CN111125599A - Rating method and device for hidden network website, storage medium and electronic equipment - Google Patents
Rating method and device for hidden network website, storage medium and electronic equipment Download PDFInfo
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- CN111125599A CN111125599A CN201911343680.6A CN201911343680A CN111125599A CN 111125599 A CN111125599 A CN 111125599A CN 201911343680 A CN201911343680 A CN 201911343680A CN 111125599 A CN111125599 A CN 111125599A
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Abstract
The application provides a rating method, a rating device, a storage medium and electronic equipment for a darknet website, wherein the method comprises the following steps: obtaining a rating factor of a hidden network website, wherein the rating factor comprises a website survival rate of the hidden network website, and the website survival rate represents a successful response proportion of the hidden network website to an access request within a preset time; and grading the hidden network website according to the grading factor. And grading the hidden network websites by acquiring a grading factor comprising the website survival rate of the hidden network websites. The website survival rate of the hidden website is the ratio of the response success of the hidden website to the access request within a period of time, so that the probability of the successful access of the hidden website can be reflected, the probability serves as one dimension of the rating of the hidden website, and the hidden website can be objectively and accurately rated.
Description
Technical Field
The application relates to the field of internet, in particular to a rating method and device of a darknet website, a storage medium and electronic equipment.
Background
Darknet is the world wide web content that exists on a darknet, an overlay network, and can only be accessed with special software, special authorization, or via a specially configured computer. The abundance and abundance of the hidden web sites and the abundance of resources are the superiority of the hidden web sites, but the hidden web sites are various in variety and are not good. When facing to websites of the same category, in order to select a better website to improve the internet experience, it is necessary to establish an evaluation system of a hidden website to grade the hidden website, so as to provide website guidance information for users.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for rating a hidden website, a storage medium, and an electronic device, so as to rate the hidden website, and provide website guidance information for a user.
In order to achieve the above object, embodiments of the present application are implemented as follows:
in a first aspect, an embodiment of the present application provides a rating method for a darknet website, where the method includes: obtaining a rating factor of a hidden network website, wherein the rating factor comprises a website survival rate of the hidden network website, and the website survival rate represents a successful response proportion of the hidden network website to an access request within a preset time; and grading the hidden network website according to the grading factor.
And grading the hidden network websites by acquiring a grading factor comprising the website survival rate of the hidden network websites. The website survival rate of the hidden website is the ratio of the response success of the hidden website to the access request within a period of time, so that the probability of the successful access of the hidden website can be reflected, the probability serves as one dimension of the rating of the hidden website, and the hidden website can be objectively and accurately rated.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the rating the darknet website according to the rating factor includes: determining website scores of the hidden network websites according to the rating factors; and grading the hidden network website according to the website grade.
The rating factor of the hidden network website is adopted, and the hidden network website can be rated as finely and accurately as possible in a scoring mode.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the determining, according to the rating factor, a website score of the darknet website includes: determining a website survival rate score of the hidden network website according to the website survival rate; and determining the website score of the dark net website according to the website survival rate score.
The website survival rate of the dark net website is scored to determine the website survival rate score, and then the website score of the dark net website is further determined, so that the dark net website can be accurately scored on the website survival rate dimension.
With reference to the first possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, the rating factor further includes listing information of the intranet site, and before determining a website score of the intranet site according to the rating factor, the method further includes: acquiring recording information for representing whether the hidden network website is recorded by a hidden network search engine, wherein the hidden network search engine is used for recording part or all websites in the hidden network; correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the search engine score of the hidden network website according to the recording information, and determining the website score of the hidden network website according to the search engine score.
In the hidden network, not every hidden network site is recorded by the search engine, the hidden network sites recorded by the search engine have certain advantages compared with the hidden network sites which are not recorded, and the hidden network sites can be objectively, accurately and finely graded by taking the recorded information of whether the hidden network sites are recorded by the hidden network search engine as one dimension of evaluating the hidden network sites and grading.
With reference to the first possible implementation manner of the first aspect, in a fourth possible implementation manner of the first aspect, the rating factor further includes a network speed of the intranet site, and before determining a website score of the intranet site according to the rating factor, the method further includes: acquiring the network speed for accessing the hidden network website; correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the network speed score of the dark network website according to the network speed, and determining the website score of the dark network website according to the network speed score.
In the hidden network, the speed of the network has a great influence on the internet surfing experience of a user and a certain influence on the loading speed of the webpage, so that the speed of the network of the hidden network website is used as a dimension for evaluating the hidden network website and is graded, and the hidden network website can be graded objectively, accurately and finely.
With reference to the first possible implementation manner of the first aspect, in a fifth possible implementation manner of the first aspect, the rating factor further includes a reference condition of the intranet site, and before determining a website score of the intranet site according to the rating factor, the method further includes: acquiring the reference condition of the darknet website, wherein the reference condition is used for representing the frequency and/or times of the external link of the darknet website being referred by other websites; correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the external link score of the dark web site according to the citation condition, and determining the web site score of the dark web site according to the external link score.
The frequency and/or times of the external links of the darknet website being quoted by other websites can reflect the popularity and attraction of the website, so the quoted condition of the darknet website is used as one dimension for evaluating the darknet website, and the rating can be carried out on the darknet website more objectively, accurately and finely.
With reference to the first possible implementation manner of the first aspect, in a sixth possible implementation manner of the first aspect, the rating factor further includes an information resource condition of the intranet site, and before determining a website score of the intranet site according to the rating factor, the method further includes: acquiring information resource conditions of the hidden network website, wherein the information resource conditions are used for expressing the richness degree of the information resources of the hidden network website; correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the information resource score of the dark web site according to the information resource condition, and determining the website score of the dark web site according to the information resource score.
The information resource condition can reflect the abundance degree of the information resources of the hidden network website and the quality of the hidden network website, and the hidden network website can be objectively, accurately and finely graded by taking the information resource condition of the hidden network website as one dimension of evaluating the hidden network website and grading.
In a second aspect, an embodiment of the present application provides a rating apparatus for a darknet website, the apparatus including: the system comprises a rating factor acquisition module, a rating factor acquisition module and a rating factor acquisition module, wherein the rating factor comprises a website survival rate of a dark web website, and the website survival rate represents the successful response proportion of the dark web website to an access request within a preset time; and the hidden network website rating module is used for rating the hidden network website according to the rating factor.
In a third aspect, an embodiment of the present application provides a storage medium, where one or more programs are stored, and the one or more programs are executable by one or more processors to implement the steps of the rating method for a darkweb website according to the first aspect or any one of possible implementations of the first aspect.
In a fourth aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, where the memory is configured to store information including program instructions, and the processor is configured to control execution of the program instructions, where the program instructions are loaded and executed by the processor to implement the steps of the rating method for a darknet website according to the first aspect or any one of the possible implementations of the first aspect.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a flowchart of a rating method for a darknet website according to an embodiment of the present application.
Fig. 2 is a block diagram illustrating a structure of a rating apparatus for a darknet website according to an embodiment of the present application.
Fig. 3 is a block diagram of an electronic device according to an embodiment of the present disclosure.
Icon: 10-rating means of a darknet website; 11-a rating factor obtaining module; 12-a darknet website rating module; 20-an electronic device; 21-a memory; 22-a communication module; 23-a bus; 24-a processor.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a flowchart illustrating a rating method for a darknet website according to an embodiment of the present application. In this embodiment, in order to improve the access experience of the user to the darknet website, the darknet website may be rated. For example, the rating method of the darknet website can be executed by the electronic device. The rating method of the darknet website may include step S10 and step S20.
In order to objectively and accurately rate the darknet website, the electronic device may perform step S10.
Step S10: the method comprises the steps of obtaining a rating factor of a hidden network website, wherein the rating factor comprises a website survival rate of the hidden network website, and the website survival rate represents the successful response proportion of the hidden network website to an access request within a preset time.
In this embodiment, in order to perform accurate and objective rating on the darknet website, the electronic device may obtain a rating factor of the darknet website.
For example, since the website survival rate (the ratio of the response success of the darknet website to the access request within a period of time) of the darknet website can represent the possibility of the successful access of the darknet website, as a dimension for rating the darknet website, the darknet website can be rated as objectively and accurately as possible. Therefore, the electronic device can acquire the website survival rate of the darknet website.
Specifically, the electronic device may determine the success rate of accessing the hidden network station (i.e., the website survival rate of the hidden network station) by accessing the hidden network station at a fixed time within a preset time period and determining the number of times of successful access and the total number of times of access.
For example, the darknet website may be accessed every 10 minutes for a day, 144 times a day. If the response success rate of the dark web site is 96 times, the web site survival rate of the dark web site is 96 ÷ 144 × 100% >, which is 60%.
In order to more accurately determine the website survival rate of the hidden website, the website survival rate can be determined for multiple times, and then an average value is obtained to determine the more accurate website survival rate.
The access success rates corresponding to multiple times can be respectively obtained in the peak time and the valley time of the dark net website access, the average value of the access success rates in the peak time and the average value of the access success rates in the valley time are obtained, and the sum is given according to the proportion (the sum of the proportion of the peak time and the proportion of the valley time is 1), so that the actual website survival rate can be determined.
The website survival rate of the hidden website is used as one dimension for evaluating the hidden website, so that the hidden website can be objectively and accurately rated.
In the intranet, not every intranet site is usually recorded by the search engine, and the intranet sites recorded by the search engine have certain advantages compared with the intranet sites which are not recorded. In order to perform accurate and objective rating on the intranet website, in this embodiment, the electronic device may further obtain inclusion information (used to characterize whether the intranet website is included by an intranet search engine) of the intranet website as a rating factor.
For example, the electronic device may obtain listing information for characterizing whether a darknet website is listed by a darknet search engine, wherein the darknet search engine is used for listing some or all websites in the darknet.
Specifically, whether the intranet site is included by any intranet search engine in the intranet can be acquired, so that the inclusion information of the intranet site is determined. Of course, the intranet search engines that record the intranet sites may also be different, and therefore, the electronic device may also determine information such as the number of intranet search engines that record the intranet sites, the popularity (e.g., whether the intranet search engines are the mainstream), and the like.
The collecting information of whether the hidden network website is collected by the hidden network search engine is used as one dimension for evaluating the hidden network website, so that the hidden network website can be objectively and accurately rated.
In the hidden network, the speed of the network has direct influence on the loading speed of the webpage and the file transmission speed, so that the internet surfing experience of a user is greatly influenced. Therefore, in this embodiment, the electronic device may obtain the internet speed of the darknet website as a rating factor for rating the darknet website.
For example, the network speed of the darknet website may be tested by a network speed measuring method (e.g., some speed measuring software) to obtain the network speed of the darknet website. Certainly, in order to ensure that the network speed of the hidden network station is accurately evaluated as much as possible, the network speeds corresponding to a plurality of times can be respectively obtained in the peak time period and the valley time period of the access of the hidden network station to obtain the average value of the network speeds, so that the network speed of the hidden network station can be accurately determined.
The speed of the hidden network website is used as one dimension of evaluating the hidden network website, so that the hidden network website can be objectively and accurately rated.
The frequency and/or number of times external links of a darknet website are referenced by other websites can reflect the popularity and appeal of the website. Therefore, in the present embodiment, the electronic device may acquire the reference condition of the darknet website (which is used for indicating the frequency and/or the number of times that the external link of the darknet website is referred to by other websites) as the rating factor for rating the darknet website.
For example, the electronic device may obtain the number and/or frequency of times the external link of the darknet website is referred to by other websites to determine the reference condition of the darknet website.
The rating of the hidden website can be objectively and accurately carried out by taking the reference condition of the hidden website as one dimension of evaluating the hidden website.
The information resource condition can reflect the richness degree of the information resources of the hidden network website and can also reflect the quality of the hidden network website. Therefore, in the present embodiment, the electronic device may acquire the information resource condition of the darknet website (which is used for indicating the richness degree of the information resource of the darknet website) as the rating factor for rating the darknet website.
For example, the electronic device may obtain information resource status of the darknet website. For example, the information resource condition of the hidden network site is determined by acquiring the ratio of the content of the network site to the webpage. The ratio of the website content to the webpage can reflect the content of the webpage of the website, so that the richness of the information resource of the hidden website is reflected.
The information resource condition of the hidden network website is used as one dimension of evaluating the hidden network website, so that the hidden network website can be objectively and accurately rated.
It should be noted that the rating factor of the darknet website may also include other factors, such as the visit volume of the darknet website. Therefore, the selection of the rating factor for the darknet website should not be considered as a limitation of the present application.
In this embodiment, after determining the rating factor of the darknet website, the electronic device may execute step S20.
Step S20: and grading the hidden network website according to the grading factor.
In this embodiment, in order to more objectively and finely rate the dark web site (i.e., perform fine-grained rating), the electronic device may determine the website score of the dark web site according to the rating factor, so as to rate the dark web site. The electronic device determines the website score of the darknet website, and will be described with the following scores in several dimensions as an example.
For example, the electronic device may determine a website survival score for the darknet website according to the website survival rate. For example, when the website survival rate of the darknet website is lower than 20%, the grade of the corresponding website survival rate is poor (score 0); when the website survival rate of the hidden website is 20% to 80%, the grade of the corresponding website survival rate is good (1 point); when the website survival rate of the hidden website is higher than 80%, the grade of the corresponding website survival rate is excellent (2 points). Therefore, the website survival rate score of the dark web website can be determined.
It should be noted that, the manner of determining the website survival score based on the website survival rate of the darknet website should not be construed as a limitation to the present application. The scoring may be performed in other manners, such as different ranges of survival rates of the ranked websites, different scores corresponding to the respective ranks, etc., and therefore, should not be considered as limiting the present application.
For example, the electronic device may determine a search engine score for the darknet website based on the listing information. For example, if the intranet site is recorded by an intranet search engine, the corresponding score is 2; and if the hidden network website is not recorded by the hidden network search engine, the corresponding score is 0.
Here, the manner of determining the search engine score based on the recording information of the intranet site should not be construed as a limitation to the present application. The search engine score may also be determined in other manners, such as, for example, determining the number of intranet search engines that include the intranet site, the popularity (e.g., scoring 2 points when the number of intranet search engines meets the criteria or the popularity meets the criteria; scoring 1 point when neither the number of intranet search engines that include the intranet site meets the criteria nor the popularity meets the criteria; scoring 0 points when the intranet site is not included by an intranet search engine), and so on. Therefore, the present application should not be considered as limited herein.
For example, the electronic device may determine a wire speed score of the darknet website according to the wire speed. For example, the network speed may be divided into fast (2 minutes), normal (1 minute) and slow (0 minute) according to the speed of the network, and the standard of the classification of the network speed may be based on the actual demand, for example, 20 mega per second or more is fast, 1 to 20 mega per second is normal, and 1 mega per second or less is slow. The determination of the wire speed score is only exemplary (both the wire speed grading standard and the score value can be adjusted according to actual requirements), and should not be considered as a limitation of the present application.
For example, the electronic device may determine the external link score of the darknet website according to the reference condition of the darknet website. That is, the external link score may be determined based on the number of references and/or frequency of external links to the darknet website. For example, the number of references (frequency) to external links of a darknet website is above 1000 (10 times per day), with a score of 2; the number of external links referenced (frequency) is above 100 to 1000 times (1 to 10 times per day), with a score of 1; the number of references (frequency) of external links is below 100 (1 per day) with a score of 0. The determination of the external link score is only exemplary (the numerical index of the number and/or frequency and the score value can be adjusted according to actual needs), and should not be considered as a limitation of the present application.
For example, the electronic device may determine the information resource score of the darknet website according to the information resource condition. Specifically, the electronic device may determine the score of the information resource of the hidden network website according to a ratio of the website content of the hidden network website to the webpage. For example, the content of a website accounts for more than 60% of the web page, with a score of 2; the ratio of the website content to the webpage is between 20% and 60%, and the score is 1; the ratio of the website content to the webpage is lower than 20%, and the score is 0. However, the determination method of the information resource score is only exemplary (the ratio of the website content to the webpage and the score value can be adjusted according to the actual requirement), and should not be considered as a limitation of the present application.
After the scores corresponding to the rating factors are determined, the electronic equipment can determine the website scores of the dark web websites. For example, the scores corresponding to the rating factors are summed up, or the scores corresponding to the rating factors are summed up according to a preset ratio (the preset ratio can be adjusted according to the type of the darknet website, and the sum of the ratio values is 1). Therefore, the website score of the dark web website can be determined.
After determining the website score of the dark web website, the electronic equipment can grade the dark web website according to the website score. For example, a website score of 3 points or less, a dark web website is rated as poor; the website score is 3 to 7 points, and the dark net website is rated as good; the website score is more than 7 points, and the dark net website is ranked as excellent. However, the rating manner of the darknet website is only exemplary (both the score index and the evaluation level of the website score of the darknet website can be adjusted according to actual needs), and should not be considered as a limitation of the present application.
By grading the rating factors, each rating dimension of the hidden network website can be objectively, accurately and finely evaluated, and the hidden network website can be objectively and finely rated.
In addition, by the rating method of the dark web site provided by the embodiment of the application, the rating of the dark web site can be ranked through comprehensive analysis of the dark web site. After rating the hidden network websites, the hidden network search engine can rank and display the websites according to the rated website scores. When some website contents are similar, the website score of the darknet website can guide a user to selectively browse the website according to the comprehensive score of the website. And the website score of the hidden network website is beneficial for website managers to optimize the website according to the scores of different dimensionalities of the website. For example, the content of the website is optimized according to the information resource score, and the content richness of the website is improved; the server of the website can be optimized according to the internet speed score, and the access speed is improved; optimizing the external links of the website according to the external link scores, so that the number of the external links of the website can be increased, and the indexed times of the website can be increased; the access success rate of the website and the like can be optimized according to the survival rate score of the website.
In addition, after the hidden network websites are graded by the grading method of the hidden network websites provided by the embodiment of the application, the hidden network search engine can select the hidden network websites with higher website grades according to the website grades of the hidden network websites to record, so that a user can find needed contents accurately and quickly; and website managers can optimize the website continuously according to the scores, and the user experience of the website is improved. The method is also beneficial to the user to select the corresponding website with high score to access according to the website score so that the user can quickly and accurately find the required content.
Referring to fig. 2, based on the same inventive concept, an embodiment of the present application further provides a rating apparatus 10 for a darknet website, including:
the rating factor obtaining module 11 is configured to obtain a rating factor of a dark web site, where the rating factor includes a website survival rate of the dark web site, and the website survival rate indicates a ratio of successful response of the dark web site to an access request within a preset time period.
And the dark web site rating module 12 is configured to rate the dark web site according to the rating factor.
In this embodiment, the hidden network website rating module 12 is further configured to determine a website score of the hidden network website according to the rating factor; and grading the hidden network website according to the website grade.
In this embodiment, the hidden network website rating module 12 is further configured to determine a website survival rate score of the hidden network website according to the website survival rate; and determining the website score of the dark net website according to the website survival rate score.
In this embodiment, the rating factor obtaining module 11 is further configured to obtain, before the hidden network site rating module 12 determines the website score of the hidden network site according to the rating factor, recording information for representing whether the hidden network site is recorded by a hidden network search engine, where the hidden network search engine is configured to record part or all of the websites in the hidden network; correspondingly, the hidden network website rating module 12 is further configured to determine, according to the rating factor, a website score of the hidden network website, including: and determining the search engine score of the hidden network website according to the recording information, and determining the website score of the hidden network website according to the search engine score.
In this embodiment, the rating factor obtaining module 11 is further configured to obtain the internet speed of accessing the dark web site before the dark web site rating module 12 determines the website rating of the dark web site according to the rating factor; correspondingly, the dark web site rating module 12 is further configured to determine a web speed score of the dark web site according to the web speed, and determine a web site score of the dark web site according to the web speed score.
In this embodiment, the rating factor obtaining module 11 is further configured to obtain a citation condition of the intranet site before the intranet site rating module 12 determines, according to the rating factor, a website score of the intranet site, where the citation condition is used to indicate a frequency and/or a number of times that an external link of the intranet site is cited by other websites; correspondingly, the dark web site rating module 12 is further configured to determine an external link score of the dark web site according to the citation condition, and determine a web site score of the dark web site according to the external link score.
In this embodiment, the rating factor obtaining module 11 is further configured to obtain an information resource condition of the hidden website before the hidden website rating module 12 determines, according to the rating factor, a website rating score of the hidden website, where the information resource condition is used to indicate a richness degree of the information resource of the hidden website; correspondingly, the hidden network website rating module 12 is further configured to determine an information resource score of the hidden network website according to the information resource condition, and determine a website score of the hidden network website according to the information resource score.
In this embodiment, a storage medium is further provided, where the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to implement the steps of the rating method for a darknet website in an embodiment of the present application.
Referring to fig. 3, fig. 3 is a block diagram of an electronic device 20 according to an embodiment of the present disclosure. In this embodiment, the electronic device 20 may be a server, and when the electronic device 20 is a server, it may be a network server, a cloud server, a server cluster formed by a plurality of servers, or the like; the electronic device 20 may also be a terminal, and when the electronic device 20 is a terminal, it may be a smart phone, a tablet computer, a personal computer, and the like, which is not limited herein.
Illustratively, the electronic device 20 may include: a communication module 22 connected to the outside world via a network, one or more processors 24 for executing program instructions, a bus 23, a Memory 21 of different form, such as a magnetic disk, a ROM (Read-only Memory), or a RAM (Random Access Memory), or any combination thereof. The memory 21, the communication module 22 and the processor 24 are connected by a bus 23.
Illustratively, the memory 21 has stored therein a program. The processor 24 may call and run these programs from the memory 21 so that the rating method of the darknet website can be performed by running the programs.
In summary, the embodiments of the present application provide a method and an apparatus for rating a hidden website, a storage medium, and an electronic device, which are used for rating a hidden website by obtaining a rating factor including a website survival rate of the hidden website. The website survival rate of the hidden website is the ratio of the response success of the hidden website to the access request within a period of time, so that the probability of the successful access of the hidden website can be reflected, the probability serves as one dimension of the rating of the hidden website, and the hidden website can be objectively and accurately rated.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of modules may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the communication connections shown or discussed may be indirect connections of devices through some communication interfaces, and may be electrical, mechanical or other forms.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A method for rating a darknet website, the method comprising:
obtaining a rating factor of a hidden network website, wherein the rating factor comprises a website survival rate of the hidden network website, and the website survival rate represents a successful response proportion of the hidden network website to an access request within a preset time;
and grading the hidden network website according to the grading factor.
2. The method for rating a darknet website according to claim 1, wherein the rating the darknet website according to the rating factor comprises:
determining website scores of the hidden network websites according to the rating factors;
and grading the hidden network website according to the website grade.
3. The method for rating a darknet website according to claim 2, wherein determining the website score of the darknet website according to the rating factor comprises:
determining a website survival rate score of the hidden network website according to the website survival rate;
and determining the website score of the dark net website according to the website survival rate score.
4. The method for rating a darknet website of claim 2, wherein the rating factor further comprises listing information of the darknet website, and the method further comprises, before determining the website rating of the darknet website according to the rating factor:
acquiring recording information for representing whether the hidden network website is recorded by a hidden network search engine, wherein the hidden network search engine is used for recording part or all websites in the hidden network;
correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the search engine score of the hidden network website according to the recording information, and determining the website score of the hidden network website according to the search engine score.
5. The method of claim 2, wherein the rating factor further comprises a net speed of the darknet website, and wherein the method further comprises, before determining the website rating of the darknet website according to the rating factor:
acquiring the network speed for accessing the hidden network website;
correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the network speed score of the dark network website according to the network speed, and determining the website score of the dark network website according to the network speed score.
6. The method of claim 2, wherein the rating factor further includes a reference condition of the darknet website, and before determining the website rating of the darknet website according to the rating factor, the method further comprises:
acquiring the reference condition of the darknet website, wherein the reference condition is used for representing the frequency and/or times of the external link of the darknet website being referred by other websites;
correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the external link score of the dark web site according to the citation condition, and determining the web site score of the dark web site according to the external link score.
7. The method of claim 2, wherein the rating factor further includes information resource status of the darknet website, and before determining the website rating of the darknet website according to the rating factor, the method further comprises:
acquiring information resource conditions of the hidden network website, wherein the information resource conditions are used for expressing the richness degree of the information resources of the hidden network website;
correspondingly, according to the rating factor, determining the website score of the darknet website, including: and determining the information resource score of the dark web site according to the information resource condition, and determining the website score of the dark web site according to the information resource score.
8. An apparatus for rating a darknet website, the apparatus comprising:
the system comprises a rating factor acquisition module, a rating factor acquisition module and a rating factor acquisition module, wherein the rating factor comprises a website survival rate of a dark web website, and the website survival rate represents the successful response proportion of the dark web website to an access request within a preset time;
and the hidden network website rating module is used for rating the hidden network website according to the rating factor.
9. A storage medium storing one or more programs, the one or more programs being executable by one or more processors to perform the steps of the method of rating a darknet website of any one of claims 1 to 7.
10. An electronic device comprising a memory for storing information including program instructions and a processor for controlling execution of the program instructions, characterized in that: the program instructions, when loaded and executed by a processor, implement the steps of the method of rating a darknet website of any one of claims 1 to 7.
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