CN110536305B - WiFi hot spot detection method and device, terminal equipment and storage medium - Google Patents
WiFi hot spot detection method and device, terminal equipment and storage medium Download PDFInfo
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- CN110536305B CN110536305B CN201910807160.XA CN201910807160A CN110536305B CN 110536305 B CN110536305 B CN 110536305B CN 201910807160 A CN201910807160 A CN 201910807160A CN 110536305 B CN110536305 B CN 110536305B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/30—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/30—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information
- H04L63/302—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information gathering intelligence information for situation awareness or reconnaissance
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/12—Detection or prevention of fraud
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The application provides a WiFi hotspot detection method, a WiFi hotspot detection device, terminal equipment and a storage medium. Comprising the following steps: according to the online WiFi cracking scheme, a common WiFi network of a suspected person is cracked, a data packet in the common WiFi network of the suspected person is obtained, network information is obtained, a weight value algorithm is established, network information appearing in browsing webpage data and chat data is marked according to the network information, the number of the marked network information in the browsing webpage data and the chat data is obtained, the weight value of the marked network information is calculated according to the weight value algorithm and is used as a first weight value and a second weight value respectively, the suspected person is detected according to the first weight value and the second weight value, the weight value of the network information stored in the data packet in the WiFi network is calculated according to the weight value algorithm, the detection direction is determined according to the size of the weight value, and the suspected person is accurately detected.
Description
Technical Field
The present application relates to the field of WiFi hotspot technologies, and in particular, to a WiFi hotspot detection method, device, terminal equipment, and storage medium.
Background
With the rapid development of WiFi technology and the widespread use of mobile devices, the development of mobile social networks is rapid, and at the same time, many criminal activities performed through the network, such as: network attacks, telecom fraud and other network criminals are realized through social networks, and currently, suspects are detected by monitoring and acquiring data packets in WiFi networks of suspects.
However, the method generally only obtains the internal data packet of the WiFi network of the suspect, and analysis of the internal data packet of the WiFi network of the suspect is often not very important, but the investigation of the suspect is realized by tracking the WiFi network, so how to detect the suspect through the internal data packet of the WiFi network becomes a problem to be solved urgently.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present application and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
In view of the above, the application provides a WiFi hotspot detection method, a WiFi hotspot detection device, terminal equipment and a storage medium, and aims to solve the technical problem that a suspected person cannot be detected through a WiFi network internal data packet in the prior art.
The technical scheme of the application is realized as follows:
in one aspect, the present application provides a WiFi hotspot detection method, where the WiFi hotspot detection method includes the following steps:
s1, acquiring a WiFi cracking scheme from the Internet, acquiring a WiFi network common to a suspected mobile phone, cracking the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, and acquiring a data packet in the WiFi network common to the suspected mobile phone, wherein the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data;
s2, acquiring network information, wherein the network information comprises: the method comprises the steps of establishing a weight value algorithm for the financial information, address information and character name information, marking network information appearing in browsing webpage data and chat data according to the network information, obtaining the number of marked network information in the browsing webpage data and the chat data, and calculating the weight value of the marked network information according to the weight value algorithm to be used as a first weight value and a second weight value respectively;
and S3, detecting the suspects according to the first weight value and the second weight value.
On the basis of the above technical solution, preferably, step S1 further includes the steps of obtaining a WiFi cracking solution from the internet, establishing a database according to the WiFi cracking solution, obtaining a WiFi cracking solution matched with the WiFi network commonly used by the suspected mobile phone, searching the WiFi cracking solution matched with the WiFi network commonly used by the suspected mobile phone from the database, and cracking the WiFi network commonly used by the suspected mobile phone to obtain a data packet in the WiFi network commonly used by the suspected mobile phone, where the data packet in the WiFi network commonly used by the suspected mobile phone includes: browsing web page data and chat data.
On the basis of the technical scheme, the method preferably further comprises the following steps of obtaining a WiFi cracking scheme from the Internet, setting preset connection time, obtaining a WiFi network commonly used by the suspected mobile phone, cracking the WiFi network commonly used by the suspected mobile phone according to the Internet WiFi cracking scheme, obtaining the connection time of the WiFi network commonly used by the suspected mobile phone, and obtaining a data packet in the WiFi network commonly used by the suspected mobile phone when the connection time of the WiFi network commonly used by the suspected mobile phone meets the preset connection time, wherein the data packet in the WiFi network commonly used by the suspected mobile phone comprises: browsing webpage data and chat data; and when the connection time of the WiFi network common to the suspected person is not met with the preset connection time, reselecting the WiFi network common to the suspected person.
On the basis of the above technical solution, preferably, in step S2, the method further includes the step of obtaining network information, where the network information includes: the method comprises the steps of establishing a weight value algorithm, marking network information appearing in browsing webpage data according to the network information, obtaining the quantity of marked network information in the browsing webpage data, calculating the weight value of the marked network information in the browsing webpage data according to the quantity of marked network information in the browsing webpage data through the weight value algorithm, comparing the weight values of the marked network information in the browsing webpage data, screening out the marked network information in the browsing webpage data corresponding to the maximum weight value, and taking the maximum weight value as a first weight value.
On the basis of the above technical solution, preferably, in step S2, the method further includes the step of obtaining network information, where the network information includes: the method comprises the steps of establishing a weight value algorithm for marking network information appearing in chat data according to the network information, obtaining the number of marked network information in the chat data, calculating the weight value of the marked network information in the chat data according to the number of marked network information in the chat data through the weight value algorithm, comparing the weight values of the marked network information in the chat data in pairs, screening out the marked network information in the chat data corresponding to the maximum weight value, and taking the maximum weight value as a second weight value.
On the basis of the above technical solution, preferably, the weight value algorithm is:
where p represents the weight value of the marked network information in the browsed web data and the chat data, μ represents the number of the marked network information in the browsed web data and the chat data, and m represents the total number of the marked network information in the browsed web data and the chat data.
On the basis of the above technical solution, preferably, step S3 further includes the steps of comparing the network information corresponding to the first weight value with the network information corresponding to the second weight value, determining main network information for investigation when the network information corresponding to the first weight value is the same as the network information corresponding to the second weight value, and performing investigation on the suspected person; when the network information corresponding to the first weight value is different from the network information corresponding to the second weight value, determining main network information to be detected according to the sizes of the first weight value and the second weight value, and when the first weight value is larger than the second weight value, determining the main network information to be detected as the network information corresponding to the first weight value and detecting the suspected person; when the first weight value is smaller than the second weight value, determining that the main network information for investigation is the network information corresponding to the second weight value, and carrying out investigation on the suspects.
Still further preferably, the WiFi hotspot detection apparatus includes:
the acquisition module acquires a WiFi cracking scheme from the Internet, acquires a WiFi network common to the suspected mobile phone, cracks the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, acquires a data packet in the WiFi network common to the suspected mobile phone, and the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data;
the computing module is used for acquiring network information, wherein the network information comprises: the method comprises the steps of establishing a weight value algorithm for the financial information, address information and character name information, marking network information appearing in browsing webpage data and chat data according to the network information, obtaining the number of marked network information in the browsing webpage data and the chat data, and calculating the weight value of the marked network information according to the weight value algorithm to be used as a first weight value and a second weight value respectively;
and the investigation module is used for carrying out investigation on the suspects according to the first weight value and the second weight value.
In a second aspect, the WiFi hotspot detection method further includes a terminal device, where the terminal device includes: a memory, a processor, and a WiFi hotspot detection method program stored on the memory and executable on the processor, the WiFi hotspot detection method program configured to implement the steps of the WiFi hotspot detection method as described above.
In a third aspect, the WiFi hotspot detection method further includes a storage medium, where the storage medium is a computer storage medium, and a WiFi hotspot detection method program is stored on the computer storage medium, where the WiFi hotspot detection method program is executed by the processor to implement the steps of the WiFi hotspot detection method as described above.
Compared with the prior art, the WiFi hotspot detection method has the following beneficial effects:
(1) The method comprises the steps that the weight value of network information appearing in the webpage data browsed by the suspects is calculated through a weight value algorithm, the webpage data browsed by the suspects can be analyzed according to the weight value, the approximate range of the browsing activities of the suspects is determined, the investigation workload of workers on the suspects can be reduced, and the workers only need to carry out key investigation on the suspects according to the range of the browsing activities of the suspects;
(2) The method has the advantages that the weight value of the network information appearing in the chat record data of the suspects is calculated through the weight value algorithm, the chat data of the suspects can be analyzed according to the weight value, the key content of the chat of the suspects can be accurately determined, workers can directly analyze and detect the suspects according to the chat content of the suspects, and therefore the suspects can be efficiently detected, and the workload of the workers is reduced.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a terminal device of a hardware running environment according to an embodiment of the present application;
fig. 2 is a flowchart of a first embodiment of a WiFi hotspot detection method according to the present application;
fig. 3 is a schematic functional block diagram of a first embodiment of a WiFi hotspot detection method according to the present application.
Detailed Description
The following description of the embodiments of the present application will clearly and fully describe the technical aspects of the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to fall within the scope of the present application.
As shown in fig. 1, the terminal device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (RandomAccess Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the terminal device, and that in actual practice the terminal device may comprise more or less components than shown, or certain components may be combined, or different arrangements of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a WiFi hotspot detection method program may be included in the memory 1005 as one type of storage medium.
In the terminal device shown in fig. 1, the network interface 1004 is mainly used for establishing a communication connection between the terminal device and a server storing all data required in the WiFi hotspot detection method system; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the WiFi hotspot detection method device of the present application may be provided in the WiFi hotspot detection method device, where the WiFi hotspot detection method device invokes a WiFi hotspot detection method program stored in the memory 1005 through the processor 1001, and executes the WiFi hotspot detection method provided by the present application.
Referring to fig. 2, fig. 2 is a flowchart of a first embodiment of a WiFi hotspot detection method according to the present application.
In this embodiment, the WiFi hotspot detection method includes the following steps:
s10: acquiring a WiFi cracking scheme from the Internet, acquiring a WiFi network common to the suspected mobile phone, cracking the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, and acquiring a data packet in the WiFi network common to the suspected mobile phone, wherein the data packet in the WiFi network common to the suspected mobile phone comprises: browsing web page data and chat data.
It should be understood that the system can continuously acquire WiFi cracking schemes from the internet, then establish a database according to the WiFi cracking schemes, the WiFi cracking schemes in the database are continuously updated so as to be timely cracked when a new WiFi network appears, then acquire the WiFi network to which a suspected person is frequently connected, then crack the WiFi network to obtain data packets in the suspected person mobile phone, wherein the data packets comprise browsing webpage data and chat data, and then analyze the browsing webpage data and the chat data to realize the investigation of the suspected person, so that the circle needing to be investigated is reduced in advance, the range of workers needing to be investigated is avoided to be too large, and some data are omitted.
It should be understood that when the WiFi network of the mobile phone of the suspect is cracked, the connection time of the mobile phone to the WiFi network is also obtained, then a time value is preset by the system, if the time of the mobile phone to connect to the WiFi network is too short and does not meet the preset time of the system, the WiFi network is not the WiFi network commonly used by the target mobile phone, the system reselects the next WiFi network to crack, when the time of the target mobile phone to connect to the WiFi network is found to be greater than the preset time of the system, the system indicates that the target mobile phone of the WiFi network is used for a period of time, and the system can obtain the data packet of the target mobile phone under the WiFi network.
S20: acquiring network information, the network information comprising: the method comprises the steps of establishing a weight value algorithm for the financial information, address information and character name information, marking network information appearing in browsing webpage data and chat data according to the network information, obtaining the number of the marked network information in the browsing webpage data and the chat data, and calculating the weight value of the marked network information according to the weight value algorithm to be used as a first weight value and a second weight value respectively.
It should be understood that in this embodiment, the system may pre-establish a weight value algorithm, then set a network information table, where the network information table is formed according to some financial information, address information and person name information to be detected, then mark the network information in the browsing web page according to the network information table, then calculate the weight values of the marked network information respectively, then compare the weight values of the network information two by two, obtain the network information with the largest weight value as the key detection object, and use the corresponding weight value as the first weight value.
It should be understood that in this embodiment, the chat data of the tracking mobile phone is also analyzed to determine whether the chat data has network information to be detected, if so, the network information in the chat data is also marked, a weight value is calculated, then the network information with the largest weight value is obtained as the most important tracking object, and the weight value is used as the second weight value.
It should be appreciated that the weight value algorithm is:
where p represents the weight value of the marked network information in the browsed web data and the chat data, μ represents the number of the marked network information in the browsed web data and the chat data, and m represents the total number of the marked network information in the browsed web data and the chat data.
S30: and detecting the suspects according to the first weight value and the second weight value.
It should be understood that, finally, the system will detect the suspicious person according to the first weight value and the second weight value, when the network information corresponding to the first weight value and the second weight value is the same, it means that the suspicious person mobile phone attaches importance to the network information, the staff only needs to detect the network information in a key way, when the network information corresponding to the first weight value and the second weight value is different, the first weight value and the second weight value need to be compared, the detected key point is determined according to the weight value, and if the weight value is large, the detected key point object is determined by directly analyzing the data packet in the WiFi network of the suspicious person, thereby reducing the workload of the staff, improving the working efficiency of the staff, and making the staff able to detect the suspicious person mobile phone in a high-efficient and fast way.
It should be noted that the foregoing is merely illustrative, and does not limit the technical solution of the present application in any way.
Through the above description, it is easy to find that the embodiment of the application provides a WiFi hotspot detection method, a device, a terminal device and a storage medium. Comprising the following steps: according to the online WiFi cracking scheme, a common WiFi network of a suspected person is cracked, a data packet in the common WiFi network of the suspected person is obtained, network information is obtained, a weight value algorithm is established, network information appearing in browsing webpage data and chat data is marked according to the network information, the number of the marked network information in the browsing webpage data and the chat data is obtained, the weight value of the marked network information is calculated according to the weight value algorithm and is used as a first weight value and a second weight value respectively, the suspected person is detected according to the first weight value and the second weight value, the weight value of the network information stored in the data packet in the WiFi network is calculated according to the weight value algorithm, the detection direction is determined according to the size of the weight value, and the suspected person is accurately detected.
In addition, the embodiment of the application also provides a WiFi hot spot detection device. As shown in fig. 3, the WiFi hotspot detection method apparatus includes: acquisition module 10, calculation module 20, investigation module 30.
The acquiring module 10 is configured to acquire a WiFi cracking scheme from the internet, acquire a WiFi network common to a suspected mobile phone, crack the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, and acquire a data packet in the WiFi network common to the suspected mobile phone, where the data packet in the WiFi network common to the suspected mobile phone includes: browsing webpage data and chat data;
a calculation module 20, configured to obtain network information, where the network information includes: the method comprises the steps of establishing a weight value algorithm for the financial information, address information and character name information, marking network information appearing in browsing webpage data and chat data according to the network information, obtaining the number of marked network information in the browsing webpage data and the chat data, and calculating the weight value of the marked network information according to the weight value algorithm to be used as a first weight value and a second weight value respectively;
the investigation module 30 is configured to perform investigation on the suspected person according to the first weight value and the second weight value.
In addition, it should be noted that the above embodiment of the apparatus is merely illustrative, and does not limit the scope of the present application, and in practical application, a person skilled in the art may select some or all modules according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in the present embodiment may refer to the WiFi hotspot detection method provided in any embodiment of the present application, which is not described herein.
In addition, the embodiment of the application also provides a storage medium, which is a computer storage medium, wherein a WiFi hot spot detection method program is stored on the computer storage medium, and the WiFi hot spot detection method program realizes the following operations when being executed by a processor:
s1, acquiring a WiFi cracking scheme from the Internet, acquiring a WiFi network common to a suspected mobile phone, cracking the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, and acquiring a data packet in the WiFi network common to the suspected mobile phone, wherein the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data;
s2, acquiring network information, wherein the network information comprises: the method comprises the steps of establishing a weight value algorithm for the financial information, address information and character name information, marking network information appearing in browsing webpage data and chat data according to the network information, obtaining the number of marked network information in the browsing webpage data and the chat data, and calculating the weight value of the marked network information according to the weight value algorithm to be used as a first weight value and a second weight value respectively;
and S3, detecting the suspects according to the first weight value and the second weight value.
Further, the WiFi hotspot detection method program further realizes the following operations when executed by the processor:
acquiring a WiFi cracking scheme from the Internet, establishing a database according to the WiFi cracking scheme, acquiring a WiFi network commonly used by a suspected person, searching the WiFi cracking scheme matched with the WiFi network commonly used by the suspected person from the database, cracking the WiFi network commonly used by the suspected person, and acquiring a data packet in the WiFi network commonly used by the suspected person, wherein the data packet in the WiFi network commonly used by the suspected person comprises: browsing web page data and chat data.
Further, the WiFi hotspot detection method program further realizes the following operations when executed by the processor:
acquiring a WiFi cracking scheme from the internet, setting preset connection time, acquiring a WiFi network common to a suspected mobile phone, cracking the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme on the internet, acquiring the connection time of the WiFi network common to the suspected mobile phone, and acquiring a data packet in the WiFi network common to the suspected mobile phone when the connection time of the WiFi network common to the suspected mobile phone meets the preset connection time, wherein the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data; and when the connection time of the WiFi network common to the suspected person is not met with the preset connection time, reselecting the WiFi network common to the suspected person.
Further, the WiFi hotspot detection method program further realizes the following operations when executed by the processor:
acquiring network information, the network information comprising: the method comprises the steps of establishing a weight value algorithm, marking network information appearing in browsing webpage data according to the network information, obtaining the quantity of marked network information in the browsing webpage data, calculating the weight value of the marked network information in the browsing webpage data according to the quantity of marked network information in the browsing webpage data through the weight value algorithm, comparing the weight values of the marked network information in the browsing webpage data, screening out the marked network information in the browsing webpage data corresponding to the maximum weight value, and taking the maximum weight value as a first weight value.
Further, the WiFi hotspot detection method program further realizes the following operations when executed by the processor:
acquiring network information, the network information comprising: the method comprises the steps of establishing a weight value algorithm for marking network information appearing in chat data according to the network information, obtaining the number of marked network information in the chat data, calculating the weight value of the marked network information in the chat data according to the number of marked network information in the chat data through the weight value algorithm, comparing the weight values of the marked network information in the chat data in pairs, screening out the marked network information in the chat data corresponding to the maximum weight value, and taking the maximum weight value as a second weight value.
Further, the WiFi hotspot detection method program further realizes the following operations when executed by the processor:
the weight value algorithm is as follows:
where p represents the weight value of the marked network information in the browsed web data and the chat data, μ represents the number of the marked network information in the browsed web data and the chat data, and m represents the total number of the marked network information in the browsed web data and the chat data.
Further, the WiFi hotspot detection method program further realizes the following operations when executed by the processor:
comparing the network information corresponding to the first weight value with the network information corresponding to the second weight value, and when the network information corresponding to the first weight value is the same as the network information corresponding to the second weight value, determining main network information for investigation, and carrying out investigation on the suspects; when the network information corresponding to the first weight value is different from the network information corresponding to the second weight value, determining main network information to be detected according to the sizes of the first weight value and the second weight value, and when the first weight value is larger than the second weight value, determining the main network information to be detected as the network information corresponding to the first weight value and detecting the suspected person; when the first weight value is smaller than the second weight value, determining that the main network information for investigation is the network information corresponding to the second weight value, and carrying out investigation on the suspects.
The foregoing description of the preferred embodiments of the application is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the application.
Claims (6)
1. A WiFi hotspot detection method is characterized by comprising the following steps of: comprises the following steps of;
s1, acquiring a WiFi cracking scheme from the Internet, acquiring a WiFi network common to a suspected mobile phone, cracking the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, and acquiring a data packet in the WiFi network common to the suspected mobile phone, wherein the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data;
s2, acquiring network information, wherein the network information comprises: the method comprises the steps of establishing a weight value algorithm, marking network information appearing in browsing webpage data and chat data according to network information, respectively obtaining the quantity of marked network information in the browsing webpage data and the chat data, respectively calculating weight values corresponding to the marked webpage data and the weight values corresponding to the marked network information in the chat data according to the financial network information, the address network information and the person name network information through the weight value algorithm, respectively comparing the weight values corresponding to the network information in the browsing webpage data with each other, comparing the weight values corresponding to the network information in the chat data with each other, screening out the marked network information in the browsing webpage data corresponding to the maximum weight value, taking the maximum weight value as a first weight value, and simultaneously screening out the marked network information in the chat data corresponding to the maximum weight value, and taking the maximum weight value as a second weight value;
the weight value algorithm is as follows:
p＝μ；
m
wherein p represents the weight value of the marked network information in the browsed webpage data or the chat data, mu represents the number of the marked network information in the browsed webpage data or the chat data, and m represents the total number of the marked network information in the browsed webpage data or the chat data;
s3, comparing the network information corresponding to the first weight value with the network information corresponding to the second weight value, and determining main network information for investigation and performing investigation on the suspects when the network information corresponding to the first weight value is the same as the network information corresponding to the second weight value; when the network information corresponding to the first weight value is different from the network information corresponding to the second weight value, determining main network information to be detected according to the sizes of the first weight value and the second weight value, and when the first weight value is larger than the second weight value, determining the main network information to be detected as the network information corresponding to the first weight value and detecting the suspected person; when the first weight value is smaller than the second weight value, determining that the main network information for investigation is the network information corresponding to the second weight value, and carrying out investigation on the suspects.
2. The WiFi hotspot detection method of claim 1, wherein: in step S1, further including the steps of obtaining a WiFi cracking scheme from the internet, establishing a database according to the WiFi cracking scheme, obtaining a WiFi network commonly used by a suspected mobile phone, searching a WiFi cracking scheme matched with the WiFi network commonly used by the suspected mobile phone from the database, and cracking the WiFi network commonly used by the suspected mobile phone to obtain a data packet in the WiFi network commonly used by the suspected mobile phone, where the data packet in the WiFi network commonly used by the suspected mobile phone includes: browsing web page data and chat data.
3. The WiFi hotspot detection method of claim 2, wherein: the method comprises the steps of obtaining a WiFi cracking scheme from the Internet, setting preset connection time, obtaining a WiFi network common to a suspected mobile phone, cracking the WiFi network common to the suspected mobile phone according to the Internet WiFi cracking scheme, obtaining connection time of the WiFi network common to the suspected mobile phone, and obtaining a data packet in the WiFi network common to the suspected mobile phone when the connection time of the WiFi network common to the suspected mobile phone meets the preset connection time, wherein the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data; and when the connection time of the WiFi network common to the suspected person is not met with the preset connection time, reselecting the WiFi network common to the suspected person.
4. The WiFi hot spot detection device is characterized in that the WiFi hot spot detection method device comprises the following steps:
the acquisition module acquires a WiFi cracking scheme from the Internet, acquires a WiFi network common to the suspected mobile phone, cracks the WiFi network common to the suspected mobile phone according to the WiFi cracking scheme, acquires a data packet in the WiFi network common to the suspected mobile phone, and the data packet in the WiFi network common to the suspected mobile phone comprises: browsing webpage data and chat data;
the computing module is used for acquiring network information, wherein the network information comprises: the method comprises the steps of establishing a weight value algorithm, marking network information appearing in browsing webpage data and chat data according to network information, respectively obtaining the quantity of marked network information in the browsing webpage data and the chat data, respectively calculating weight values corresponding to the marked webpage data and the weight values corresponding to the marked network information in the chat data according to the financial network information, the address network information and the person name network information through the weight value algorithm, respectively comparing the weight values corresponding to the network information in the browsing webpage data with each other, comparing the weight values corresponding to the network information in the chat data with each other, screening out the marked network information in the browsing webpage data corresponding to the maximum weight value, taking the maximum weight value as a first weight value, and simultaneously screening out the marked network information in the chat data corresponding to the maximum weight value, and taking the maximum weight value as a second weight value;
the weight value algorithm is as follows:
p＝μ；
m
wherein p represents the weight value of the marked network information in the browsed webpage data or the chat data, mu represents the number of the marked network information in the browsed webpage data or the chat data, and m represents the total number of the marked network information in the browsed webpage data or the chat data;
the detection module compares the network information corresponding to the first weight value with the network information corresponding to the second weight value, and when the network information corresponding to the first weight value is the same as the network information corresponding to the second weight value, main network information for detection is determined and the suspects are detected; when the network information corresponding to the first weight value is different from the network information corresponding to the second weight value, determining main network information to be detected according to the sizes of the first weight value and the second weight value, and when the first weight value is larger than the second weight value, determining the main network information to be detected as the network information corresponding to the first weight value and detecting the suspected person; when the first weight value is smaller than the second weight value, determining that the main network information for investigation is the network information corresponding to the second weight value, and carrying out investigation on the suspects.
5. A terminal device, characterized in that the terminal device comprises: a memory, a processor, and a WiFi hotspot detection method program stored on the memory and executable on the processor, the WiFi hotspot detection method program configured to implement the steps of the WiFi hotspot detection method of any of claims 1 to 3.
6. A storage medium, characterized in that the storage medium is a computer storage medium, on which a WiFi hotspot detection method program is stored, which WiFi hotspot detection method program, when executed by a processor, implements the steps of the WiFi hotspot detection method according to any of claims 1 to 3.
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