Blockchain address risk identification method, device, equipment and program product

Abstract

The application is suitable for the field of blockchain technology, and provides a risk identification method, device, equipment and program product of a blockchain address. The method comprises the following steps: obtaining N associated address sets of a target blockchain address; the associated address sets comprise a first-level associated address set to an N-level associated address set; the first-level associated address set comprises a first-level associated address; the N-level associated address set comprises an N-level associated address; the first-level associated address is an address having a transaction record with the target blockchain address; the N-level associated address is an address having a transaction record with an (N-1)-level associated address; and risk factors of the target blockchain address are determined according to risk information of the N associated address sets. According to the risk information of the first-level associated address set to the N-level associated address set, the method can determine the risk factors of the target blockchain address, can quickly determine whether the target blockchain address is a successor address, and improves the security of the blockchain.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of blockchains, and particularly relates to a blockchain address risk identification method and device, equipment and program product. BACKGROUND

[0002] There are many risk activities in the blockchain field, such as fraud, phishing and money laundering, and the common means to deal with these risk activities is to identify the risk of a blockchain address, so as to identify a blockchain address with risk factors, and then monitor the blockchain address with risk factors to help users prevent risk activities.

[0003] However, since the cost of generating a blockchain address is very low, when a certain risk address is identified and sanctioned, the person engaging in the risk activity may continuously generate a new blockchain address as a successor address to replace the risk address for risk activities. Since risk identification of a blockchain address requires a certain amount of time, the existing risk identification method of a blockchain address is difficult to identify the risk factors of the successor address in a timely manner, and thus cannot monitor the successor address in a timely manner, reducing the security of the blockchain. SUMMARY

[0004] Therefore, the embodiments of the present application provide a blockchain address risk identification method, device, equipment and program product to solve the technical problem of low security of the existing blockchain.

[0005] In a first aspect, the embodiments of the present application provide a blockchain address risk identification method, comprising:

[0006] Obtaining a set of N associated addresses of a target blockchain address; wherein the set of N associated addresses comprises a first-level associated address set to an N-level associated address set, the first-level associated address set comprises at least one first-level associated address, the N-level associated address set comprises at least one N-level associated address, the first-level associated address is a blockchain address having a transaction record with the target blockchain address, the N-level associated address is a blockchain address having a transaction record with an N-1-level associated address, and N is an integer greater than or equal to 1;

[0007] According to the risk information of the set of N associated addresses, determining the risk factors of the target blockchain address.

[0008] Optionally, the risk information includes a risk address; and the determining of the risk factors of the target blockchain address according to the risk information of the set of N associated addresses comprises:

[0009] According to the risk address of each of the set of N associated addresses, respectively determining the risk factors of each of the set of N associated addresses.

[0010] According to the risk factors of the N sets of associated addresses respectively, the risk factors of the target blockchain address are determined.

[0011] Optionally, the determining the risk factors of the N sets of associated addresses respectively according to the risk addresses of the N sets of associated addresses respectively comprises:

[0012] For a first-level set of associated addresses in the N sets of associated addresses, each risk address of the first-level set of associated addresses is obtained;

[0013] For each risk address in each risk address, according to all transaction records between the risk address and the target blockchain address, it is determined whether there is a risk transmission relationship between the risk address and the target blockchain address;

[0014] According to the risk factors of all risk addresses in each risk address and the target blockchain address, the risk factors of the first-level set of associated addresses are determined.

[0015] Optionally, the determining whether there is a risk transmission relationship between the risk address and the target blockchain address according to all transaction records between the risk address and the target blockchain address comprises:

[0016] According to the all transaction records, the association degree score between the risk factors of the target blockchain address and the risk address is determined;

[0017] If the association degree score is greater than a preset association degree score threshold, it is determined that there is a risk transmission relationship between the risk address and the target blockchain address.

[0018] Optionally, the determining the risk factors of the first-level set of associated addresses according to the risk factors of all risk addresses in each risk address and the target blockchain address comprises:

[0019] The union of the risk factors of all risk addresses and the target blockchain address is taken as the risk factors of the first-level set of associated addresses.

[0020] Optionally, the determining the risk factors of the N sets of associated addresses respectively according to the risk addresses of the N sets of associated addresses respectively comprises:

[0021] For an N-level set of associated addresses in the N sets of associated addresses, each risk address of the N-level set of associated addresses is obtained;

[0022] For each of the risk addresses, whether there is a risk transmission relationship between the risk address and an N-1 level associated address set in the N associated address sets is determined according to all transaction records between the risk address and the N-1 level associated address set.

[0023] According to risk factors of all risk addresses in the risk addresses and having the risk transmission relationship with the N-1 level associated address set, risk factors of the N level associated address set are determined.

[0024] Optionally, the determining the risk factors of the target blockchain address according to the risk factors of the N associated address sets comprises:

[0025] The union set of the risk factors of the N associated address sets is taken as the risk factors of the target blockchain address.

[0026] In a second aspect, an embodiment of the present application provides a blockchain address risk identification device, comprising:

[0027] An address set acquisition unit is configured to acquire N associated address sets of a target blockchain address, wherein the N associated address sets comprise a first level associated address set and an N level associated address set, the first level associated address set comprises at least one first level associated address, the N level associated address set comprises at least one N level associated address, the first level associated address is a blockchain address having a transaction record with the target blockchain address, the N level associated address is a blockchain address having a transaction record with an N-1 level associated address, and N is an integer greater than or equal to 1.

[0028] A risk identification unit is configured to determine risk factors of the target blockchain address according to risk information of the N associated address sets.

[0029] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement each step of the blockchain address risk identification method of the first aspect.

[0030] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement each step of the blockchain address risk identification method of the first aspect.

[0031] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when running on an electronic device, causes the electronic device to perform each step of the method for identifying a risk of a blockchain address according to the first aspect.

[0032] The method, device, and program product for identifying a risk of a blockchain address provided by the embodiments of the present application have the following beneficial effects:

[0033] The method for identifying a risk of a blockchain address provided by the embodiments of the present application comprises the following steps: obtaining a first-level associated address set composed of each first-level associated address having a direct transaction record with the target blockchain address, and obtaining an Nth-level associated address set composed of each Nth-level associated address having an indirect transaction record with the target blockchain address; and determining a risk factor of the target blockchain address according to risk information of the first-level associated address set to the Nth-level associated address set. Considering that there is a direct or indirect transaction record between a risk address and a corresponding successor address, the method for identifying a risk provided by the embodiments of the present application can determine a risk factor of the target blockchain address according to risk information of each first-level associated address having a direct transaction record with the target blockchain address and risk information of each Nth-level associated address having an indirect transaction record with the target blockchain address, so that whether the target blockchain address is a successor address can be quickly determined, and measures can be taken in time when the target blockchain address is a successor address, thereby improving the security of the blockchain. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0035] Figure 1 An implementation flowchart of the method for identifying a risk of a blockchain address provided by the embodiments of the present application;

[0036] Figure 2 A structural schematic diagram of the device for identifying a risk of a blockchain address provided by the embodiments of the present application;

[0037] Figure 3 A structural schematic diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0038] It should be noted that the terms used in the embodiments of the present application are used only for the purpose of explaining the specific embodiments of the present application, and are not intended to limit the present application. In the description of the embodiments of the present application, "a plurality of" means two or more than two, and "at least one", "one or more" means one, two or more than two. The terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the "first", "second" features defined can explicitly or implicitly include one or more features.

[0039] In this specification, the phrase "one embodiment" or "some embodiments" etc. means that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Therefore, the phrases "in one embodiment", "in some embodiments", "in other some embodiments", "in further some embodiments" etc. appearing in different places in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "include", "contain", "have" and their variants mean "including but not limited to", unless otherwise specifically emphasized.

[0040] The risk identification method of the blockchain address provided by the embodiments of the present application can be applied to various scenarios that require risk identification of target blockchain addresses.

[0041] The execution subject of the risk identification method of the blockchain address provided by the embodiments of the present application can include but is not limited to electronic devices such as mobile phones, tablet computers, notebook computers and desktop computers.

[0042] At present, when a certain risk address is identified and sanctioned, the person engaging in the risk activity may generate a new blockchain address as a successor address to replace the risk address to engage in the risk activity. For example, the person engaging in the risk activity may generate a successor address A to replace a risk address B to engage in the risk activity, or the person engaging in the risk activity may generate a successor address A and a transit address C, and use the transit address C as a transit address of the successor address A and the risk address B, to achieve the purpose of using the successor address A to replace the risk address B to engage in the risk activity.

[0043] However, the current risk identification method of the blockchain address needs a certain time to identify whether a certain address has a risk factor, so the prior art cannot effectively and timely respond to the above situation of replacing the risk address with the successor address to engage in the risk activity.

[0044] Based on this, the embodiment of the present application provides a risk identification method of a blockchain address. By executing each step of the risk identification method of the blockchain address provided by the embodiment of the present application through an electronic device, whether the target blockchain address is a successor address can be quickly determined, thereby improving the security of the blockchain.

[0045] Please refer to Figure 1 , Figure 1 The implementation flowchart of the risk identification method of the blockchain address provided by the embodiment of the present application can include steps S101-S102, which are described in detail as follows.

[0046] In S101, a set of N associated addresses of a target blockchain address is obtained.

[0047] In the embodiment of the present application, when the risk identification of the target blockchain address is needed, the set of N associated addresses of the target blockchain address can be obtained through an electronic device.

[0048] The set of N associated addresses includes a first-level associated address set to an N-level associated address set. The first-level associated address set includes at least one first-level associated address, and the N-level associated address set includes at least one N-level associated address. The first-level associated address is a blockchain address that has a transaction record with the target blockchain address. The N-level associated address is a blockchain address that has a transaction record with the N-1-level associated address. N is an integer greater than or equal to 1.

[0049] For example, if the target blockchain address has transaction records with address 1, address 2, and address 3, address 1, address 2, and address 3 can be used as the first-level associated addresses of the target blockchain address. Therefore, the first-level associated address set can include address 1, address 2, and address 3.

[0050] If address 1 has transaction records with address 4 and address 5 in addition to the transaction record with the target blockchain address, address 2 has a transaction record with address 6 in addition to the transaction record with the target blockchain address, and address 3 has a transaction record with address 7 in addition to the transaction record with the target blockchain address, address 4, address 5, address 6, and address 7 can be used as the second-level associated addresses of the target blockchain address. Therefore, the second-level associated address set can include address 4, address 5, address 6, and address 7.

[0051] Similarly, if address 4 has transaction records with address 1, address 10 and address 11, if address 5 has transaction records with address 1 and address 12, if address 6 has transaction records with address 2 and address 13, and if address 7 has transaction records with address 3 and address 14, addresses 10, 11, 12, 13 and 14 can be regarded as the third-level associated addresses of the target blockchain address, and thus addresses 10, 11, 12, 13 and 14 can be included in the third-level associated address set.

[0052] The N-level associated address set can be obtained according to the same method as the above example, which will not be described here.

[0053] In a possible implementation, the user can input a transaction record time range into the electronic device, so that the electronic device can obtain the N associated address sets of the target blockchain address according to the transaction record time range.

[0054] For example, the user inputs a transaction record time range of one year, and if the target blockchain address has transaction records with address 1 and address 2 within one year, addresses 1 and 2 can be regarded as the first-level associated addresses of the target blockchain address, and thus addresses 1 and 2 can be included in the first-level associated address set.

[0055] If address 1 has transaction records with address 4 within one year in addition to the transaction records with the target blockchain address, if address 2 has transaction records with address 6 within one year in addition to the transaction records with the target blockchain address, and if address 3 has transaction records with address 7 within one year in addition to the transaction records with the target blockchain address, addresses 4, 6 and 7 can be regarded as the second-level associated addresses of the target blockchain address, and thus addresses 4, 6 and 7 can be included in the second-level associated address set.

[0056] The N-level associated address set can be obtained according to the same method as the above example, which will not be described here.

[0057] The electronic device can obtain the transaction records of the target blockchain address, and can obtain the N associated address sets of the target blockchain address according to the method described in the above example.

[0058] In S102, the risk factors of the target blockchain address are determined according to the risk information of the N associated address sets.

[0059] In the embodiments of the present application, after obtaining the N associated address sets of the target blockchain address, the electronic device can determine the risk factors of the target blockchain address according to the risk information of the N associated address sets.

[0060] In a possible implementation, the risk information can include risk addresses, based on which the electronic device can determine the risk factors of the target blockchain address through steps a to b, which are described as follows.

[0061] In step a, the risk factors of the N associated address sets are respectively determined according to the risk addresses of the N associated address sets.

[0062] In the present implementation, the electronic device can obtain each risk address in the first-level associated address set from the N associated address sets. The risk address can be an address that is considered to be risky by the electronic device, that is, an address that is considered to be used for engaging in risky activities by the electronic device.

[0063] In a possible implementation, the electronic device can determine the risk addresses in each associated address set according to the transaction records of each associated address.

[0064] In another possible implementation, in order to improve the efficiency of risk identification, the electronic device can determine the sanction addresses as the risk addresses. The sanction address can be an address that is considered to be risky and is sanctioned by the security agency of the blockchain, based on which the electronic device can obtain the information of the sanction addresses disclosed by the security agency of the blockchain, so as to determine each risk address in the first-level associated address set.

[0065] After obtaining each risk address in the first-level associated address set, the electronic device can determine, for each risk address in the risk addresses, whether there is a risk transmission relationship between the risk address and the target blockchain address according to all transaction records between the risk address and the target blockchain address.

[0066] For example, if the address 1, the address 2 and the address 3 in the first-level associated address set are all risk addresses, the electronic device can respectively determine whether there is a risk transmission relationship between the address 1, the address 2 and the address 3 and the target blockchain address according to all transaction records between the address 1, the address 2 and the address 3 and the target blockchain address.

[0067] The risk transmission relationship determination model can be determined in advance through training. The input of the risk transmission relationship determination model can be risk factors of the risk address and all transaction records between the risk address and the target blockchain address. The output of the risk transmission relationship determination model can be whether there is a risk transmission relationship between the risk address and the target blockchain address.

[0068] In order to more clearly illustrate the function of the risk transmission relationship determination model, some examples of determining whether there is a risk transmission relationship according to transaction records are provided as follows:

[0069] For example, if the risk factor of address 1 is phishing, and all transaction records between address 1 and the target blockchain address are transaction record 1, transaction record 2 and transaction record 3, and transaction record 1, transaction record 2 and transaction record 3 are all transfer transactions initiated by address 1 to the target blockchain address, the transaction currency is fake currency, and the transaction amount is very low. Based on this, the risk transmission relationship determination model can determine that the target blockchain address is the phishing attack object of address 1, and therefore there is no risk transmission relationship between address 1 and the target blockchain address.

[0070] For example, if the risk factor of address 2 is fraud, and all transaction records between address 1 and the target blockchain address are transaction record 4, transaction record 5 and transaction record 6, and transaction record 4, transaction record 5 and transaction record 6 are all transfer transactions initiated by the target blockchain address to address 2. Based on this, the risk transmission relationship determination model can determine that the target blockchain address is the fraud attack object of address 2, and therefore there is no risk transmission relationship between address 2 and the target blockchain address.

[0071] For example, if the risk factor of address 3 is money laundering, and all transaction records between address 3 and the target blockchain address are 100 transaction records, and the 100 transaction records include both transfer transactions initiated by the target blockchain address to address 3 and transfer transactions initiated by address 3 to the target blockchain address, and the transfer amount of the 100 transaction records is high. Based on this, the risk transmission relationship determination model can determine that there is a risk transmission relationship between address 3 and the target blockchain address.

[0072] More specifically, the risk transmission relationship determination model can determine, according to all transaction records between the risk address and the target blockchain address, a correlation score between the target blockchain address and a risk factor of the risk address, determine that there is a risk transmission relationship between the risk address and the target blockchain address if the correlation score is greater than a preset correlation score threshold, and determine that there is no risk transmission relationship between the risk address and the target blockchain address if the correlation score is less than the preset correlation score threshold. The specific value of the correlation score threshold and the specific method of determining the correlation score can be set according to actual needs, and are not limited here.

[0073] After the electronic device determines each risk address in the first-level associated address set and determines whether there is a risk transmission relationship between each associated address and the target blockchain address, the electronic device can determine a risk factor of the first-level associated address set according to risk factors of all risk addresses in the first-level associated address set that have a risk transmission relationship with the target blockchain address.

[0074] For example, if the risk addresses in the first-level associated address set that have a risk transmission relationship with the target blockchain address are address 2 and address 3, and the risk factor of address 2 is fraud and the risk factor of address 3 is money laundering, the electronic device can determine the risk factor of the first-level associated address set according to the risk factor of address 2 and the risk factor of address 3.

[0075] In one possible implementation, the electronic device can determine, as the risk factor of the first-level associated address set, the risk factor of the risk address that has the highest correlation score between the target blockchain address and the risk factor of the risk address. For example, if the risk addresses in the first-level associated address set that have a risk transmission relationship with the target blockchain address are address 2 and address 3, and the risk factor of address 2 is fraud and the risk factor of address 3 is money laundering, and the correlation score between the target blockchain address and the risk factor of address 2 is higher than the correlation score between the target blockchain address and the risk factor of address 3, the electronic device can determine the risk factor of address 2, fraud, as the risk factor of the first-level associated address set.

[0076] In another possible implementation, the electronic device can determine, as the risk factor of the first-level associated address set, the union of the risk factors of all risk addresses that have a risk transmission relationship with the target blockchain address. For example, if the risk addresses in the first-level associated address set that have a risk transmission relationship with the target blockchain address are address 2 and address 3, and the risk factor of address 2 is fraud and the risk factor of address 3 is money laundering, the electronic device can determine the risk factor of address 2, fraud, and the risk factor of address 3, money laundering, as the risk factor of the first-level associated address set.

[0077] The above gives a specific method for determining the risk factors of the first-level associated address set in the N associated address sets, and the following continues to give a specific method for determining the risk factors of the N-level associated address set in the N associated address sets.

[0078] The electronic device can obtain each risk address in the N-level associated address set for the N-level associated address set in the N associated address sets.

[0079] For example, if the electronic device obtains the first-level associated address set, the second-level associated address set, and the third-level associated address set in step 101, the electronic device can obtain each risk address in the second-level associated address set for the second-level associated address set, and can obtain each risk address in the third-level associated address set for the third-level associated address set.

[0080] After obtaining each risk address in the N-level associated address set, the electronic device can determine whether there is a risk transmission relationship between each risk address and the N-1-level associated address set in the N associated address sets according to all transaction records between the risk address and the N-1-level associated address set.

[0081] For example, each risk address in the second-level associated address set can be address 4 and address 5, based on which the electronic device can determine whether there is a risk transmission relationship between address 4 and the first-level associated address set according to all transaction records between address 4 and the first-level associated address set. In the example in S101, address 4 and address 1 in the first-level associated address set have transaction records, so the electronic device can determine whether there is a risk transmission relationship between address 4 and address 1 according to all transaction records between address 4 and address 1, and similarly, the electronic device can determine whether there is a risk transmission relationship between address 4 and address 1 according to all transaction records between address 5 and address 1.

[0082] Exemplarily, the risk addresses in the third-level associated address set can be address 10 and address 11, based on which, the electronic device can determine, for the address 10, whether there is a risk transmission relationship between the address 10 and the second-level associated address set according to all transaction records between the address 10 and the second-level associated address set. Wherein, since in the example of S101, the address 10 has a transaction record with the address 4 in the second-level associated address set, the electronic device can determine whether there is a risk transmission relationship between the address 10 and the address 4 according to all transaction records between the address 10 and the address 4, and similarly, the electronic device can determine whether there is a risk transmission relationship between the address 11 and the address 4 according to all transaction records between the address 11 and the address 4.

[0083] Wherein, the specific implementation manner of determining whether there is a risk transmission relationship between two addresses can refer to the related description provided in the foregoing by the embodiments of the present application, which will not be repeated here.

[0084] After determining whether there is a risk transmission relationship between each risk address in the Nth-level associated address set and the (N-1)th-level associated address set, the electronic device can determine the risk factor of the Nth-level associated address set according to the risk factors of all risk addresses in the risk address, which have a risk transmission relationship with the (N-1)th-level associated address set.

[0085] Exemplarily, if in the second-level associated address set, the address 4 has a risk transmission relationship with the first-level associated address set, and the address 5 does not have a risk transmission relationship with the first-level associated address set, the risk factor corresponding to the address 4 can be determined as the risk factor of the second-level associated address set.

[0086] Exemplarily, if in the third-level associated address set, the address 10 and the address 11 both have a risk transmission relationship with the second-level associated address set, the risk factor corresponding to the address 10 and the risk factor corresponding to the address 11 can be collectively determined as the risk factor of the third-level associated address set.

[0087] Based on this, the electronic device can determine the risk factors of the N associated address sets respectively.

[0088] In step b, the risk factor of the target blockchain address is determined according to the risk factors of the N associated address sets respectively.

[0089] In the embodiments of the present application, after determining the risk factors of the N associated address sets respectively, the electronic device can determine the risk factor of the target blockchain address according to the risk factors of the N associated address sets respectively.

[0090] Specifically, the electronic device can take the union of the risk factors of the N sets of associated addresses as the risk factors of the target blockchain address.

[0091] For example, if the risk factor of the first set of associated addresses is fraud, the risk factor of the second set of associated addresses is money laundering, and the risk factor of the third set of associated addresses is phishing, the risk factor of the target blockchain address can be determined to be fraud, money laundering, and phishing.

[0092] The following provides an example to illustrate the principle that the risk identification method of the blockchain address provided by the embodiments of the present application can quickly determine whether the target blockchain address is a successor address.

[0093] If the risk activity performer generates a successor address A and a transit address C after being sanctioned at the risk address B, and uses the transit address C as the transit address of the successor address A and the risk address B to achieve the purpose of the successor address A replacing the risk address B to conduct risk activities, then there must be transaction records between the successor address A and the transit address C, and there must be transaction records between the transit address C and the risk address B. Therefore, the successor address A can be taken as the target blockchain address, the transit address C can be the first set of associated addresses, and the risk address B can be the second set of associated addresses.

[0094] By executing each step of the risk identification method of the blockchain address provided by the embodiments of the present application with the electronic device taking the successor address A as the target blockchain address, the risk factors of the determined successor address A must include the risk factors corresponding to the risk address B. Therefore, the successor address A can be quickly determined to be the successor address of the risk address B, so that appropriate actions can be taken in time to control the successor address A, thereby improving the security of the blockchain.

[0095] It can be seen from the above that the risk identification method of the blockchain address provided by the embodiment of the application obtains a first-level associated address set composed of each first-level associated address having a direct transaction record with the target blockchain address, and an Nth-level associated address set composed of each Nth-level associated address having an indirect transaction record with the target blockchain address, and then determines the risk factors of the target blockchain address according to the risk information of the first-level associated address set to the Nth-level associated address set. Considering that there is a direct or indirect transaction record between the risk address and the corresponding successor address, the risk identification method provided by the embodiment of the application can determine the risk factors of the target blockchain address according to the risk information of each first-level associated address having a direct transaction record with the target blockchain address and the risk information of each Nth-level associated address having an indirect transaction record with the target blockchain address, so that whether the target blockchain address is a successor address can be quickly determined, and measures can be taken in time when the target blockchain address is a successor address, thereby improving the security of the blockchain.

[0096] Based on the risk identification method of the blockchain address provided in the above embodiment, the embodiment of the application further provides a risk identification device of a blockchain address for implementing the above method embodiment, please refer to Figure 2 , Figure 2 The structure diagram of a risk identification device of a blockchain address provided by the embodiment of the application. As shown in Figure 2 , the risk identification device of the blockchain address 20 can include an address set acquisition unit 21 and a risk identification unit 22. Wherein:

[0097] The address set acquisition unit 21 is configured to acquire N associated address sets of a target blockchain address; wherein the N associated address sets include a first-level associated address set to an Nth-level associated address set, the first-level associated address set includes at least one first-level associated address, the Nth-level associated address set includes at least one Nth-level associated address, the first-level associated address is a blockchain address having a transaction record with the target blockchain address, the Nth-level associated address is a blockchain address having a transaction record with the (N-1)th-level associated address, and N is an integer greater than or equal to 1.

[0098] The risk identification unit 22 is configured to determine the risk factors of the target blockchain address according to the risk information of the N associated address sets.

[0099] Optionally, the risk identification unit 22 is specifically configured to:

[0100] determine the risk factors of the N associated address sets respectively according to the risk addresses of the N associated address sets respectively;

[0101] determine the risk factors of the target blockchain address according to the risk factors of the N associated address sets respectively.

[0102] Optionally, the risk identification unit 22 is specifically configured to:

[0103] For a first-level associated address set in the N associated address sets, obtain each risk address of the first-level associated address set;

[0104] For each risk address in each risk address, determine whether there is a risk transmission relationship between the risk address and the target blockchain address according to all transaction records between the risk address and the target blockchain address;

[0105] According to the risk factors of all risk addresses in each risk address that have a risk transmission relationship with the target blockchain address, determine the risk factors of the first-level associated address set.

[0106] Optionally, the risk identification unit 22 is specifically configured to:

[0107] According to all transaction records, determine the association degree score between the target blockchain address and the risk factors of the risk address;

[0108] If the association degree score is greater than a preset association degree score threshold, it is determined that there is a risk transmission relationship between the risk address and the target blockchain address.

[0109] Optionally, the risk identification unit 22 is specifically configured to:

[0110] The union of the risk factors of all risk addresses that have a risk transmission relationship with the target blockchain address is taken as the risk factors of the first-level associated address set.

[0111] Optionally, the risk identification unit 22 is specifically configured to:

[0112] For an N-level associated address set in the N associated address sets, obtain each risk address of the N-level associated address set;

[0113] For each risk address in each risk address, determine whether there is a risk transmission relationship between the risk address and the N-1 level associated address set in the N associated address set according to all transaction records between the risk address and the N-1 level associated address set;

[0114] According to the risk factors of all risk addresses in each risk address that have a risk transmission relationship with the N-1 level associated address set, determine the risk factors of the N-level associated address set.

[0115] Optionally, the risk identification unit 22 is specifically configured to:

[0116] The union of the risk factors of the N associated address sets is used as the risk factor of the target blockchain address.

[0117] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 3 provided in this embodiment may include: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a program corresponding to the risk identification method for blockchain addresses. When the processor 30 executes the computer program 32, the steps in the embodiment of the risk identification method for blockchain addresses are implemented, such as Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of each module / unit in the embodiment of the risk identification device for blockchain addresses are realized, such as Figure 2 The functions of the units 21-22 are shown.

[0118] For example, the computer program 32 can be divided into one or more modules / units, one or more modules / units are stored in the memory 31 and executed by the processor 30 to complete the present application. One or more modules / units can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program 32 in the electronic device 3. For example, the computer program 32 can be divided into an address set acquisition unit and a risk identification unit. The specific functions of each unit can be found in Figure 2 The relevant descriptions in the corresponding embodiments are not repeated here.

[0119] Those skilled in the art will understand that Figure 3 This is merely an example of the electronic device 3 and does not constitute a limitation on the electronic device 3 . The electronic device 3 may include more or fewer components than shown in the figure, or may combine certain components, or may include different components.

[0120] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0121] The memory 31 can be an internal storage unit of the electronic device 3, such as a hard disk or a memory of the electronic device 3. The memory 31 can also be an external storage device of the electronic device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like equipped on the electronic device 3. Further, the memory 31 can also include both the internal storage unit and the external storage device of the electronic device 3. The memory 31 is used to store computer programs and other programs and data required by the electronic device. The memory 31 can also be used to temporarily store data that has been output or will be output.

[0122] It can be clearly understood by those skilled in the art that, for the convenience and brevity of description, only the division of the above functional units is taken as an example for illustration, and in actual application, the above functions can be completed by different functional units according to needs, that is, the internal structure of the blockchain address risk identification device is divided into different functional units to complete all or part of the functions described above. Each functional unit in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit, and the integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific name of each functional unit is only for convenient distinction, and does not limit the protection scope of the present application. The specific working process of the unit in the above system can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0123] The embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium stores a computer program, and the computer program is executed by a processor to realize the steps in each of the method embodiments.

[0124] The embodiment of the present application provides a computer program product, when the computer program product runs on an electronic device, the electronic device realizes the steps in each of the method embodiments.

[0125] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in detail in a certain embodiment can be referred to the related description of other embodiments.

[0126] Those skilled in the art can understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software manner depends on the specific application and design constraints of the technical solutions. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0127] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalent replacements; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for risk identification of a blockchain address, characterized in that, The method comprises: obtaining a set of N associated addresses of a target blockchain address; wherein the set of N associated addresses comprises a first-level associated address set and an N-level associated address set, the first-level associated address set comprises at least one first-level associated address, the N-level associated address set comprises at least one N-level associated address, the first-level associated address is a blockchain address having a transaction record with the target blockchain address, the N-level associated address is a blockchain address having a transaction record with an (N-1)-level associated address, and N is an integer greater than or equal to 1; determining a risk factor of the target blockchain address according to risk information of the set of N associated addresses; the risk information comprises a risk address; and the determination of the risk factor of the target blockchain address according to the risk information of the set of N associated addresses comprises: determining a risk factor of each of the set of N associated addresses according to the risk address of each of the set of N associated addresses; the determination of the risk factor of each of the set of N associated addresses according to the risk address of each of the set of N associated addresses comprises: for the first-level associated address set in the set of N associated addresses, obtaining each risk address of the first-level associated address set; for each risk address in each risk address, determining whether there is a risk transmission relationship between the risk address and the target blockchain address according to all transaction records between the risk address and the target blockchain address; determining a risk factor of the first-level associated address set according to risk factors of all risk addresses having a risk transmission relationship with the target blockchain address in each risk address.

2. The method of claim 1, wherein, the determination of the risk factor of the target blockchain address according to the risk information of the set of N associated addresses further comprises: determining the risk factor of the target blockchain address according to the risk factor of each of the set of N associated addresses.

3. The method of claim 1, wherein, the determination of whether there is a risk transmission relationship between the risk address and the target blockchain address according to all transaction records between the risk address and the target blockchain address comprises: determining an association score between a risk factor of the target blockchain address and the risk address according to the all transaction records; if the association score is greater than a preset association score threshold, it is determined that there is a risk transmission relationship between the risk address and the target blockchain address.

4. The method of claim 1, wherein, the determination of the risk factor of the first-level associated address set according to risk factors of all risk addresses having a risk transmission relationship with the target blockchain address in each risk address comprises: taking a union of the risk factors of all risk addresses having a risk transmission relationship with the target blockchain address as the risk factor of the first-level associated address set.

5. The method of claim 1, wherein, the determination of the risk factor of each of the set of N associated addresses according to the risk address of each of the set of N associated addresses comprises: For an Nth-level associated address set in the N associated address sets, each risk address of the Nth-level associated address set is obtained; For each risk address in each risk address, whether there is a risk transmission relationship between the risk address and the N-1th-level associated address set in the N associated address sets is determined according to all transaction records between the risk address and the N-1th-level associated address set; According to the risk factors of all risk addresses in each risk address that have a risk transmission relationship with the N-1th-level associated address set, the risk factor of the Nth-level associated address set is determined.

6. The method according to any one of claims 2 to 5, characterized in that, The risk factor of the target blockchain address is determined according to the risk factors of the N associated address sets, including: The union of the risk factors of the N associated address sets is taken as the risk factor of the target blockchain address. 7.A device for risk identification of a blockchain address, characterized in that, Including: An address set acquisition unit is configured to obtain N associated address sets of a target blockchain address; wherein the N associated address sets include a first-level associated address set to an Nth-level associated address set, the first-level associated address set includes at least one first-level associated address, the Nth-level associated address set includes at least one Nth-level associated address, the first-level associated address is a blockchain address having transaction records with the target blockchain address, the Nth-level associated address is a blockchain address having transaction records with an N-1th-level associated address, and N is an integer greater than or equal to 1; A risk identification unit is configured to determine a risk factor of the target blockchain address according to risk information of the N associated address sets; The risk information includes risk addresses; the risk identification unit is specifically configured to: Determine the risk factor of each of the N associated address sets according to the risk addresses of the N associated address sets, respectively; The risk identification unit is specifically configured to: For the first-level associated address set in the N associated address sets, each risk address of the first-level associated address set is obtained; For each risk address in each risk address, whether there is a risk transmission relationship between the risk address and the target blockchain address is determined according to all transaction records between the risk address and the target blockchain address; According to the risk factors of all risk addresses in each risk address that have a risk transmission relationship with the target blockchain address, the risk factor of the first-level associated address set is determined.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement each step in the risk identification method of the blockchain address according to any one of claims 1 to 6.

9. A computer program product, when the computer program product runs on a computer device, causes the computer device to execute the risk identification method of the blockchain address according to any one of claims 1 to 6.

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