processor.
In a fifth aspect, the present application provides a computer program product comprising program instructions for executing the method according to the first aspect and any possible implementation manner of the first aspect when the program instructions are executed by a computing device.
In a sixth aspect, the present application provides a system on a chip comprising a processor configured to perform the functions recited in the above aspects, such as generating, receiving, sending, or processing data and/or information recited in the above methods.
The chip system may be formed by a chip, or may include a chip and other discrete devices.
In one possible design, the system-on-chip further includes a memory for storing necessary program instructions and data. The processor and the memory may be decoupled, disposed on different devices, connected in a wired or wireless manner, or coupled on the same device.
Drawings
Fig. 1 is a schematic block diagram illustrating a flow of steps of a mobile application service method based on a genetic algorithm provided in the present application.
Fig. 2 is a schematic diagram of a mobile unit as provided herein initially on a map.
Fig. 3 is a schematic diagram illustrating a selection manner of a mobile unit according to the present application.
Fig. 4 is a schematic diagram of a process for performing a deletion process by a mobile unit according to the present application.
Detailed Description
The technical solution of the present application will be described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, a mobile application service method based on genetic algorithm disclosed in the present application includes the following steps:
s101, responding to the acquired information, and calculating the length of the information;
s102, randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making autonomous decisions of steering, executing and waiting for each mobile unit at a road intersection;
s103, selecting a moving result of at least one mobile unit as a true random number after a set time period is finished;
s104, inputting the true random number into an encryption information generator to obtain an encryption sequence, wherein the length of the encryption sequence is equal to that of the information;
s105, encrypting the information by using the encryption sequence to obtain encrypted information and a cipher book; and
s106, storing the cipher book and the encrypted information in two positions.
The mobile application service method based on the genetic algorithm is applied to local information security service and used for encrypting local information to obtain encrypted information and a cipher book after encryption, and the cipher book and the encrypted information are respectively stored in a cloud side and a local place.
Specifically, in step S101, in response to the acquired information, the length of the information is first calculated, and the length is used to calculate the length of the encryption sequence according to the length of the information in the present application, and the lengths of the two are the same, so that the partial encryption and the full encryption can be selected to process in the encryption process.
In a specific encryption process, the true random number is obtained through the uncertainty of an individual in a genetic algorithm and the uncertainty of a final result, and for convenience of understanding the technical scheme in the application, the prior art is introduced first.
The genetic algorithm is a randomized search method evolved by taking advantage of the evolution law (survival of fittest and elimination of genetic mechanism) of the biology world, and is mainly characterized in that a structural object is directly operated, the limitation of derivation and function continuity does not exist, and the genetic algorithm has the inherent implicit parallelism and better global optimization capability.
The genetic algorithm adopts a probabilistic optimization method, can automatically acquire and guide an optimized search space, and adaptively adjusts the search direction without a determined rule. The genetic algorithm has the advantages of parallel processing and fuzzy processing, and the final result cannot be determined in the processing process. Of course, genetic algorithms also have problems, particularly in the uncertainty of the final result, such as local optimization may not be achieved and global optimization may not be achieved, or the final result may not be obtained because the results do not have convergence.
The above disadvantages may be converted into advantages under certain conditions, and in the present application, the feature of genetic algorithm is used to generate true random numbers.
It should be understood that random numbers are both true random numbers and pseudo random numbers:
true random numbers: there are many uncertain phenomena in nature, such as the weight of each sand grain in a piece of desert, or the thermal motion trajectory of molecules in the atmosphere, and by measuring these phenomena, true random numbers can be obtained.
Pseudo random number: the pseudo-random number is calculated and if the primordial seed is short, periodic repetitions of the pseudo-random number occur soon, which means that the way in which the pseudo-random number is generated can be deduced back by means of analog calculations.
For some specific devices, the current value, the voltage value, the vibration value and the like in the device can be obtained as a true random number through a customization circuit, but it should be noted that the ranges of the current value, the voltage value, the vibration value and the like are fixed, that is, the range of the random number obtained in this way is fixed, although the random number is generated irregularly, the random number can still be decrypted in a reverse derivation way, and the reverse derivation way can be disabled only depending on an infinitely large sample capacity.
Referring to fig. 2, a line segment represents a road, a solid dot represents a mobile unit, in step S102, a plurality of location points are randomly selected from a map, one mobile unit is placed on each location point, the mobile unit randomly moves on the map within a set time period, and the mobile unit makes autonomous decisions of turning, executing, and waiting at each road intersection.
The purpose of this step is to get a true random number, the concrete way is to simulate the actual situation in nature, a plurality of mobile units on the map move randomly and make autonomous decision, these mobile units make turning, executing and waiting operations at each road intersection, the turning, executing and waiting are decided by the mobile units themselves, that is, each mobile unit has autonomous decision-making right.
The target for the mobile unit may be given by:
reaching a designated position;
the parking time is minimum;
the average speed is fastest;
the instantaneous speed is fastest;
by setting the above target, the mobile unit can make an autonomous decision to achieve the target, and a plurality of mobile units process in parallel in the decision process, and the result is uncertain before the set time is not over, because the autonomous decision of the mobile unit has unpredictability. It is also understood herein that multiple individuals live in an unknown environment, with the result that the number of remaining individuals is five, but it is uncertain which individuals can remain, and a particular individual number can only be obtained by waiting until the number of remaining individuals is five.
This method is unpredictable, but considering the time factor, in step S103, the moving result of at least one moving unit is selected as the true random number after the set time period ends, here, the coordinate point of the coordinate point is taken as an example, after the set time period ends, all the moving units stop moving, and then the coordinate where at least one moving unit is located is selected as the true random number.
Referring to fig. 3, after the set time period ends, the mobile unit is selected as follows:
s201, selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
s202, selecting a mobile unit positioned in the selection area;
and S203, expanding the range of the selected area or replacing the reference point when the mobile unit does not exist in the selected area.
The steps S201 to S203 use a range selection (dotted circle in fig. 3) which makes the result uncertain. As mentioned above, the mobile unit will try to complete the target under the premise of target setting, but the completion degree is not controllable, some mobile units can complete the target, and some mobile units cannot complete the target.
The selection of the mobile unit is not based on the completion level in the present application, but is based on the location of the mobile unit. Because the mobile unit moves on the map to complete the target, the location of the mobile unit changes, and the mobile unit is selected by using a range selection method, the selected mobile unit can be either a complete target or an incomplete target, and the number of the selected mobile units can be one or more.
When a plurality of mobile units exist in the selection area, the coordinates of the mobile units are accumulated or randomly arranged to obtain a true random number. That is, there are many options for the way in which truly random numbers are ultimately obtained.
After obtaining the true random number, executing step S104, in which the true random number is input into the encryption information generator to obtain an encryption sequence, where the length of the encryption sequence is equal to the length of the information;
in step S105, the information is encrypted by using the encryption sequence to obtain encrypted information and a codebook, which are respectively stored in the cloud and the local, that is, the content of step S106.
The content in steps S104 to S106 is to encrypt the information by using the encryption sequence, because the length of the encryption sequence is consistent with the length of the information, the usage method processes the encryption sequence and two characters of corresponding bits on the information to obtain an encrypted character, and the encrypted character is used to replace the corresponding character in the information. The replacement mode can be a whole replacement mode or a partial replacement mode, and the replacement mode is not required in the application.
The encrypted information and the codebook are obtained after replacement is completed, the encrypted information can be decrypted by using the codebook, and in order to improve the security, the encrypted information and the codebook are stored separately, for example, one is stored in the cloud, and the other is stored in the local; or one in the normal storage area and one in the secret area. The separate storage can avoid the two being acquired at the same time.
As a specific embodiment of the mobile application service method based on genetic algorithm provided by the application, at least one mobile unit is selected at a time point when a plurality of time points exist within a set time period, and the deletion processing is performed, where the number of the selected mobile units is smaller than the total number of the mobile units, and the purpose of the deletion processing is to further improve the uncertainty of the finally selected mobile units.
Referring to fig. 4, the manner of selecting a mobile unit at a time point further includes:
s301, selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
s302, the mobile unit located in the selected area is subjected to deletion processing.
The content in step S301 and step S302 is to further improve the randomness, and the randomness of the final result is further improved by deleting some mobile units. As mentioned above, in order to complete the target, the mobile unit moves on the map, and the location of the mobile unit changes, the mobile unit is selected by using a range selection method, the selected mobile unit may be a complete target or an incomplete target, and the number of the selected mobile units may be one or more.
Of course, the map used by the mobile unit also needs to be updated, and a specific way is to update the coordinate points in the map each time information is acquired, and the updating way includes:
s401, selecting a coordinate point on a map and recording the coordinate point as a standard coordinate point;
s402, giving new coordinate values to the standard coordinate points again; and
and S403, updating the coordinates of other coordinate points on the map according to the new coordinate values of the standard coordinate points.
Besides the coordinate point updating method, the method also updates the connection relationship of roads in the map, and specifically comprises the following steps:
s501, determining the number of roads in the current map;
s502, adjusting the number of roads, wherein the adjustment comprises increasing and decreasing; and
s503, re-determining the connection relationship of the roads, wherein both ends of any one road are connected with the non-both ends of other roads.
In each updating process of the road connection relationship, firstly, the number is adjusted, and then the connection relationship of the roads is determined again, specifically, the roads are numbered from 1, wherein 1 represents a first road, 11 and 12 represent two ends of the road, and 13-19 represent random points on the road; 2 denotes the first road, 21 and 22 denote the ends of the road, 23-29 denote random points on the road, and so on.
When the connection relationship is re-determined, 11 and 12 randomly select a random point on a road, 21 and 22 randomly select a random point on a road, and so on.
After the processing in the above manner, the connection relationship of the roads is determined again. Here, it should be noted that the codes used in the road connection relationship determination process are used only as connection relationships.
Every time the coordinate and road connection relation on the map is updated, the source of the true random number at each time can be uncertain, the random number obtained from an uncertain source (including direct obtaining and processing obtaining) is the true random number, and the true random number has unpredictability and the source is non-traceable.
The present application also provides a mobile application service device based on a genetic algorithm, including:
the processing unit is used for responding to the acquired information and calculating the length of the information;
the system comprises a random processing unit, a control unit and a control unit, wherein the random processing unit is used for randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making autonomous decisions of steering, executing and waiting for each mobile unit at a road intersection;
the selecting unit is used for selecting a moving result of at least one moving unit as a true random number after the set time period is finished;
the generating unit is used for inputting the true random number into the encryption information generator to obtain an encryption sequence, and the length of the encryption sequence is equal to that of the information;
the encryption unit is used for encrypting the information by using the encryption sequence to obtain encrypted information and a cipher book; and
and the storage unit is used for storing the cipher book and the encrypted information at two positions.
In a possible implementation manner of the first aspect, each time information is acquired, a coordinate point in a map is updated, and the updating manner includes:
selecting a coordinate point on a map and recording the coordinate point as a standard coordinate point;
giving a new coordinate value to the standard coordinate point again; and
and updating the coordinates of other coordinate points on the map according to the new coordinate values of the standard coordinate points.
Further, still include:
a number determination unit for determining the number of roads in the current map;
a number adjustment unit for adjusting the number of roads, the adjustment including an increase and a decrease; and
and the relationship adjusting unit is used for re-determining the connection relationship of the roads, and both ends of any road are connected with the non-both ends of other roads.
Further, a plurality of time points exist in the set time period, at least one mobile unit is selected at the time point and deletion processing is carried out, and the number of the selected mobile units is smaller than the total number of the mobile units.
Further, the method also comprises the following steps:
the first area selection unit is used for selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
and the deleting unit is used for deleting the mobile unit positioned in the selection area.
Further, still include:
the second area selection unit is used for selecting a coordinate point on the map and generating a selection area by taking the coordinate point as a reference point; and
a selection unit for selecting mobile units located in the selection area;
and an adjusting unit for expanding the range of the selection area or replacing the reference point when the mobile unit does not exist in the selection area.
Further, when a plurality of mobile units exist in the selection area, the coordinates of the plurality of mobile units are accumulated or randomly arranged to obtain a true random number.
In one example, the units in any of the above apparatuses may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), or a combination of at least two of these integrated circuit forms.
For another example, when a unit in the apparatus can be implemented in the form of a processing element scheduler, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling programs. As another example, these units may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Various objects such as various messages/information/devices/network elements/systems/devices/actions/operations/procedures/concepts may be named in the present application, it is to be understood that these specific names do not limit the related objects, and the named names may vary according to the circumstances, the context or the usage habit, and the understanding of the technical meaning of the technical terms in the present application should be mainly determined by the functions and technical effects embodied/performed in the technical solutions.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units 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 units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It should also be understood that, in various embodiments of the present application, the first, second, etc. are merely intended to represent that a plurality of objects are different. For example, the first time window and the second time window are merely to illustrate different time windows. And should not have any influence on the time window itself, and the above-mentioned first, second, etc. should not impose any limitation on the embodiments of the present application.
It is also to be understood that the terminology and/or the description of the various embodiments herein is consistent and mutually inconsistent if no specific statement or logic conflicts exists, and that the technical features of the various embodiments may be combined to form new embodiments based on their inherent logical relationships.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a computer-readable storage medium, which includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned computer-readable storage media comprise: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
The present application also provides a mobile application service system based on a genetic algorithm, the system including:
one or more memories for storing instructions; and
one or more processors configured to retrieve and execute the instructions from the memory to perform the methods as described above.
The present application also provides a computer program product comprising instructions that, when executed, cause the mobile application service system to perform operations of the mobile application service system corresponding to the above-described method.
The present application further provides a system on a chip comprising a processor configured to perform the functions recited above, such as generating, receiving, transmitting, or processing data and/or information recited in the above-described methods.
The chip system may be formed by a chip, or may include a chip and other discrete devices.
The processor mentioned in any of the above may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of programs of the method for transmitting feedback information.
In one possible design, the system-on-chip further includes a memory for storing necessary program instructions and data. The processor and the memory may be decoupled, disposed on different devices respectively, and connected in a wired or wireless manner to support the system on chip to implement various functions in the foregoing embodiments. Alternatively, the processor and the memory may be coupled to the same device.
Optionally, the computer instructions are stored in a memory.
Alternatively, the memory is a storage unit in the chip, such as a register, a cache, and the like, and the memory may also be a storage unit outside the chip in the terminal, such as a ROM or another type of static storage device that can store static information and instructions, a RAM, and the like.
It will be appreciated that the memory herein can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory.
The non-volatile memory may be ROM, programmable Read Only Memory (PROM), erasable Programmable Read Only Memory (EPROM), electrically Erasable Programmable Read Only Memory (EEPROM), or flash memory.
Volatile memory can be RAM, which acts as external cache memory. There are many different types of RAM, such as Static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and DSRAMs.
The embodiments of the present invention are preferred embodiments of the present application, and the scope of protection of the present application is not limited by the embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.

Claims (10)

1. A mobile application service method based on genetic algorithm is characterized by comprising the following steps:
responding to the acquired information, and calculating the length of the information;
randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making an autonomous decision of steering, execution and waiting by the mobile unit at each road intersection;
selecting a moving result of at least one mobile unit as a true random number after the set time period is over;
inputting the true random number into an encryption information generator to obtain an encryption sequence, wherein the length of the encryption sequence is equal to the length of the information;
encrypting the information by using the encryption sequence to obtain encrypted information and a codebook; and
the codebook and the encryption information are stored in two locations.
2. The mobile application service method based on genetic algorithm according to claim 1, wherein the coordinate points in the map are updated each time information is acquired, and the updating method comprises:
selecting a coordinate point on a map and recording the coordinate point as a standard coordinate point;
giving a new coordinate value to the standard coordinate point again; and
and updating the coordinates of other coordinate points on the map according to the new coordinate values of the standard coordinate points.
3. The mobile application service method based on the genetic algorithm according to claim 1 or 2, wherein the road connection relationship of the map is updated each time information is acquired, and the updating method includes:
determining the number of roads in the current map;
adjusting the number of roads, wherein the adjustment comprises increasing and decreasing; and
and re-determining the connection relation of the roads, wherein both ends of any road are connected with the non-both ends of other roads.
4. The genetic algorithm-based mobile application service method of claim 1, wherein a plurality of time points exist within a set time period, at least one mobile unit is selected at a time point and subjected to deletion processing, and the number of the selected mobile units is smaller than the total number of the mobile units.
5. The genetic algorithm-based mobile application service method of claim 4, wherein the manner of selecting the mobile unit at a time comprises:
selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
the mobile units located within the selected area are subjected to a deletion process.
6. The genetic algorithm-based mobile application service method of claim 1, 4 or 5, wherein selecting the mobile unit after the set period of time is over comprises:
selecting a coordinate point on a map and generating a selection area by taking the coordinate point as a reference point; and
selecting a mobile unit located in the selection area;
when the mobile unit is not present in the selected area, the range of the selected area is expanded or the reference point is replaced.
7. The genetic algorithm-based mobile application service method of claim 6, wherein when a plurality of mobile units exist in the selection area, the coordinates of the plurality of mobile units are accumulated or randomly arranged to obtain a true random number.
8. A mobile application service apparatus based on genetic algorithm, comprising:
the processing unit is used for responding to the acquired information and calculating the length of the information;
the system comprises a random processing unit, a data processing unit and a data processing unit, wherein the random processing unit is used for randomly selecting a plurality of position points in a map, placing a mobile unit on each position point, randomly moving the mobile unit on the map within a set time period, and making an autonomous decision on turning, execution and waiting for the mobile unit at each road intersection;
the selecting unit is used for selecting a moving result of at least one moving unit as a true random number after the set time period is finished;
the generating unit is used for inputting the true random number into the encryption information generator to obtain an encryption sequence, and the length of the encryption sequence is equal to that of the information;
the encryption unit is used for encrypting the information by using the encryption sequence to obtain encrypted information and a cipher book; and
and the storage unit is used for storing the cipher book and the encrypted information in two positions.
9. A mobile application service system based on genetic algorithm, the system comprising:
one or more memories for storing instructions; and
one or more processors configured to call and execute the instructions from the memory to perform the method of any one of claims 1 to 7.
10. A computer-readable storage medium, the computer-readable storage medium comprising:
program for performing the method according to any one of claims 1 to 7 when the program is run by a processor.
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Denomination of invention: A Mobile Application Service Method and System Based on Genetic Algorithm

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