Method for determining attribution information of IP address segment, device, product, and storage medium

Abstract

Embodiments of the present disclosure provide a method for determining attribution information of an IP address segment, a device, a product, and a storage medium. The method comprises: acquiring target IP addresses within a target IP address segment for which attribution information is to be determined; for the target IP addresses, respectively acquiring candidate attribution information of the target IP addresses by means of different acquisition modes, and then on the basis of preset weights of the respective pieces of candidate attribution information of the target IP addresses, determining attribution information of the target IP addresses, wherein the preset weights are positively correlated with the reliability levels of the acquisition modes corresponding to the candidate attribution information; and on the basis of the attribution information of the respective target IP addresses within the target IP address segment, determining attribution information of the target IP address segment. In the present embodiments, accurate attribution information of an IP address segment can be obtained.

Description

Method, device, product and storage medium for determining ownership information of IP address segment Cross-reference to Related Applications

[0001] The present disclosure claims priority to Chinese Patent Application No. 202411088705.3, filed on August 08, 2024, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the technical field of Internet, and particularly relates to a method, device, product and storage medium for determining ownership information of an IP address segment. BACKGROUND

[0003] In network scheduling, it is very important to manage and schedule IP address segments according to their ownership information (such as regional information and operator information). Accurate ownership information can ensure effective allocation and optimized use of network resources, thereby improving the performance and stability of the overall network. If the ownership information of an IP address segment is incorrect, it may lead to incorrect scheduling decisions, and even cause network failures or service interruptions. Therefore, how to accurately determine the ownership information of an IP address segment is a technical problem to be solved. SUMMARY

[0004] To overcome the problems in the related art, the present disclosure provides a method, device, program product and storage medium for determining ownership information of an IP address segment.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for determining ownership information of an IP address segment is provided, the method comprising: obtaining target IP addresses in a target IP address segment whose ownership information is to be determined; for each target IP address, obtaining candidate ownership information of the target IP address through different obtaining manners, and then determining the ownership information of the target IP address according to preset weights of each candidate ownership information of the target IP address, wherein the preset weight is positively correlated with the reliability of the obtaining manner of the candidate ownership information; and determining the ownership information of the target IP address segment according to the ownership information of each target IP address in the target IP address segment.

[0006] According to a second aspect of an embodiment of the present disclosure, a computer device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method embodiment of the first aspect when executing the computer program.

[0007] According to a third aspect of the embodiments of the present disclosure, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement the steps of the method embodiment of the first aspect.

[0008] According to a fourth aspect of the embodiments of the present disclosure, a computer program product is provided, and the computer program product comprises a computer program. The computer program is executed by a processor to implement the steps of the method embodiment of the first aspect.

[0009] The technical solutions provided by the embodiments of the present disclosure can include the following beneficial effects.

[0010] In the embodiments of the present disclosure, for a target IP address segment to be determined with the home information, the target IP address within the address segment can be acquired. For each target IP address, the candidate home information of the target IP address can be acquired through different acquisition manners respectively, and then the home information of the target IP address can be determined according to the preset weights of the candidate home information of the target IP address. The different acquisition manners include acquisition from a public IP address information library, acquisition through network detection, and acquisition from a self-constructed IP address information library. The preset weights are positively correlated with the reliability degrees of the acquisition manners of the candidate home information. Based on this, since the candidate home information of the target IP address is acquired through multiple different acquisition manners in the embodiments, multiple different information sources are referred to. On this basis, the embodiments further set corresponding preset weights for the reliability degrees of the different acquisition manners. The higher the reliability degree is, the higher the preset weight of the candidate home information acquired through the acquisition manner is. Therefore, the home information of the target IP address can be accurately determined based on the preset weights corresponding to each acquisition manner respectively, and multiple information sources are comprehensively utilized. Furthermore, the home information of each target IP address is utilized to accurately determine the home information of the target IP address segment.

[0011] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0012] FIG. 1 is a flowchart of a method for determining the home information of an IP address segment according to an exemplary embodiment of the present disclosure.

[0013] FIG. 2A is a schematic diagram of a network path between a probe machine and a target IP address according to an exemplary embodiment of the present disclosure.

[0014] FIG. 2B is a schematic diagram of a query of the home information of an IP address according to an exemplary embodiment of the present disclosure.

[0015] FIG. 2C is a schematic diagram of a method for determining the home information of an IP address segment according to an exemplary embodiment of the present disclosure.

[0016] FIG. 3 is a diagram illustrating a hardware structure of a computer device in which a determination apparatus of home information of an IP address segment according to an exemplary embodiment of the present disclosure is located. DETAILED DESCRIPTION

[0017] The exemplary embodiments will be described in detail herein below with reference to the drawings. In the following description, the same drawings refer to the same elements or similar elements. The embodiments described in the following exemplary embodiments do not represent all the embodiments consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0018] The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used in the present disclosure and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0019] It should be understood that although the terms first, second, third, etc. can be employed in this disclosure to describe various information, these information should not be limited to these terms. These terms are only used to differentiate one piece of information from another piece of information of the same type. For example, a first information can also be called a second information without departing from the scope of the present disclosure, and similarly, a second information can also be called a first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining."

[0020] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the embodiments of the present disclosure are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation portal for the user to choose authorization or refusal.

[0021] The IP address information library and IP address information involved in the embodiments of the present disclosure are all information and data authorized by the IP address provider or authorized by all parties, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation portal for the IP address provider to choose authorization or refusal.

[0022] For many service providers, especially cloud computing service providers, a library of IP address segments with accurate attribution information is crucial for the basic network department to improve the accuracy of traffic scheduling. For example, if the IP address segment attributed to country A is mistakenly scheduled as the IP address segment of country B, it may increase the access latency of users in country A. Based on this, the embodiment of the present disclosure provides a scheme capable of accurately determining the attribution information of an IP address.

[0023] First, some words involved in the embodiments of the present disclosure are explained.

[0024] IP address (Internet Protocol Address): IP address is a unique address used to identify devices (such as computers, routers) in the Internet. It is composed of a set of 32-bit or 128-bit binary numbers, usually represented in dotted decimal (IPv4) or colon-separated hexadecimal (IPv6) form. IPv4 addresses are usually represented as four groups of 8-bit numbers, such as 192.168.*.*, while IPv6 addresses are longer, such as 2001:0db8:85a3:0000:0000:8a2e:0370:****. The main role of IP address is to uniquely identify and locate devices on the Internet, so that data packets can be accurately routed to their destination.

[0025] IP address segment: IP address segment refers to a range of multiple IP addresses in succession. It can be used to define the starting and ending addresses of a certain network or subnet, for example, from 192.168.1.0 to 192.168.1.255 is an IP address segment, representing all possible addresses of a subnet.

[0026] My Traceroute (MTR): MTR combines the functions of traceroute and ping, and is a tool for testing network connection quality. It not only shows the routing path of data packets (similar to traceroute), but also provides the delay and packet loss information of each hop along the way (similar to ping). MTR can help network administrators or users diagnose network connection problems and performance bottlenecks.

[0027] Traceroute: Traceroute is a network diagnostic tool used to determine the path of data packets from the source IP address to the target IP address. It sends data packets, observes each network hop the data packets pass through, and measures the response time of each hop, thereby helping users identify and solve network connection problems.

[0028] Ping: Ping is a commonly used network tool for testing the connectivity and response speed of computer networks. It sends an ICMP request (ping request) to the target host and waits for the return of the ICMP response (ping response). By measuring the response time, users can determine whether the target host is reachable and the network delay.

[0029] AS (Autonomous System): An autonomous system is a single administrative unit in the Internet, usually composed of one or more IP address prefixes, managed and controlled by one or more network operators. AS has its own set of routing policies to determine how to transmit data packets on the Internet.

[0030] ASN (Autonomous System Number): Autonomous System Number is a unique number that identifies an autonomous system. Each AS must have an ASN to uniquely identify the autonomous system in the global scope.

[0031] ISP (Internet Service Provider): Internet Service Provider is a company or organization that provides Internet access services to end users. ISP connects to the core of the Internet through its own network infrastructure and provides network connection, data transmission and other Internet-related services to users.

[0032] As shown in FIG. 1, a flowchart of a method for determining the ownership information of an IP address segment according to an exemplary embodiment of the present disclosure can include the following steps 102 to 106.

[0033] In step 102, a target IP address within a target IP address segment whose ownership information is to be determined is obtained.

[0034] In step 104, for the target IP address, candidate ownership information of the target IP address is obtained through different acquisition methods, and then the ownership information of the target IP address is determined according to the preset weight of each candidate ownership information of the target IP address.

[0035] Among them, the preset weight is positively correlated with the reliability of the acquisition method of the candidate ownership information.

[0036] In step 106, the ownership information of the target IP address segment is determined according to the ownership information of each target IP address within the target IP address segment.

[0037] The data processing method provided by the embodiments of the present disclosure can be executed by a computer device, which includes but is not limited to a physical server, a server cluster, a cloud server, a smart phone, a tablet computer, a personal digital assistant (PDA), a laptop computer, a desktop computer and other devices with computing functions.

[0038] As an example, the embodiments can determine the attribution information for an IP address segment. Taking the IPv4 address space as an example, IP addresses are usually divided into different subnets according to a subnet mask, and each subnet contains a certain number of IP addresses. An IP address segment refers to a range of continuous IP addresses. IP addresses can be divided into different categories, and common categories include A-class, B-class and C-class IP addresses. As an example, the IP address segment for which attribution information is to be determined in the embodiments can be a C-class IP address. If a CIDR (Classless Inter-Domain Routing) method is used to define the IP address range, as an example, “ / 24” in 8.8.8.0 / 24 represents a subnet mask, which indicates that the first 24 bits are the network part, and the remaining 8 bits are the host part. This CIDR block contains all IP addresses from 8.8.8.0 to 8.8.8.255, a total of 256 addresses.

[0039] As an example, the target IP address segment for which attribution information is to be determined in step 102 can be obtained in various ways, for example, it can be obtained from a public IP address information library, which can have one or more.

[0040] As an example, a plurality of target IP addresses within the target IP address segment can be obtained, and the attribution information of the target IP address segment is determined based on the attribution information of the target IP addresses.

[0041] The attribution information of the IP address segment of the embodiments can be one or more types of attribution information, including but not limited to one or more combinations of the following: geographical information, operator information or ASN attribution information.

[0042] As an example, after determining each type of attribution information of the target IP address, the attribution information of the target IP address segment of each type is determined according to the attribution information of each type of the plurality of target IP addresses. For example, the geographical information of the target IP address segment is determined according to the geographical information of each target IP address; the operator information of the target IP address segment is determined according to the operator information of each target IP address; similarly, the ASN attribution information of the target IP address segment is determined according to the ASN attribution information of each target IP address.

[0043] The target IP addresses in the target IP address segment in step 102 can be multiple, and the acquisition manner can also be multiple, for example, a random algorithm can be used to select multiple target IP addresses in the target IP segment; or all target IP addresses in the target IP address segment can be selected, or multiple target IP addresses can be proportionally sampled, and the like. The embodiment does not limit the number and acquisition manner of the target IP addresses in the target IP address segment.

[0044] As an example, the selected target IP address can be an IP address that has a response after a Ping request is initiated to the target IP address. For example, a Ping request packet is sent to an IP address, and a Ping response packet from the IP address is received. If an IP address successfully responds to the Ping request, it indicates that the target host is in an online state, and the network connection is active. Not all IP addresses will respond to the Ping request, for example, the IP address is not assigned to a host or the corresponding host access is limited, and the like. Therefore, if the IP address does not have a response, it is not the target IP address here. Based on this, the embodiment can determine the target IP address that can be accessed from the target IP address segment, so as to accurately determine the ownership information of the target IP address segment.

[0045] As an example, in order to accurately determine the ownership information of the target IP address, the embodiment can acquire the candidate ownership information of the target IP address through multiple different acquisition manners, and then determine the final ownership information of the target IP address through multiple candidate ownership information of the target IP address. That is, the ownership information of the target IP address in the embodiment is not determined by a single information source, but is determined by multiple information sources, so that the ownership information of the target IP address can be more accurately determined.

[0046] In step 104, the different acquisition manners can be multiple, for example, can be acquired from a public IP address information library, acquired through network detection, and acquired from a self-constructed IP address information library, and the like. Of course, other acquisition manners of candidate ownership information can also be included in actual applications, and the embodiment does not limit this. Next, some acquisition manners are described respectively.

[0047] For example, the disclosed IP address information library can store one or more combinations of the following attribution information of some IP addresses: geographical information, operator attribution information or ASN attribution information. There can be one or more disclosed IP address information libraries in this embodiment. In the case of multiple disclosed IP address information libraries, there can be an IP address with different attribution information in different disclosed IP address information libraries. In this case, there can be multiple processing methods. For example, the target IP address can be discarded, and the target IP address with the same attribution information recorded in each disclosed IP address information library can be selected. The target IP address can also be retained, but the candidate attribution information obtained from the disclosed IP address information library is empty, and so on.

[0048] Based on this, the disclosed IP address information library can obtain one or more combinations of the candidate attribution region, the candidate attribution operator or the candidate attribution ASN of the target IP address.

[0049] As an example, there can be multiple ways for the network probe to obtain candidate attribution information, such as MTR probe, Ping probe and / or SRv6 (Segment Routing IPv6, tunnel probe) and so on.

[0050] As an example, multiple probe machines distributed in different regions can be used to respectively initiate network probes, such as MTR probes and Ping probes, to each target IP address. For example, the attribution information can include geographical information, and the network probe can include: using multiple probe machines distributed in different regions to respectively initiate MTR probes to each target IP address, obtaining the time length of the delay of each probe machine accessing the target IP address, and determining the region of the probe machine with a time length of delay lower than a first time length threshold as the candidate attribution information; and / or, using multiple probe machines distributed in different regions to respectively initiate Ping probes to each target IP address, obtaining the time length of the delay of each probe machine accessing the target IP address, and determining the region of the probe machine with a time length of delay lower than a second time length threshold as the candidate attribution information.

[0051] If the probe machine and the region to which the target IP address belongs are in the same region, the time length of the delay of the probe machine to the target IP address is likely to be small, so the first time length threshold and the second time length threshold can be set based on this. As an example, the first time length threshold and the second time length threshold can be set to 10 milliseconds or the like. The specific values can be flexibly configured according to actual needs, and this embodiment does not limit this.

[0052] As an example, in some operating systems, MTR is a command line tool available, which can be installed on the probing machine through a package manager, and the probing machine can start the MTR tool and input an mtr command carrying a target IP address to be probed, after which the MTR tool can start sending packets to the target IP address, and can obtain information of each intermediate router between the packet and the target IP address, such as IP address, delay duration, or packet loss rate, and possibly including DNS (Domain Name System) resolution results.

[0053] As an example, in some operating systems, Ping is a built-in command line tool, and the probing machine can start a command prompt window and input a Ping command carrying a target IP address to be probed, and the command line tool will display information such as delay duration and packet loss rate of each packet.

[0054] As an example, if there are a large number of probing machines, or they are evenly and densely distributed, there is a high probability that at least one probing machine has a delay duration to the target IP address lower than the threshold. In addition, there can be multiple probing machines in different regions with a delay duration to the target IP address lower than the threshold; therefore, the candidate attribution information determined by the region of the probing machine with a delay duration lower than the first duration threshold can be one or more, and similarly, the candidate attribution information determined by the region of the probing machine with a delay duration lower than the second duration threshold can also be one or more.

[0055] Based on this, the delay duration obtained by MTR probing and the delay duration obtained by Ping probing are used to attempt to obtain the candidate attribution region of the target IP address.

[0056] Based on this, the embodiment can obtain the delay duration from the probing machine to the target IP address through network probing initiated by the probing machine, and the distance between the probing machine and the target IP address has a positive correlation with the delay duration, based on which the candidate region information of some target IP addresses can be accurately determined based on the delay duration determined by network probing initiated by multiple probing machines, thereby improving the accuracy of subsequent determination of the region information of the target IP address.

[0057] In the network probing mode, the attribution region can be determined by the delay duration, and other types of information, such as attribution operator and attribution ASN, can also be attempted to be obtained. As an example, after the probing machine initiates MTR probing to each of the target IP addresses, it can be determined whether the DNS resolution result corresponding to the target IP address can be obtained; if so, candidate attribution information is obtained from the DNS resolution result.

[0058] As an example, the owner of some target IP address can configure some information for the IP address, based on which, the probe machine can include the DNS resolution result in the returned probe result of the MTR tool after initiating the MTR probe to the target IP address using the MTR tool, and the DNS resolution result can include the combination of one or more of the above-mentioned attribution information.

[0059] As an example, the following is the probe result obtained by a certain probe machine after initiating the MTR probe to the target IP address “47.242.49.218”: ttl 07-129.250.6.93-ntt.com-as2914-USA-6ms, ae-7.r26.tkokhk01.hk.bb.gin.ntt.net.

[0060] Among them, “6ms” represents the time length of the delay, and “ae-7.r26.tkokhk01.hk.bb.gin.ntt.net.” is the DNS resolution result.

[0061] The DNS resolution result includes the domain name corresponding to the target IP address: “ae-7.r26.tkokhk01.hk.bb.gin.ntt.net.”. The attribution information can be obtained from the domain name, for example, “hk” represents the regional information, and “ntt.com” represents the attribution operator. Optionally, a plurality of strings corresponding to the attribution regions (for example, a plurality of English abbreviations of different attribution regions) and a plurality of strings of attribution operators (for example, a plurality of English abbreviations of different attribution operators) can be prepared in advance to identify and extract the attribution region or the attribution operator from the DNS resolution result.

[0062] In other examples, the DNS resolution result can also include the attribution ASN, for example, the following is the DNS resolution result obtained by a certain probe machine after initiating the MTR probe to the target IP address “180.87.169.10”: ix-be-6.ecore1.hk2-hongkong.as6453.net;

[0063] Among them, the attribution region “hk” and the attribution ASN “as6453” are included; wherein, the identification of the ASN can be determined by identifying whether the DNS resolution result includes a string composed of “as” and “numbers”, if the string composed of “as” and “numbers” exists, it can be determined as the attribution ASN.

[0064] In some examples, the plurality of different geographical detection machines can respectively initiate MTR detection to the target IP address. In general, if the target IP address is not an Anycast IP, and the owner of the target IP address configures some information for the IP address, the ownership information contained in the DNS resolution result obtained by each detection machine after initiating MTR detection is generally consistent.

[0065] Based on this, through MTR detection, if the DNS resolution result can be obtained, the candidate ownership region, candidate ownership operator or candidate ownership ASN of the target IP address or a combination of one or more of them can be obtained through the DNS resolution result.

[0066] Based on this, the embodiment can determine the candidate region information of some target IP addresses through the network detection initiated by the detection machine through the DNS resolution result, thereby expanding the source of the candidate ownership information of the target IP address, and improving the accuracy of subsequent determination of the ownership information of the target IP address.

[0067] In some examples, the ownership region can also be obtained according to the MTR detection result. As an example, the candidate ownership information can be obtained by the following method: obtaining the MTR detection result of the detection machine to the target IP address, which can include the network path from the detection machine to the intermediate forwarding node, and then to the node corresponding to the target IP address, and the time length of the delay of the detection machine to each node; try to configure the ownership region for each node in the network path by the following method: after determining the ownership region of the node with a delay time length less than a third time threshold between the detection machine as the geographical region of the detection machine, if the delay time length between the target node without configured ownership region and the last node with configured ownership region is less than the third time threshold, the ownership region of the target node is configured as the ownership region of the last node; after completing the configuration of the ownership region, if the node corresponding to the target IP address is configured with an ownership region, the ownership region configured by the corresponding node is taken as the candidate ownership information of the target IP address.

[0068] As shown in FIG. 2A, it is a schematic diagram of detecting a network path between a probe machine and a target IP address according to an exemplary embodiment of the present disclosure, including the probe machine, a plurality of intermediate forwarding nodes (three nodes are taken as an example in the figure) and a node corresponding to the target IP address. In the MTR detection result, the time length of the delay between the probe machine and each node in the network path is included, for example, the time length 1 of the delay between the probe machine and node 1, the time length 2 of the delay between the probe machine and node 2, and so on, and the time length of the delay between the probe machine and the target IP address. The geographical information of each node in the network path can be attempted to be configured according to the region where the probe machine is located and the above-mentioned time length of the delay.

[0069] As an example, the present embodiment can attempt to configure the geographical information of each node in the network path according to the following two principles.

[0070] ① The node whose time length of the delay with the probe machine is lower than a third time length threshold value is configured with the region where the probe machine is located as its home region; the third time length threshold value can be configured as needed, for example, 5 milliseconds or 10 milliseconds or other values.

[0071] ② The node whose time length of the delay with the previous node is lower than the third time length threshold value is configured with the region where the previous node is located as its home region.

[0072] For example, if the time length 1 of the delay between the probe machine and node 1 is lower than the third time length threshold value, the home region of node 1 is the region where the probe machine is located. However, the time length 1 of the delay between the probe machine and node 2 is higher than the third time length threshold value, so the home region of node 2 has not been configured. Since node 1 has been configured with the home region, and the time length of the delay between node 2 and node 1 can be obtained by subtracting the time length 1 of the delay between the probe machine and node 1 from the time length 2 of the delay between the probe machine and node 2, if the time length of the delay between node 2 and node 1 is lower than the third time length threshold value, the home region of node 2 is the home region of node 1. In this way, all nodes in the network path are traversed, and the nodes that meet the above-mentioned rules can be configured with the home region.

[0073] In this way, through the above-mentioned method, all nodes in the network path can be configured with the home region, or some nodes may not be able to be configured with the home region. If the configuration of the home region of the network path is completed, and the node corresponding to the target IP address is configured with the home region, the home region configured by the corresponding node can be taken as the candidate home region of the target IP address.

[0074] Based on this, through the above-mentioned method, the present embodiment can attempt to obtain the candidate home information of the target IP address based on the MTR detection result, thereby providing more information sources for subsequent determination of the home information of the target IP address, thereby improving the accuracy of the home information determination.

[0075] In some examples, the self-constructed IP address information library can include an IP address information library of a cloud computing service provider and / or a user information library, the IP address information library of the cloud computing service provider storing pre-collected home information of IP addresses provided by the cloud computing service provider, and the user information library storing pre-collected home information of IP addresses provided by a user.

[0076] As an example, a cloud computing service provider provides services for users, and is therefore usually configured with a machine room, which usually has a large number of machines. The cloud computing service provider usually also purchases a large number of IP address segments from a network operator to configure IP addresses for the machines. Considering that the positions of the machines in the machine room are usually fixed, the home information of the IP address segments owned by the cloud computing service provider usually does not change frequently. Based on this, the embodiment can pre-collect home information of IP addresses provided by the cloud computing service provider, and establish an IP address information library of the cloud computing service provider. Based on this, if a target IP address for which home information is to be determined has a record in the database, candidate home information can be obtained from the database. The candidate home information can include one or a combination of candidate home regions, candidate home operators, or candidate home ASNs.

[0077] As another example, a user information library can also be constructed, and pre-collected home information of IP addresses provided by a user can be stored in the database. As an example, some cloud computing service providers provide cloud computing services for a large number of users, and some users can also own some machines and IP addresses. During the use of the cloud computing services by the users, the users can provide home information of some IP addresses through some ways, and therefore, the home information of the IP addresses provided by the users can be pre-collected through manual or other ways. Based on this, if a target IP address for which home information is to be determined has a record in the database, candidate home information can be obtained from the database. The candidate home information can include one or a combination of candidate home regions, candidate home operators, or candidate home ASNs.

[0078] As can be seen from the above embodiments, the embodiment expands the source of home information of IP addresses by self-constructing an IP address information library, thereby improving the accuracy of home information determination.

[0079] In some examples, there can be other ways to obtain the information. For example, the home information can include an autonomous system number (ASN), and the self-built IP address information database can include a route collector system that stores an autonomous system path list between a router and an IP address segment. The candidate home information of the target IP address can be obtained by: obtaining an autonomous system path list from the router to the target IP address segment from the route collector system; and taking the last non-private ASN in the autonomous system path list as the candidate home information of the target IP address.

[0080] For example, some service providers can build a route collector system, such as some cloud computing service providers building a route collector system to obtain and store an autonomous system path list (AS-Path) of a router in the process of sending traffic from one IP address to another IP address when providing cloud computing services to users. The route collector system can store a plurality of autonomous system path lists of a router to an IP address segment. For a target IP address whose home information is to be determined, one of the AS-Paths of a router to the target IP address can be obtained from the route collector system. For example, in the case of multiple AS-Paths of a router to the target IP address, the shortest AS-Path can be obtained.

[0081] For example, the AS-Path is a list of autonomous systems that a router passes through to an IP address, which includes each node passed through and the ASN of each node in the process of sending traffic from the router to the IP address. Each autonomous system (AS) has a unique ASN (autonomous system number). In the AS-Path, the last ASN is the ASN of the target IP address. However, sometimes the AS-Path contains private ASNs, which are not public ASNs. Therefore, in this embodiment, the "last non-private ASN" refers to the last ASN in the AS-Path excluding private ASNs, i.e., the public ASN closest to the target IP address, so that the accurate candidate home ASN information of the target IP address can be determined.

[0082] For example, some network protocols, such as the Border Gateway Protocol, define the range of private ASNs as numbers greater than 4200000000 and numbers between 64512 and 65535. Therefore, ASNs with ASN_num>4200000000 or (ASN_num>=64512 and ASN_num<=65535) can be identified from the AS-Path as private ASNs.

[0083] In step 104, the home information of the target IP address can be determined according to preset weights of each candidate home information of the target IP address, wherein the preset weights are in positive correlation with the reliability of the acquisition manner of the candidate home information.

[0084] As an example, if there are multiple candidate home information of the target IP address, such as candidate home region, candidate home operator or candidate home ASN, the home information of the target IP address of each type of candidate home information can be determined. For example, the home region of the target IP address can be determined according to each candidate home region of the target IP address, and the other two types of home information are the same.

[0085] As an example, the preset weights can be set based on the reliability of the acquisition manner of the candidate home information, and the specific values can be configured according to actual needs, which are not limited in the embodiment.

[0086] As an example, the size relationship of the preset weights corresponding to each acquisition manner in the different acquisition manners is from high to low in turn: from the self-constructed IP address information library, through network detection and from the public IP address information library. In the embodiment, since the IP address information in the self-constructed IP address information library is self-constructed, the information is the most reliable, and therefore the preset weight is the largest. The second is network detection, which can access the target IP address through the detection machine to obtain network information, although it may be affected by the network condition, but it can also provide the current more accurate information, and therefore the preset weight of the network detection manner is the second. The last is the public IP address information library, the updating speed of the address information in the public information library may not be timely, and the information source is unknown, and therefore the preset weight is set to the lowest. Based on this, the embodiment analyzes the reliability of the three manners and sets the corresponding preset weights, so that the home information of the target IP address can be accurately determined based on the preset weights corresponding to each acquisition manner and the comprehensive information from multiple sources.

[0087] As an example, for each type of candidate home information, how to determine the home information of the target IP address of the type based on the preset weight of each acquisition manner can have multiple implementation manners.

[0088] ① The candidate home information acquired by the acquisition manner with the highest preset weight can be selected as the final home information according to the preset weight of each acquisition manner.

[0089] ② The preset weight of each acquisition manner and the number of each candidate home information hit by different acquisition manners can be determined.

[0090] As a certain target IP address, when the above embodiment is implemented, there are 7 obtaining manners to obtain the following candidate home regions.

[0091] A way, through the public IP address library, the candidate home region A obtained is R1; the weight of this obtaining manner is RαA.

[0092] B way, through the MTR detection, the candidate home region B set obtained is R2 and R3; the weight of this obtaining manner is RαB.

[0093] C way, through the MTR detection, the DNS result, the candidate home region C obtained is R2; the weight of this obtaining manner is RαC.

[0094] D way, through the Ping detection, the candidate home region D set obtained is R2; the weight of this obtaining manner is RαD.

[0095] E way, through the IP address information library of the cloud computing service party, the candidate home region E obtained is R3; the weight of this obtaining manner is RαE.

[0096] F way, through the user information library, the candidate home region F obtained is empty; the weight of this obtaining manner is RαF; and.

[0097] As an example, the preset weight corresponding to each candidate home region obtaining manner can be RαF>RαE>RαD and RαB≥RαA≥RαC.

[0098] Based on this, since in the above example, the weight of R2 obtained is the highest, R2 can be selected as the home region of the target IP address. Alternatively, the number of each candidate home region can also be combined to determine that for R1, it appears once, and its score is the weight A; for R2, it appears 3 times, and its score is the sum of the weights B, C and D divided by 3; for R3, it is calculated twice, and its score is the sum of the weights B and E divided by 2; the candidate home region with the highest score is determined as the home region of the target IP address.

[0099] The determination manner of the home operator of the target IP address is also the same. It is assumed that the following candidate home operators are obtained.

[0100] A way, through the public IP address library, the candidate home operator A obtained is Y1; the weight of this obtaining manner is YαA.

[0101] B way, through the MTR detection, if the DNS resolution result is obtained, the candidate home operator B obtained is Y2; the weight of this obtaining manner is YαB.

[0102] The candidate operator C obtained by the C method through the IP address information base of the cloud computing service provider is Y3, and the weight of the obtaining method is YαC.

[0103] The candidate operator D obtained by the D method through the user information base is Y4, and the weight of the obtaining method is YαD.

[0104] As an example, the relationship between the preset weights corresponding to the various candidate home operators obtaining methods described above can be YαD> YαC> YαA and YαB.

[0105] The home operator of the target IP address can be determined based on the preset weights described above.

[0106] The determination method of the home ASN of the target IP address is the same, assuming that the following candidate home ASNs are obtained.

[0107] The candidate home ASN_A obtained by the A method through the public IP address base is A1, and the weight of the obtaining method is AαA.

[0108] The candidate home ASN_B obtained by the B method through MTR detection is A2 if the DNS resolution result is obtained, and the weight of the obtaining method is AαB.

[0109] The candidate ASN_C obtained by the C method through the IP address information base of the cloud computing service provider is A3, and the weight of the obtaining method is AαC.

[0110] The candidate ASN_D obtained by the D method through the user information base is A4, and the weight of the obtaining method is AαD.

[0111] The candidate ASN_E obtained by the E method through the routing collection system is A5, and the weight of the obtaining method is AαE.

[0112] As an example, the relationship between the preset weights corresponding to the various candidate home ASN obtaining methods described above can be AαD> AαE> AαC> AαA and AαB.

[0113] The home ASN of the target IP address can be determined based on the preset weights described above.

[0114] After determining the home region, home operator and home ASN of each target IP address in the target IP address segment by the above method, the home region, home operator and home ASN of the target IP address segment can be determined respectively.

[0115] In some examples, the determining the ownership information of the target IP address segment according to the ownership information of each target IP address in the target IP address segment can include: determining the number of target IP addresses of each ownership information according to the ownership information of each target IP address in the target IP address segment; and determining the ownership information of the target IP address segment according to the number of target IP addresses of each ownership information.

[0116] Taking the ownership region as an example, there are n target IP addresses in the target IP address segment, and the n target IP addresses correspond to m ownership regions. The number of target IP addresses corresponding to each ownership region in the m ownership regions can be the same or different. The ownership region of the target IP address segment is determined based on the number of target IP addresses corresponding to each ownership region. The specific determination manner can be adjusted according to actual needs. For example, the ownership region with the highest number of corresponding target IP addresses can be determined as the ownership region of the target IP address segment. If the number of target IP addresses corresponding to at least two different ownership regions is the same, one of the two or the ownership region of the target IP address segment can be determined in combination with other manners.

[0117] The determination manners of the ownership operator and the ownership ASN are the same. Therefore, the embodiment can accurately determine the ownership information of the target IP address segment by determining the number of target IP addresses of each ownership information based on the ownership information of each target IP address.

[0118] In some examples, the ownership information includes region information, and the determining the ownership information of the target IP address segment according to the number of target IP addresses of each ownership information can include: determining the ownership information of the target IP address segment according to the number of target IP addresses of each ownership information and the population number.

[0119] As an example, for the region information, the population number corresponding to each ownership region information can also be obtained, and the ownership information of the target IP address segment is determined in combination with the number of target IP addresses of each ownership information and the population number. For example, in the foregoing example, the target IP address segment involves m ownership regions, and the ownership region of the target IP address segment can be determined by the number of target IP addresses of each ownership region and the population number corresponding to each ownership region in the m ownership regions. The larger the number of target IP addresses and the larger the population number, the greater the possibility that the ownership region is the ownership region of the target IP address segment.

[0120] For example, the weighted score of each home region can be obtained, the weighted score being determined according to the number of target IP addresses and the population number of the home region, and the weights corresponding to the number of target IP addresses and the population number can be set according to actual needs. Alternatively, the number of target IP addresses corresponding to each home region can be determined first, and if the number of target IP addresses corresponding to at least two home regions among the m home regions is the highest and the difference in the number of target IP addresses is lower than a preset threshold, then the population number of the at least two home regions is combined to determine the home region of the target IP address segment.

[0121] Based on this, the embodiment further combines the population number with the regional information to accurately determine the home information of the target IP address segment.

[0122] As an example, the method of the embodiment can further include: storing the determined target IP address segment and corresponding home information in a database; and if a home information query request of a to-be-queried IP address is received, querying the corresponding home information from the database according to the IP address segment corresponding to the to-be-queried IP address and returning the home information.

[0123] As an example, after the home information of the target IP address segment is determined, a database can be constructed to store each kind of home information of each IP address segment. As shown in FIG. 2B, the database can be used to provide a home information query service of an IP address. Any user can submit a home information query request of a to-be-queried IP address, the corresponding home information can be queried from the database according to the IP address segment corresponding to the to-be-queried IP address and returned, so that an accurate home information query service of an IP address can be provided for the user.

[0124] As an example, each kind of home information of an IP address segment in the database can be attached with a time stamp to mark the time when each kind of home information is determined. Optionally, the embodiment can be repeatedly executed based on a preset period to update each kind of home information of each IP address segment in the database. For example, based on the time stamp of each kind of home information, the home information that is far away from the current time is re-executed to obtain the latest home information, and whether the home information needs to be updated is determined according to the latest home information, so that the database of the embodiment can record the latest home information continuously.

[0125] Next, in combination with FIG. 2C, an embodiment corresponding to each kind of home information is described.

[0126] 1. An embodiment of determining regional information.

[0127] (1) One or more public IP address information libraries can be used as information sources.

[0128] As an example, the disclosed IP address information library can store the ownership information of IP address segments, and can also store the ownership information of IP addresses. For each target IP address segment in the disclosed IP address information library, all target IP addresses in the target IP address segment are selected, or a plurality of target IP addresses are randomly selected through a random algorithm, or a plurality of target IP addresses are proportionally sampled.

[0129] As an example, the selected target IP address can refer to an IP address that has a response after a Ping request is initiated to the target IP address.

[0130] Candidate regional information A of the target IP address can be obtained based on the disclosed IP address information library. As an example, if the ownership regions of a target IP address segment in different disclosed IP address information libraries are the same, the ownership region recorded in the disclosed IP address information library is taken as the candidate ownership region A of the IP address segment.

[0131] (2) The candidate ownership region is obtained through MTR detection.

[0132] As an example, a plurality of detection machines in different regions in the world can be selected, and MTR detection is initiated to each target IP address.

[0133] For MTR detection, if the time delay of a detection machine to a target IP address is less than a certain value, the geographical position of the detection machine is taken as the candidate ownership region B of the target IP address. There can be a plurality of detection machines whose time delays satisfy the above condition, so the candidate ownership region B can be a set, that is, it can contain one or more candidate regional information.

[0134] Optionally, if the MTR detection result contains the DNS resolution result of the target IP address, the specific regional information contained in the DNS resolution result can be taken as the candidate ownership region C of the target IP address.

[0135] Optionally, if the MTR detection result does not contain the DNS resolution result, the network path and the time delay of the detection machine to each node in the network path contained in the MTR detection result can be used to attempt to obtain the candidate ownership region C of the target IP address. The specific obtaining process can be seen in the foregoing embodiments.

[0136] (3) The candidate ownership region is obtained through Ping detection.

[0137] As an example, a plurality of detection machines in different regions in the world can be selected, and Ping detection is initiated to each target IP address.

[0138] For Ping detection, if the time delay of a detection machine to a target IP address is less than a certain value, the geographical location of the detection machine is taken as a candidate home region D of the target IP address. There can be multiple detection machines whose time delays satisfy the above condition, and therefore the candidate home region D can be a set, that is, it can contain one or more candidate region information.

[0139] (4) Obtain the candidate home region E through an IP address information library of a cloud computing service provider.

[0140] For example, query the IP address information library to determine whether there is home information of the target IP address. If there is, the candidate home region E is obtained; if not, the candidate home region E is empty.

[0141] (5) Obtain the candidate home region F through a user information library.

[0142] For example, the user information library is constructed in advance by an operation expert knowledge, which stores the home information of the IP address provided by the user. Query the IP address information library to determine whether there is home information of the target IP address. If there is, the candidate home region F is obtained; if not, the candidate home region F is empty.

[0143] (6) For each target IP address, the home region information of the target IP address is determined by using each candidate home region of each target IP address and the weight of each acquisition method. The specific determination method can be seen in the foregoing embodiments.

[0144] (7) Determine the home information of the target IP address segment according to the home information of each target IP address in the target IP address segment.

[0145] As an example, it can be the region information to which the most IP addresses in the IP address segment belong. For example, the home region of the IP address segment can be:

[0146] Among them, argmax represents the input value for finding the maximum value of the function. Optionally, the population number of the home region can also be combined to determine, which can be seen in the foregoing embodiments.

[0147] 2. Embodiments for determining ISP information.

[0148] (1) One or more public IP address information libraries can be used as information sources.

[0149] Among them, the target IP address is selected as in the foregoing embodiments, which will not be described here. The candidate home operator A of the target IP address can be obtained based on the public IP address information library.

[0150] (2) Obtain the candidate home operator through MTR detection.

[0151] MTR probe can be initiated to each target IP address by one or more probe machines. Optionally, if the MTR probe result contains the DNS resolution result of the target IP address, the specific operator information contained in the DNS resolution result can be taken as the candidate home operator B of the target IP address.

[0152] (3) Obtain the candidate home operator C through the IP address information library of the cloud computing service party.

[0153] For example, query from the IP address information library whether there is the home operator information of the target IP address, if yes, take it as the candidate home operator C; if no, the candidate home operator C is empty.

[0154] (4) Obtain the candidate home operator D through the user information library.

[0155] For example, the user information library is constructed by the expert knowledge in advance, which stores the home information of the IP address provided by the user. Query from the IP address information library whether there is the home operator information of the target IP address, if yes, take it as the candidate home operator D; if no, the candidate home operator D is empty.

[0156] (5) For each target IP address, determine the home operator of the target IP address by using each candidate home operator of each target IP address and the weight of each acquisition method. The specific determination method can be seen in the foregoing embodiments.

[0157] (6) Determine the home operator of the target IP address segment according to the home operators of each target IP address in the target IP address segment.

[0158] As an example, it can be the operator information to which the most IP addresses in the IP address segment belong. For example, the home operator of the IP address segment can be:

[0159] 3. Embodiment of determining home ASN information.

[0160] (1) One or more public IP address information libraries can be used as information sources.

[0161] Among them, the target IP address is selected as in the foregoing embodiments, which will not be repeated here. The candidate home ASN_A of the target IP address can be obtained based on the public IP address information library.

[0162] (2) Obtain the candidate home ASN through MTR probe.

[0163] The MTR probe can be initiated by one or more probe machines to each target IP address. Optionally, if the MTR probe result contains the DNS resolution result of the target IP address, the specific ASN information contained in the DNS resolution result can be used as the candidate home ASN_B of the target IP address.

[0164] (3) Obtain the candidate home ASN_C through the IP address information library of the cloud computing service party.

[0165] For example, query the IP address information library to determine whether there is a home ASN of the target IP address. If there is, use it as the candidate home ASN_C. If there is not, the candidate home ASN_C is empty.

[0166] (4) Obtain the candidate home ASN_D through the user information library.

[0167] For example, the user information library is constructed in advance by an operation expert knowledge, which stores the home information of the IP address provided by the user. Query the IP address information library to determine whether there is home ASN information of the target IP address. If there is, use it as the candidate home ASN_D. If there is not, the candidate home ASN_D is empty.

[0168] (5) Obtain the candidate home ASN_E using the route collection system.

[0169] For example, from the route collection system, obtain the autonomous system path list from the target router to the target IP address segment, and use the last non-private ASN in the autonomous system path list as the candidate home ASN_E of the target IP address. If the route collection system does not obtain it, the candidate home ASN_E can be empty.

[0170] (5) For each target IP address, determine the home ASN of the target IP address using each candidate home ASN of each target IP address and the weight of each acquisition method. The specific determination method can be found in the foregoing embodiments.

[0171] (6) Determine the home ASN of the target IP address segment according to the home ASN of each target IP address in the target IP address segment.

[0172] As an example, it can be the ASN to which the most IP addresses in the IP address segment belong. For example, the home ASN of the IP address segment can be:

[0173] In the related art, only a single information source or a single method is usually used to determine the single-dimension attribution information of the IP address. The embodiment considers that the single-source attribution information may become invalid over time. The embodiment obtains the attribution information of the IP address segment by weighting the attribution regions, attribution operators and attribution ASNs of different information sources, so as to make the attribution information more accurate, and overcomes the problem that the single-source attribution information may become invalid over time by establishing a long-term detection mechanism and expert knowledge revision.

[0174] Corresponding to the foregoing embodiment of the method for determining the attribution information of the IP address segment, the disclosure also provides an embodiment of a device for determining the attribution information of the IP address segment and a computer device to which the device is applied.

[0175] The embodiment of the device for determining the attribution information of the IP address segment can be applied to a computer device, such as a server or a terminal device. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. For example, the software implementation is a logical device formed by reading the corresponding computer program instructions in the non-volatile memory into the memory for execution by the processor. From the hardware perspective, as shown in FIG. 3, it is a hardware structure diagram of the computer device to which the device for determining the attribution information of the IP address segment belongs. In addition to the processor 310, network interface 320, memory 330 and non-volatile memory 340 shown in FIG. 3, the computer device to which the device for determining the attribution information of the IP address segment belongs in the embodiment usually includes other hardware according to the actual function of the computer device, which is not described again.

[0176] As an example, the embodiment of the disclosure also provides a device for determining the attribution information of the IP address segment, which can include:

[0177] An address acquisition module is configured to acquire a target IP address in a target IP address segment whose attribution information is to be determined.

[0178] An address attribution information acquisition module is configured to acquire candidate attribution information of the target IP address by different acquisition methods, and then determine the attribution information of the target IP address according to preset weights of the candidate attribution information of the target IP address. The preset weights are positively correlated with the reliability of the acquisition method of the candidate attribution information.

[0179] An address segment attribution information module is configured to determine the attribution information of the target IP address segment according to the attribution information of each target IP address in the target IP address segment.

[0180] The implementation process of the functions and roles of each module in the above IP address segment ownership information determining apparatus is specifically described in the implementation process of the corresponding steps in the above IP address segment ownership information determining method, and thus will not be described here.

[0181] Correspondingly, the present disclosure also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned IP address segment ownership information determining method embodiment.

[0182] Correspondingly, the present disclosure also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the IP address segment ownership information determining method embodiment when executing the program.

[0183] Correspondingly, the present disclosure also provides a computer-readable storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the steps of the IP address segment ownership information determining method embodiment.

[0184] For the device embodiment, since it basically corresponds to the method embodiment, the related parts can be referred to the part of the method embodiment. The device embodiment described above is only illustrative, wherein the modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical modules, i.e., they can be located in one place or distributed on multiple network modules. Some or all of the modules can be selected to achieve the purpose of the present disclosure according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0185] The above embodiments can be applied to one or more computer devices, which is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions. The hardware of the computer device includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0186] The computer device can be any electronic product that can interact with a user, such as a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), a game console, an interactive Internet Protocol Television (IPTV), a smart wearable device, etc.

[0187] The computer device can also include a network device and / or a user device. The network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on cloud computing.

[0188] The network in which the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), etc.

[0189] The above describes specific embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than the order in which they are recited and still achieve the desired results. In addition, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous or necessary.

[0190] The division of steps in the above methods is only for the purpose of clear description. When implemented, a step can be combined into one or some steps can be split into multiple steps, as long as the same logical relationship is included, which is within the protection scope of the present patent; adding insignificant modifications or introducing insignificant designs in the algorithm or process, but not changing the core design of the algorithm and process, are within the protection scope of the present application.

[0191] Although the present disclosure contains many specific embodiments, these should not be construed as limiting any of the claims in scope or the scope of the claims to be required, but are mainly used to describe the features of the specific embodiments of the particular application. Some features described in the present disclosure in multiple embodiments can also be implemented in a single embodiment. On the other hand, various features described in a single embodiment can also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although the features can function in some combinations as described above and even initially so claimed, one or more features from a claimed combination can be removed in some cases, and the claimed combination can be directed to a sub-combination or a variation of a sub-combination.

[0192] Where a range of values is provided, it is intended to encompass both endpoints and intervening values. Any intervening value not explicitly recited is "part of the scope of the application" or "within the scope of the application." For values which are less than one, or contain an un-specifiable value such as less than about, it is intended that the greater value is encompassed. For values which are greater than one or contain an un-specifiable value such as greater than about, it is intended that the lesser value is encompassed. Whenever a compositional limitation is recited, it is intended to encompass the compositional range explicitly recited, and also implicitly recited compositions outside the stated range. For example, if a composition is recited as being "about 1% to about 5%," it is intended that "about 1%" and "about 5%" are encompassed within the scope of the application. Whenever a compositional limitation is recited, it is intended to encompass the compositional range explicitly recited, and also implicitly recited compositions outside the stated range. For example, if a composition is recited as being "about 1% to about 5%," it is intended that "about 1%" and "about 5%" are encompassed within the scope of the application.

[0193] Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the disclosure being indicated by the following claims.

[0194] It is to be understood that the disclosure is not limited to the precise construction herein described and as shown in the attached drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the disclosure. The scope of the disclosure is limited only by the claims that follow.

[0195] The above description is intended to be illustrative and not restrictive. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the disclosure should, therefore, be determined not with reference to the above description, but instead with reference to the appended claims, along with their full scope of equivalents.

Claims

1. A method for determining the ownership information of an IP address segment, the method comprising: obtaining target IP addresses in a target IP address segment for which ownership information is to be determined; obtaining candidate ownership information of the target IP addresses by different obtaining manners, and determining the ownership information of the target IP addresses according to preset weights of the candidate ownership information of the target IP addresses, wherein the preset weights are positively correlated with the reliability of the obtaining manner of the candidate ownership information; and determining the ownership information of the target IP address segment according to the ownership information of the target IP addresses in the target IP address segment. 2.The method of claim 1, wherein the determining the ownership information of the target IP address segment according to the ownership information of the target IP addresses in the target IP address segment comprises: determining the number of target IP addresses of each ownership information according to the ownership information of the target IP addresses in the target IP address segment; and determining the ownership information of the target IP address segment according to the number of target IP addresses of each ownership information. 3.The method of claim 2, wherein the ownership information comprises regional information, and the determining the ownership information of the target IP address segment according to the number of target IP addresses of each ownership information comprises: determining the ownership information of the target IP address segment according to the number of target IP addresses of each ownership information and the population number. 4.A method for obtaining the ownership information of an IP address, the method comprising: obtaining target IP addresses in a target IP address segment; obtaining candidate ownership information of the target IP addresses by different obtaining manners; and determining the ownership information of the target IP addresses according to preset weights of the candidate ownership information of the target IP addresses, wherein the preset weights are positively correlated with the reliability of the obtaining manner of the candidate ownership information. 5.A cloud computing service provider's IP address information database and / or a user information database, wherein the cloud computing service provider's IP address information database stores the ownership information of IP addresses provided by the cloud computing service provider, and the user information database stores the ownership information of IP addresses provided by the user. 6.The method of claim 4, wherein the ownership information comprises a home region, and the network detection comprises: initiating MTR detection to each of the target IP addresses by a plurality of detection machines distributed in different regions, obtaining the time length of the delay of each detection machine accessing the target IP addresses, and determining the region of the detection machine with a time length of the delay lower than a first time threshold as candidate ownership information; and / or initiating Ping detection to each of the target IP addresses by a plurality of detection machines distributed in different regions, obtaining the time length of the delay of each detection machine accessing the target IP addresses, and determining the region of the detection machine with a time length of the delay lower than a second time threshold as candidate ownership information. 7.The method of claim 4, wherein the network detection comprises: determining whether the DNS resolution result corresponding to the target IP addresses can be obtained after initiating MTR detection to each of the target IP addresses by a detection machine; and obtaining candidate ownership information from the DNS resolution result if the DNS resolution result corresponding to the target IP addresses can be obtained. 8.The method of claim 7, wherein the ownership information comprises a home region, and the candidate ownership information is obtained by: ​ 4. The method of claim 1, the different acquisition modes comprising: ​ 5. The method of claim 4, the self-constructing IP address information base comprising: ​ ​ ​ ​ ​ ​ ​ ​ ​ obtaining an MTR probe result of the probe machine to the target IP address, the MTR probe result comprising: a network path from the probe machine to an intermediate forwarding node and then to the target IP address corresponding node, and a time length of a delay from the probe machine to each of the nodes; configuring a home region for each node in the network path by determining a home region of a node with a time length of a delay from the probe machine lower than a third time length threshold as a home region of the probe machine, and then configuring a home region of a target node without a configured home region information as a home region of a last node with a configured home region if a time length of a delay between the target node and the last node is lower than the third time length threshold; after the configuration of the home region is completed, if the target IP address corresponding node is configured with a home region, taking the home region configured by the target IP address corresponding node as candidate home information of the target IP address.

9. The method of claim 4, the home information comprising: a home autonomous system number (ASN); the self-built IP address information library comprises a route collection system for storing an autonomous system path list between a router and an IP address segment; the candidate home information of the target IP address is obtained by: obtaining an autonomous system path list from a target router to the target IP address segment from the route collection system; taking a last non-private ASN in the autonomous system path list as the candidate home information of the target IP address.

10. The method of claim 1, the target IP address comprising: an IP address with a response after a Ping request to the target IP address is initiated.

11. The method of any one of claims 4 to 10, wherein a size relationship of preset weights corresponding to each of the different obtaining manners is, from high to low, in an order of: obtaining from the self-built IP address information library, obtaining through network detection, and obtaining from the public IP address information library.

12. The method of any one of claims 1 to 10, further comprising: storing the determined target IP address segment and corresponding home information into a database; and if a home information query request of a to-be-queried IP address is received, querying corresponding home information from the database according to an IP address segment corresponding to the to-be-queried IP address and returning the corresponding home information.

13. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, The processor implements the steps of the method of any one of claims 1 to 12 when executing the computer program.

14. A computer program product comprising a computer program, wherein the computer program implements the steps of the method of any one of claims 1 to 12 when executed by a processor.

15. A computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method of any one of claims 1 to 12 when executed by a processor.

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