CN105653536B - Data processing method and device - Google Patents
Data processing method and device Download PDFInfo
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- CN105653536B CN105653536B CN201410640616.5A CN201410640616A CN105653536B CN 105653536 B CN105653536 B CN 105653536B CN 201410640616 A CN201410640616 A CN 201410640616A CN 105653536 B CN105653536 B CN 105653536B
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Abstract
This application involves a kind of data processing method and device, this method includes：Set the acquisition methods and comparative approach of different type characterization factor；The first transaction record is extracted, the fisrt feature factor of each type of first transaction record is obtained according to the acquisition methods；The second transaction record is extracted, the second feature factor of each type of second transaction record is obtained according to the acquisition methods；Compare the fisrt feature factor and the second feature factor of same type according to the comparative approach, if the second feature factor of same type is identical with the fisrt feature factor, preserves second transaction record.Data processing method provided by the present application and device reduce the cost of artificial case analysis by the way of automation, improve the efficiency of case analysis, meanwhile, it can quickly increase the dimension of merit analysis, be conducive to quickly cope with new case characteristic.
Description
Technical field
This application involves data processing method more particularly to a kind of numbers using historical data analysis current data legitimacy
According to processing method and processing device.
Background technology
With the rapid development of network technology, computer network becomes the indispensable composition portion of people's daily life
Point, it changes the traditional living habit and work rhythm of people.But with the opening of the network information and shared demand day
Benefit enhancing, thing followed safety problem are also original more prominent.With the continuous expansion of network size, network security accident number
Amount, and caused by lose also in growth at double.Hacker, network crime etc. are that information security brings very big threat.Therefore, such as
What analyzes case, finds out the same or analogous potential case of feature according to the historical data that case has occurred, and avoids same
The network security accident of class occurs again, is inherently eliminated security risk, becomes the important means for ensureing network security.
In the prior art, right by acquiring the case information currently reported a case to the security authorities by the way of manually analyzing case
The fix information (IP address and MAC Address) of case is analyzed, and in history case database, is manually inquired, is found out
The matched case of characteristic information, that is, be confirmed as potential case.For example, an appropriator uses an IP address, usurp multiple
Account can inquire whole user behavior datas according to IP address or MAC Address, if inquired when usurping
Between section have identical IP address and MAC Address, then corresponding user is confirmed as stolen account.
The anti-factor of looking into of case in the prior art is fixed, and IP address and MAC Address are pertained only to, and increasing a business feature newly needs
System is wanted to make larger transformation, therefore, being easy omission case characteristic can not carry out if appropriator identifies the two factors
Related potential the counter of case is looked into.Moreover, relying on artificial manual queries, working efficiency is relatively low, cannot achieve large batch of data
Processing.
Invention content
The purpose of the application is to provide a kind of data processing method and device, is easy to ignore case to solve counter look into of artificial case
Part characteristic and ineffective problem.
In a first aspect, a kind of data processing method is provided, the method includes：
Set the acquisition methods and comparative approach of different type characterization factor；
The first transaction record is extracted, the first of each type of first transaction record is obtained according to the acquisition methods
Characterization factor；
The second transaction record is extracted, the second of each type of second transaction record is obtained according to the acquisition methods
Characterization factor；
The fisrt feature factor and the second feature factor for comparing same type according to the comparative approach, if same type
The second feature factor it is identical with the fisrt feature factor, then preserve second transaction record.
Second aspect, provides a kind of data processing equipment, and described device includes：
Setting unit, acquisition methods and comparative approach for setting different type characterization factor；
First extraction unit obtains first transaction according to the acquisition methods and remembers for extracting the first transaction record
The fisrt feature factor of each type of record；
Second extraction unit obtains second transaction according to the acquisition methods and remembers for extracting the second transaction record
The second feature factor of each type of record；
Comparing unit, the fisrt feature factor and second feature for comparing same type according to the comparative approach because
Son preserves second transaction record if the second feature factor of same type is identical with the fisrt feature factor.
Data processing method provided by the present application and device, by the acquisition methods and ratio that set different type characterization factor
Compared with method, the characterization factor of illegal transaction and whole historical operating datas is extracted, is compared according to the comparative approach mutually similar
Two kinds of characterization factors of type preserve the user behavior number of the historical operation if two kinds of characterization factors of same type are identical
According to.Data processing method provided by the present application realizes case analysis automation, reduces the cost of artificial case analysis, improves
The efficiency of case analysis, meanwhile, it can quickly increase the dimension of merit analysis, be conducive to quickly to cope with new case characteristic.
Description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the application
Example, for those of ordinary skill in the art, without creative efforts, can also obtain according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the data processing method flow chart that the embodiment of the present application one provides；
Fig. 2 is that the case characterization factor that the embodiment of the present application one provides safeguards schematic diagram；
Fig. 3 is the data processing equipment schematic diagram that the embodiment of the present application two provides.
Specific implementation mode
To keep the purpose, technical scheme and advantage of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, technical solutions in the embodiments of the present application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
The every other embodiment obtained without making creative work, shall fall in the protection scope of this application.
Data processing method provided by the embodiments of the present application and device are grasped suitable for user using e-commerce website
The scene of work is particularly suitable for the scene that user is traded operation by payment system, wherein payment system includes server
And client, or including server and browser.Wherein, browser or client are used to interact with user, including
It obtains information input by user and shows result information to user；Server is used to handle information input by user, and
Obtain result information.Server includes database, and the user for the operations such as logged in or merchandised is stored in the database
Operation data.
Fig. 1 is the data processing method flow chart that the embodiment of the present application one provides.The executive agent of the method can be
Equipment with processing capacity：Server either system or device, as shown in Figure 1, the method specifically includes：
S101 sets the acquisition methods and comparative approach of different type characterization factor.
For the ease of being safeguarded to case characterization factor, is setting the acquisition methods of different type characterization factor and comparing
It, can be according to the understanding and requirement of case analysis personnel to the illegal transaction occurred and whole historical operation numbers before method
According to classifying, for example, environmental classes, fund class etc..
For different classification, corresponding characterization factor acquisition methods and comparative approach are set.Characterization factor acquisition methods
Specially calculation, characterization factor is different, then acquisition methods are different, as shown in Figure 2.
Characterization factor includes one or more of：
The address information (IP address, MAC Address etc.) of trade user, the account information (bank's card number etc.) of trade user,
The operation data of trade user, the information etc. for identifying equipment speciality.For example, choosing IP address as characterization factor, then setting should
The acquisition methods of characterization factor are：userAction.ip.
The illegal comparative approach for merchandising IP address and the IP address of whole historical operating datas, which is arranged, is：
StolenUserAction.ip==userAction.ip.
It should be noted that historical operation includes：Register and transactional operation etc..When the operation of user is register
When, then the operation data of user may include：The log-on messages such as user name, the ID card No. of user.And when the operation of user
For transactional operation when, then the operation data of user includes：1) information of user, e.g., the registered place of user, the age of user and
The length of surfing the Net etc. of user；2) behavioural information of user, e.g., (e.g., user A may be before Taobao finally places an order the searching times of user
N to N+n times search can be undergone, is linked up with M to M+m Taobao seller Wang Wang), (e.g., user A is in evening for the time buying section of user
Upper 8：00-10：Pay the bill between 00), (e.g., the amount of money of the clothes class of user's purchase is in 80-200 members for the purchase amount of money of user
Between)；3) user transactional operation scene (e.g., go back credit card, also water rate, also the electricity charge, also gas charge, hospital's reservation, look for vehicle etc.)；
4) the access equipment information (e.g., the information of the MAC Address of access equipment or other energy unique mark access equipments) of user.
S102 extracts the first transaction record, each type of first transaction record is obtained according to the acquisition methods
The fisrt feature factor.
First transaction record is known illegal transaction record, and case analysis personnel with stolen person's phone by consulting
The mode of inquiry extracts illegal transaction record by risk recognition system.
According to the characterization factor acquisition methods set, obtain the characterization factor of the illegal transaction of each type, i.e.,
The fisrt feature factor of each type of one transaction record.
The fisrt feature factor includes one or more of：
The address information (IP address, MAC Address etc.) of trade user, the account information (bank's card number etc.) of trade user,
The operation data of trade user, the information etc. for identifying equipment speciality.
S103 extracts the second transaction record, each type of second transaction record is obtained according to the acquisition methods
The second feature factor.
Second transaction record is whole historical operating datas of our station user, according to case analysis personnel to all going through
The classification of history operation data, according to the characterization factor acquisition methods set obtain the feature of sorted historical operating data because
Son, i.e. the second feature factor.
According to the characterization factor acquisition methods set, the characterization factor of the historical operating data of each type is obtained, i.e.,
The second feature factor of each type of second transaction record.
The second feature factor includes one or more of：
The address information (IP address, MAC Address etc.) of trade user, the account information (bank's card number etc.) of trade user,
The operation data of trade user, the information etc. for identifying equipment speciality.
S104 compares the fisrt feature factor and the second feature factor of same type according to the comparative approach, if phase
The second feature factor of same type is identical with the fisrt feature factor, then preserves second transaction record.
Case analysis personnel set the counter of illegal transaction and look into the time, according to setting according to illegal transaction time of origin
Good comparative approach, the characterization factor of more same type of illegal transaction record and historical operating data, limit are all gone through
History operation data is compared, if the feature of the characterization factor and historical operating data of the illegal transaction record of same type
The factor is identical, then preserves the user behavior data in historical operating data.For example, an appropriator has used an IP address,
Usurped multiple accounts, then can have been inquired in whole historical transaction records using this IP address, if inquire with
The relevant account of IP address then can be confirmed that these accounts are stolen account, preserve the user behavior data of these accounts.
For example, the selected characteristic factor is IP address, using the characterization factor acquisition methods and comparative approach of step S101, such as
True when fruit result exports, then return to userAction.
Data processing method provided by the present application, by the acquisition methods and the comparison side that set different type characterization factor
Method extracts the characterization factor of illegal transaction and whole historical operating datas, compares same type according to the comparative approach
Two kinds of characterization factors preserve the user behavior data of the historical operation if two kinds of characterization factors of same type are identical.This
The data processing method that application provides realizes case analysis automation, reduces the cost of artificial case analysis, raising is concluded a case
The efficiency of part analysis, meanwhile, it can quickly increase the dimension of merit analysis, be conducive to quickly cope with new case characteristic.
Accordingly with above-mentioned data processing method, a kind of data processing equipment that the embodiment of the present application also provides, Fig. 3 are this
Apply for that the schematic device that embodiment two provides, the device include：Setting unit 201, the extraction of the first extraction unit 202, second
Unit 203, comparing unit 204.
The setting unit 201, acquisition methods and comparative approach for setting different type characterization factor；
The setting unit 201 includes：
First setting unit 2011, for according to different types of first transaction record and the second transaction record, setting pair
Answer different types of characterization factor acquisition methods.
Ratio is arranged for the fisrt feature factor and the second feature factor for same type in second setting unit 2012
Compared with method.
First extraction unit 202 obtains described first for extracting the first transaction record according to the acquisition methods
The fisrt feature factor of each type of transaction record；
Second extraction unit 203 obtains described second for extracting the second transaction record according to the acquisition methods
The second feature factor of each type of transaction record；
The comparing unit 204, the fisrt feature factor and second for comparing same type according to the comparative approach
Characterization factor preserves second transaction record if the second feature factor of same type is identical with the fisrt feature factor.
Optionally, described device further includes：
First taxon 205 obtains different types of first transaction for carrying out classification processing to the first transaction record
Record；
Second taxon 206 obtains different types of second transaction for carrying out classification processing to the second transaction record
Record.
The method that the device that the embodiment of the present application two provides implants the offer of the embodiment of the present application one, therefore, the application carries
The specific work process of the device of confession, does not repeat again herein.
Data processing equipment provided by the present application, by the acquisition methods and the comparison side that set different type characterization factor
Method extracts the characterization factor of illegal transaction and whole historical operating datas, compares same type according to the comparative approach
Two kinds of characterization factors preserve the user behavior data of the historical operation if two kinds of characterization factors of same type are identical.This
The data processing method that application provides realizes case analysis automation, reduces the cost of artificial case analysis, raising is concluded a case
The efficiency of part analysis, meanwhile, it can quickly increase the dimension of merit analysis, be conducive to quickly cope with new case characteristic.
Professional should further appreciate that, described in conjunction with the examples disclosed in the embodiments of the present disclosure
Object and algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, hard in order to clearly demonstrate
The interchangeability of part and software generally describes each exemplary composition and step according to function in the above description.
These functions are implemented in hardware or software actually, depend on the specific application and design constraint of technical solution.
Professional technician can use different methods to achieve the described function each specific application, but this realization
It is not considered that exceeding scope of the present application.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can use hardware, processor to execute
The combination of software module or the two is implemented.Software module can be placed in random access memory (RAM), memory, read-only memory
(ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technical field
In any other form of storage medium well known to interior.
Above-described specific implementation mode has carried out further the purpose, technical solution and advantageous effect of the application
It is described in detail, it should be understood that the foregoing is merely the specific implementation mode of the application, is not used to limit the application
Protection domain, within the spirit and principles of this application, any modification, equivalent substitution, improvement and etc. done should all include
Within the protection domain of the application.
Claims (10)
1. a kind of data processing method, which is characterized in that this method includes：
Set the acquisition methods and comparative approach of different type characterization factor in transaction record；
The first transaction record is extracted, the fisrt feature of each type of first transaction record is obtained according to the acquisition methods
The factor, first transaction record are illegal transaction record；
The second transaction record is extracted, the second feature of each type of second transaction record is obtained according to the acquisition methods
The factor, second transaction record are historical operating data；
Compare the fisrt feature factor and the second feature factor of same type according to the comparative approach, if the of same type
Two characterization factors are identical with the fisrt feature factor, then preserve second transaction record.
2. according to the method described in claim 1, it is characterized in that, described set different type characterization factor in transaction record
Before acquisition methods and comparative approach, further include：
Classification processing is carried out to the first transaction record, obtains different types of first transaction record；
Classification processing is carried out to the second transaction record, obtains different types of second transaction record.
3. method according to claim 1 or 2, which is characterized in that in the setting transaction record different type feature because
The acquisition methods and comparative approach of son, specially：
According to different types of first transaction record and the second transaction record, the corresponding different types of characterization factor acquisition side of setting
Method.
4. according to the method described in claim 1, it is characterized in that, described set different type characterization factor in transaction record
Acquisition methods and comparative approach, including：
For the fisrt feature factor and the second feature factor of same type, comparative approach is set.
5. according to the method described in claim 1, it is characterized in that, the fisrt feature factor and the second feature factor include with
Under it is one or more：
The letter of the address information of trade user, the account information of trade user, the operation data of trade user, mark equipment speciality
Breath.
6. a kind of data processing equipment, which is characterized in that described device includes：
Setting unit, acquisition methods and comparative approach for setting different type characterization factor in transaction record；
First extraction unit obtains first transaction record for extracting the first transaction record according to the acquisition methods
The fisrt feature factor of each type, first transaction record are illegal transaction record；
Second extraction unit obtains second transaction record for extracting the second transaction record according to the acquisition methods
The second feature factor of each type, second transaction record are historical operating data；
Comparing unit, the fisrt feature factor for comparing same type according to the comparative approach and the second feature factor, such as
The second feature factor of fruit same type is identical with the fisrt feature factor, then preserves second transaction record.
7. device according to claim 6, which is characterized in that described device further includes：
First taxon obtains different types of first transaction record for carrying out classification processing to the first transaction record；
Second taxon obtains different types of second transaction record for carrying out classification processing to the second transaction record.
8. the device described according to claim 6 or 7, which is characterized in that the setting unit includes：
First setting unit, for according to different types of first transaction record and the second transaction record, setting corresponding inhomogeneity
The characterization factor acquisition methods of type.
9. device according to claim 6, which is characterized in that the setting unit includes：
Comparative approach is arranged for the fisrt feature factor and the second feature factor for same type in second setting unit.
10. device according to claim 6, which is characterized in that the fisrt feature factor and the second feature factor include
One or more of：
The letter of the address information of trade user, the account information of trade user, the operation data of trade user, mark equipment speciality
Breath.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201410640616.5A CN105653536B (en) | 2014-11-13 | 2014-11-13 | Data processing method and device |
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| CN201410640616.5A CN105653536B (en) | 2014-11-13 | 2014-11-13 | Data processing method and device |
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| CN105653536A CN105653536A (en) | 2016-06-08 |
| CN105653536B true CN105653536B (en) | 2018-10-23 |
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| CN110188127A (en) * | 2019-05-27 | 2019-08-30 | 成都信息工程大学 | A kind of car networking network security emergency response system and method based on cbr |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101253507A (en) * | 2005-08-29 | 2008-08-27 | 大金工业株式会社 | Account false use detecting/suppressing device, data collecting device, and account false use detecting/suppressing program |
| CN101751629A (en) * | 2008-12-16 | 2010-06-23 | 国际商业机器公司 | Method and system for authenticating multifactor with changing unique values |
| CN103049851A (en) * | 2012-12-27 | 2013-04-17 | 中国建设银行股份有限公司 | Transaction data-based anti-fraud monitoring method and device |
| CN103123712A (en) * | 2011-11-17 | 2013-05-29 | 阿里巴巴集团控股有限公司 | Method and system for monitoring network behavior data |
| CN103532797A (en) * | 2013-11-06 | 2014-01-22 | 网之易信息技术（北京）有限公司 | Abnormity monitoring method and device for user registration |
-
2014
- 2014-11-13 CN CN201410640616.5A patent/CN105653536B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101253507A (en) * | 2005-08-29 | 2008-08-27 | 大金工业株式会社 | Account false use detecting/suppressing device, data collecting device, and account false use detecting/suppressing program |
| CN101751629A (en) * | 2008-12-16 | 2010-06-23 | 国际商业机器公司 | Method and system for authenticating multifactor with changing unique values |
| CN103123712A (en) * | 2011-11-17 | 2013-05-29 | 阿里巴巴集团控股有限公司 | Method and system for monitoring network behavior data |
| CN103049851A (en) * | 2012-12-27 | 2013-04-17 | 中国建设银行股份有限公司 | Transaction data-based anti-fraud monitoring method and device |
| CN103532797A (en) * | 2013-11-06 | 2014-01-22 | 网之易信息技术（北京）有限公司 | Abnormity monitoring method and device for user registration |
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Effective date of registration: 20200925 Address after: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman Islands Patentee after: Innovative advanced technology Co.,Ltd. Address before: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman Islands Patentee before: Advanced innovation technology Co.,Ltd. Effective date of registration: 20200925 Address after: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman Islands Patentee after: Advanced innovation technology Co.,Ltd. Address before: A four-storey 847 mailbox in Grand Cayman Capital Building, British Cayman Islands Patentee before: Alibaba Group Holding Ltd. |