CN107330311A - A kind of method and apparatus of man-machine identification - Google Patents
A kind of method and apparatus of man-machine identification Download PDFInfo
- Publication number
- CN107330311A CN107330311A CN201710517666.8A CN201710517666A CN107330311A CN 107330311 A CN107330311 A CN 107330311A CN 201710517666 A CN201710517666 A CN 201710517666A CN 107330311 A CN107330311 A CN 107330311A
- Authority
- CN
- China
- Prior art keywords
- client
- data
- people
- behavioral data
- machine
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/316—User authentication by observing the pattern of computer usage, e.g. typical user behaviour
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Social Psychology (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention discloses a kind of method and apparatus of man-machine identification, wherein this method includes：Obtain the behavioral data of client under operation；If the behavioural characteristic of behavioral data people corresponding with default Analysis model of network behaviors, it is determined that the operator of the client is people；If the behavioral data and the behavioral data of the people of default behavioral data judgment models are mismatched, it is determined that the operator of the client is machine.With this behavioral data by client operationally, namely the operation whether behavioural characteristic of spin data, stress data, the bearing data people corresponding with default Analysis model of network behaviors by client operationally are matched to be defined as client is people or machine, with this behavioural characteristic based on people's operation client to being that people or machine are identified, simple accurate quick is recognized.
Description
Technical field
The present invention relates to man-machine identification field, more particularly to a kind of method and apparatus of man-machine identification.
Background technology
With the high speed development of internet, the plug-in industry of game traditional in early days, namely utilize machine slotted eye current
Internet air control service security field is deep into, most of business software is for this based on the anti-of man-machine identification in the market
Man-machine technology, which is not widely used also, even to be not used to cause related service to occur in that some safety problems.
Existing man-machine identification method main restricted IP, device-fingerprint, browser fingerprint, identifying code, graphic verification, hand
The technologies such as machine short message.
But it is Internet resources limitation that limitation is carried out to client for IP, nowadays without great restriction effect,
It is still able to more easily bypass this limitation if attacker possesses substantial amounts of IP resource pools；As for being physics for device-fingerprint
Resource constraint, if malicious attacker possesses a large amount of physical resources and is still able to more easily bypass client limitation；For
The limitation of browser fingerprint then limits for request header, can generally change camouflage to bypass the limit to client
System.
Nowadays largely can quickly it be cracked as identification methods such as identifying code identification, graphic verifications；SMS is then
It is that process CIMS is cumbersome, cost is also higher.
Existing identification at present simple and effective can not all carry out man-machine identification, therefore need at present a kind of simple and effective
Man-machine recognition methods.
The content of the invention
For defect of the prior art, the present invention proposes a kind of method and apparatus of man-machine identification, to realize letter
Single effective man-machine identification.
Specifically, the embodiment of the present invention proposes embodiment in detail below：
The embodiment of the present invention proposes a kind of man-machine knowledge method for distinguishing, including：
Obtain the behavioral data of client under operation；Wherein, the behavioral data includes the rotation of the client
Revolution evidence, the stress data of the client, the bearing data of the client；
If the behavioural characteristic matching of behavioral data people corresponding with default Analysis model of network behaviors, it is determined that the visitor
The operator at family end is people；
If the behavioral data and the behavioral data of the people of default behavioral data judgment models are mismatched, it is determined that described
The operator of client is machine.
In a specific embodiment, this method also includes：
When it is determined that the operator of the client is machine, to the default defence flow of the client terminal start-up.
In a specific embodiment, this method also includes：
When it is determined that the operator of the client is people, the behavioral data and the generation of corresponding analysis result are marked
Notebook data is simultaneously stored in human behavior database.
In a specific embodiment, in addition to：The Analysis model of network behaviors is by mankind's analytical database
Middle quantity exceedes the sample data of predetermined threshold value to train what is obtained.
In a specific embodiment, the spin data is to monitor the obtain, stress data by gyroscope
It is to monitor the obtain, bearing data by the accelerometer to obtain by magnetometer location equipment monitoring.
The embodiment of the present invention also proposed a kind of equipment of man-machine identification, including：
Acquisition module, for obtaining the behavioral data of client under operation；Wherein, the behavioral data includes institute
State the spin data, the stress data of the client, the bearing data of the client of client；
Identification module, for the behavioural characteristic matching as behavioral data people corresponding with default Analysis model of network behaviors
When, the operator for determining the client is people；And when the behavioral data and the people of default behavioral data judgment models
Behavioral data mismatch when, the operator for determining the client is machine.
In a specific embodiment, the equipment also includes：
Defense module, it is default to the client terminal start-up for when it is determined that the operator of the client is machine
Defend flow.
In a specific embodiment, the equipment also includes：
Memory module, for when it is determined that the operator of the client is people, by the behavioral data and corresponding
Analysis result generates sample data and is stored in human behavior database.
In a specific embodiment,
The Analysis model of network behaviors is the sample data for exceeding predetermined threshold value by quantity in mankind's analytical database
To train what is obtained.
In a specific embodiment, the spin data is to monitor the obtain, stress data by gyroscope
It is to monitor the obtain, bearing data by the accelerometer to obtain by magnetometer location equipment monitoring.
With this, the embodiment of the invention discloses a kind of method and apparatus of man-machine identification, wherein this method includes：Obtain visitor
The behavioral data of family end under operation；Wherein, the behavioral data includes the spin data of the client, the client
The bearing data of the stress data at end, the client；If behavioral data people corresponding with default Analysis model of network behaviors
Behavioural characteristic, it is determined that the operator of the client is people；If the behavioral data judges mould with default behavioral data
The behavioral data of the people of type is mismatched, it is determined that the operator of the client is machine.With this by client operationally
Behavioral data, namely pass through client spin data operationally, stress data, bearing data and default behavioural analysis
The operation that whether behavioural characteristic of correspondence people is matched to be defined as client in model is people or machine, is operated with this based on people
The behavioural characteristic of client recognizes simple accurate quick to being that people or machine are identified.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be attached to what is used required in embodiment
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore is not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 is a kind of schematic flow sheet for man-machine knowledge method for distinguishing that the embodiment of the present invention is proposed；
Fig. 2 is a kind of schematic flow sheet for man-machine knowledge method for distinguishing that the embodiment of the present invention is proposed；
Fig. 3 is a kind of structural representation of the equipment for man-machine identification that the embodiment of the present invention is proposed；
Fig. 4 is a kind of structural representation of the equipment for man-machine identification that the embodiment of the present invention is proposed；
Fig. 5 is a kind of structural representation of the equipment for man-machine identification that the embodiment of the present invention is proposed.
Embodiment
Hereinafter, the various embodiments of the disclosure will be described more fully.The disclosure can have various embodiments, and
It can adjust and change wherein.It should be understood, however, that：It is limited to spy disclosed herein in the absence of by the various embodiments of the disclosure
Determine the intention of embodiment, but the disclosure should be interpreted as covering in the spirit and scope for the various embodiments for falling into the disclosure
All adjustment, equivalent and/or alternative.
Hereinafter, the term " comprising " that can be used in the various embodiments of the disclosure or " may include " indicate disclosed
Function, operation or the presence of element, and do not limit the increase of one or more functions, operation or element.In addition, such as existing
Used in the various embodiments of the disclosure, term " comprising ", " having " and its cognate are meant only to represent special characteristic, number
Word, step, operation, element, the combination of component or foregoing item, and be understood not to exclude first one or more other
Feature, numeral, step, operation, element, the presence of the combination of component or foregoing item or increase one or more features, numeral,
Step, operation, element, the possibility of the combination of component or foregoing item.
In the various embodiments of the disclosure, statement "or" or " in A or/and B at least one " include what is listed file names with
Any combinations of word or all combinations." A or B " or " in A or/and B at least one " may include A, may include for example, statement
B may include A and B both.
The statement (" first ", " second " etc.) used in the various embodiments of the disclosure can be modified to be implemented various
Various element in example, but corresponding element can not be limited.For example, presented above be not intended to limit the suitable of the element
Sequence and/or importance.The purpose presented above for being only used for differentiating an element and other elements.For example, the first user fills
Put and indicate different user device with second user device, although the two is all user's set.For example, not departing from each of the disclosure
In the case of the scope for planting embodiment, the first element is referred to alternatively as the second element, similarly, and the second element is also referred to as first
Element.
It should be noted that：, can be by the first composition member if an element ' attach ' to another element by description
Part is directly connected to the second element, and " connection " the 3rd can be constituted between the first element and the second element
Element.On the contrary, when an element " being directly connected to " is arrived into another element, it will be appreciated that be in the first element
And second the 3rd element is not present between element.
The term " user " used in the various embodiments of the disclosure, which may indicate that, to be used the people of electronic installation or uses electricity
The device (for example, artificial intelligence electronic installation) of sub-device.
The term used in the various embodiments of the disclosure is only used for describing the purpose of specific embodiment and not anticipated
In the various embodiments of the limitation disclosure.As used herein, singulative is intended to also include plural form, unless context is clear
Chu it is indicated otherwise.Unless otherwise defined, all terms (including the technical term and scientific terminology) tool being otherwise used herein
There is the implication identical implication that the various embodiment one skilled in the art with the disclosure are generally understood that.The term
(term such as limited in the dictionary typically used) is to be interpreted as having and the situational meaning in correlative technology field
Identical implication and it will be not construed as with Utopian implication or excessively formal implication, unless in the various of the disclosure
It is clearly defined in embodiment.
Embodiment 1
The embodiment of the present invention 1 discloses a kind of man-machine knowledge method for distinguishing, as shown in Figure 1 and Figure 2, including：
Step 101, the behavioral data of acquisition client under operation；
Wherein, the behavioral data includes the spin data, the stress data of the client, the visitor of the client
The bearing data at family end；
Specifically, in the embodiment of a reality, client is moveable client, namely mobile terminal, for example
Mobile phone, tablet personal computer etc., the spin data be by gyroscope monitor the obtain, stress data be by described plus
Speed meter monitoring the is obtained, bearing data is obtained by magnetometer location equipment monitoring.
And current mobile terminal, such as mobile phone, due to above-mentioned gyroscope, accelerometer, magnetometer location equipment etc. all
It is to be built in mobile phone, therefore behavioral data can be directly obtained, is specially obtained without extra increase equipment
Behavioral data is taken, use cost has been saved.
Specifically, behavioral data can be encrypted when being transmitted, with the further accuracy for improving identification, it is ensured that
Follow-up identification process is carried out based on accurately not tampered information；For example client get behavioral data it
Afterwards, it can be encrypted, and send the behavioral data after encryption to server, and server is receiving the behavioral data of encryption
Afterwards, first it is decrypted, then the behavioral data after decryption is handled.
Specifically, the execution equipment of step 101 can be server, in the case, client is monitoring itself
After behavioral data, server is reported, subsequent server can be handled behavioral data, specific process can be as
Under：
If the behavioural characteristic of step 102, the behavioral data people corresponding with default Analysis model of network behaviors, it is determined that institute
The operator for stating client is people；
Specifically, being illustrated still exemplified by above-mentioned, machine learning end, specific engineering can be passed through in server
Practise in end and include human behavior database, client is operated comprising someone in the human behavior database, such as user grasps
Make the behavioural characteristic of mobile phone, the amplitude for example moved holds the dynamics of mobile phone, mobile frequency etc., therefore can be effective
Behavioral data is identified, identifies it is that people or machine are being operated on earth.
Specifically, in the embodiment of a reality, this method also includes：
When it is determined that the operator of the client is people, the behavioral data and the generation of corresponding analysis result are marked
Notebook data is simultaneously stored in human behavior database.
In order to further improve accuracy, it is determined that operating handset be people after, analysis result by this identification (is
People is in operation) and the generation of corresponding behavioral data sample data and be stored in human behavior database, so as to follow-up
Played a role in identification process.、
If be that machine is operated as recognition result, then operations described below is carried out：
If step 103, the behavioral data and the behavioral data of the people of default behavioral data judgment models are mismatched,
The operator for determining the client is machine.
It is of course also possible to generate reverse data based on the behavioral data for being identified as machine, and it is stored in human behavior data
Exist in storehouse as the data of reverse side, positive and negative contrast can subsequently be carried out with this, improve the accuracy of identification.
In a specific embodiment, in addition to：
When it is determined that the operator of the client is machine, to the default defence flow of the client terminal start-up.
Specifically, when behavioral data and the behavioral data of the people of default behavioral data judgment models are mismatched, then may be used
To confirm being that machine is being operated, in the case, because machine operation is the operation with risk, in this case, it is possible to really
The operation for determining client is risky, it is therefore desirable to be on the defensive, and can start defence flow, for example, carry out again its other party
The certification of formula, or control described client shutdown etc..
In a specific embodiment, this method also includes：The Analysis model of network behaviors is by people's alanysis
Quantity exceedes the sample data of predetermined threshold value to train what is obtained in database.
Specifically, behavior analysis model is obtained by big data to train, the quantity of specific sample data is got over
It is many, train obtained Analysis model of network behaviors more accurate, sample data can constantly be got with this, and be constantly trained.
With this, the embodiment of the present invention 1, which discloses a kind of man-machine knowledge method for distinguishing, to be included：Obtain client under operation
Behavioral data；Wherein, the behavioral data includes the spin data, the stress data of the client, institute of the client
State the bearing data of client；If the behavioural characteristic of behavioral data people corresponding with default Analysis model of network behaviors, really
The operator of the fixed client is people；If the behavioral data and the behavioral data of the people of default behavioral data judgment models
Mismatch, it is determined that the operator of the client is machine.With this, during based under normal condition, people's operation client, for example
During mobile terminal, the change on position, pressure etc. can be produced, and if the operation that is carried out by machine to client, or
Do not have data in the data on position and pressure, or position and pressure and artificial data be it is completely different,
People is identified with machine from a brand-new angle with this, simply, fast, and accurately is difficult to be avoided.
Embodiment 2
In order to which the present invention is further detailed, the embodiment of the present invention 2 also discloses a kind of equipment of man-machine identification,
As shown in figure 3, including：
Acquisition module 201, for obtaining the behavioral data of client under operation；Wherein, the behavioral data bag
Include the spin data, the stress data of the client, the bearing data of the client of the client；
Identification module 202, for when the behavioural characteristic of behavioral data people corresponding with default Analysis model of network behaviors
When, the operator for determining the client is people；And when the behavioral data and the people of default behavioral data judgment models
Behavioral data mismatch when, the operator for determining the client is machine.
In a specific embodiment, as shown in figure 4, the equipment also includes：
Defense module 203, it is default to the client terminal start-up for when it is determined that the operator of the client is machine
Defence flow.
In a specific embodiment, as shown in figure 5, the equipment also includes：
Memory module 204, for when it is determined that the operator of the client is people, by the behavioral data and correspondingly
Analysis result generation sample data and be stored in human behavior database.
In a specific embodiment,
The Analysis model of network behaviors is the sample data for exceeding predetermined threshold value by quantity in mankind's analytical database
To train what is obtained.
In a specific embodiment, the spin data is to monitor the obtain, stress data by gyroscope
It is to monitor the obtain, bearing data by the accelerometer to obtain by magnetometer location equipment monitoring.
Each module above can carry out flexibly arranging in pairs or groups with combining as needed, however it is not limited to several in Figure of description
Individual specific embodiment.
With this, the embodiment of the invention discloses a kind of method and apparatus of man-machine identification, wherein this method includes：Obtain visitor
The behavioral data of family end under operation；Wherein, the behavioral data includes the spin data of the client, the client
The bearing data of the stress data at end, the client；If behavioral data people corresponding with default Analysis model of network behaviors
Behavioural characteristic, it is determined that the operator of the client is people；If the behavioral data judges mould with default behavioral data
The behavioral data of the people of type is mismatched, it is determined that the operator of the client is machine.With this by client operationally
Behavioral data, namely pass through client spin data operationally, stress data, bearing data and default behavioural analysis
The operation that whether behavioural characteristic of correspondence people is matched to be defined as client in model is people or machine, is operated with this based on people
The behavioural characteristic of client recognizes simple accurate quick to being that people or machine are identified.
It will be appreciated by those skilled in the art that accompanying drawing is a schematic diagram for being preferable to carry out scene, module in accompanying drawing or
Flow is not necessarily implemented necessary to the present invention.
It will be appreciated by those skilled in the art that the module in device in implement scene can be described according to implement scene into
Row is distributed in the device of implement scene, can also carry out one or more dresses that respective change is disposed other than this implement scene
In putting.The module of above-mentioned implement scene can be merged into a module, can also be further split into multiple submodule.
The invention described above sequence number is for illustration only, and the quality of implement scene is not represented.
Disclosed above is only several specific implementation scenes of the present invention, and still, the present invention is not limited to this, Ren Heben
What the technical staff in field can think change should all fall into protection scope of the present invention.
Claims (10)
1. a kind of man-machine knowledge method for distinguishing, it is characterised in that including：
Obtain the behavioral data of client under operation；Wherein, the behavioral data includes the rotation number of the client
According to, the bearing data of the stress data of the client, the client；
If the behavioural characteristic matching of behavioral data people corresponding with default Analysis model of network behaviors, it is determined that the client
Operator be people；
If the behavioral data and the behavioral data of the people of default behavioral data judgment models are mismatched, it is determined that the client
The operator at end is machine.
2. the method as described in claim 1, it is characterised in that also include：
When it is determined that the operator of the client is machine, to the default defence flow of the client terminal start-up.
3. the method as described in claim 1, it is characterised in that also include：
When it is determined that the operator of the client is people, the behavioral data and corresponding analysis result are generated into number of samples
According to and be stored in human behavior database.
4. the method as described in claim 1 or 3, it is characterised in that also include：The Analysis model of network behaviors is by the people
Quantity exceedes the sample data of predetermined threshold value to train what is obtained in alanysis database.
5. the method as described in claim 1, it is characterised in that the spin data is to monitor obtain, institute by gyroscope
State stress data be by the accelerometer monitor obtain, the bearing data be by the magnetometer location equipment monitor
Obtain.
6. a kind of equipment of man-machine identification, it is characterised in that including：
Acquisition module, for obtaining the behavioral data of client under operation；Wherein, the behavioral data includes the visitor
The spin data at family end, the stress data of the client, the bearing data of the client；
Identification module, for when behavioral data people corresponding with default Analysis model of network behaviors behavioural characteristic matching when,
The operator for determining the client is people；And when the behavioral data and the row of the people of default behavioral data judgment models
When being mismatched for data, the operator for determining the client is machine.
7. equipment as claimed in claim 6, it is characterised in that also include：
Defense module, for when it is determined that the operator of the client is machine, to the default defence of the client terminal start-up
Flow.
8. equipment as claimed in claim 6, it is characterised in that also include：
Memory module, for when it is determined that the operator of the client is people, by the behavioral data and corresponding analysis
As a result sample data are generated and are stored in human behavior database.
9. the equipment as described in claim 6 or 8, it is characterised in that
The Analysis model of network behaviors is to exceed the sample data of predetermined threshold value to instruct by quantity in mankind's analytical database
Get.
10. equipment as claimed in claim 6, it is characterised in that the spin data is to monitor obtain, institute by gyroscope
State stress data be by the accelerometer monitor obtain, the bearing data be by the magnetometer location equipment monitor
Obtain.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710517666.8A CN107330311A (en) | 2017-06-29 | 2017-06-29 | A kind of method and apparatus of man-machine identification |
| PCT/CN2018/093553 WO2019001558A1 (en) | 2017-06-29 | 2018-06-29 | Human and machine recognition method and device |
| PCT/CN2018/093618 WO2019001566A1 (en) | 2017-06-29 | 2018-06-29 | Authentication method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710517666.8A CN107330311A (en) | 2017-06-29 | 2017-06-29 | A kind of method and apparatus of man-machine identification |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107330311A true CN107330311A (en) | 2017-11-07 |
Family
ID=60199267
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710517666.8A Pending CN107330311A (en) | 2017-06-29 | 2017-06-29 | A kind of method and apparatus of man-machine identification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107330311A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107979596A (en) * | 2017-11-24 | 2018-05-01 | 武汉斗鱼网络科技有限公司 | It is a kind of it is live in prevent the method and system of brush popularity behavior |
| CN108022101A (en) * | 2017-11-29 | 2018-05-11 | 上海壹账通金融科技有限公司 | Man-machine input operation recognition methods, device, equipment and readable storage medium storing program for executing |
| CN108495272A (en) * | 2018-03-19 | 2018-09-04 | 上海哔哩哔哩科技有限公司 | Robot recognition methods, system and storage medium based on HTML5 browsers |
| WO2019001566A1 (en) * | 2017-06-29 | 2019-01-03 | 苏州锦佰安信息技术有限公司 | Authentication method and device |
| CN109145544A (en) * | 2018-09-05 | 2019-01-04 | 郑州云海信息技术有限公司 | A kind of human-computer behavior detection system and method |
| CN109635533A (en) * | 2018-12-07 | 2019-04-16 | 中国移动通信集团江苏有限公司 | Personal identification method, device, equipment and medium |
| CN109688183A (en) * | 2018-08-20 | 2019-04-26 | 深圳壹账通智能科技有限公司 | Group control device recognition methods, device, equipment and computer readable storage medium |
| CN110059794A (en) * | 2018-01-18 | 2019-07-26 | 北京京东金融科技控股有限公司 | Man-machine recognition methods and device, electronic equipment, storage medium |
| CN112351006A (en) * | 2020-10-27 | 2021-02-09 | 杭州安恒信息技术股份有限公司 | Website access attack interception method and related components |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530543A (en) * | 2013-10-30 | 2014-01-22 | 无锡赛思汇智科技有限公司 | Behavior characteristic based user recognition method and system |
| CN103678417A (en) * | 2012-09-25 | 2014-03-26 | 华为技术有限公司 | Man-machine interaction data processing method and device |
| CN106155298A (en) * | 2015-04-21 | 2016-11-23 | 阿里巴巴集团控股有限公司 | Man-machine recognition methods and device, the acquisition method of behavior characteristics data and device |
| CN106487747A (en) * | 2015-08-26 | 2017-03-08 | 阿里巴巴集团控股有限公司 | User identification method, system, device and processing method, device |
-
2017
- 2017-06-29 CN CN201710517666.8A patent/CN107330311A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103678417A (en) * | 2012-09-25 | 2014-03-26 | 华为技术有限公司 | Man-machine interaction data processing method and device |
| CN103530543A (en) * | 2013-10-30 | 2014-01-22 | 无锡赛思汇智科技有限公司 | Behavior characteristic based user recognition method and system |
| CN106155298A (en) * | 2015-04-21 | 2016-11-23 | 阿里巴巴集团控股有限公司 | Man-machine recognition methods and device, the acquisition method of behavior characteristics data and device |
| CN106487747A (en) * | 2015-08-26 | 2017-03-08 | 阿里巴巴集团控股有限公司 | User identification method, system, device and processing method, device |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019001566A1 (en) * | 2017-06-29 | 2019-01-03 | 苏州锦佰安信息技术有限公司 | Authentication method and device |
| WO2019001558A1 (en) * | 2017-06-29 | 2019-01-03 | 苏州锦佰安信息技术有限公司 | Human and machine recognition method and device |
| CN107979596A (en) * | 2017-11-24 | 2018-05-01 | 武汉斗鱼网络科技有限公司 | It is a kind of it is live in prevent the method and system of brush popularity behavior |
| CN107979596B (en) * | 2017-11-24 | 2020-10-16 | 武汉斗鱼网络科技有限公司 | Method and system for preventing people from being refreshed in live broadcast |
| CN108022101A (en) * | 2017-11-29 | 2018-05-11 | 上海壹账通金融科技有限公司 | Man-machine input operation recognition methods, device, equipment and readable storage medium storing program for executing |
| CN110059794A (en) * | 2018-01-18 | 2019-07-26 | 北京京东金融科技控股有限公司 | Man-machine recognition methods and device, electronic equipment, storage medium |
| CN108495272A (en) * | 2018-03-19 | 2018-09-04 | 上海哔哩哔哩科技有限公司 | Robot recognition methods, system and storage medium based on HTML5 browsers |
| CN109688183A (en) * | 2018-08-20 | 2019-04-26 | 深圳壹账通智能科技有限公司 | Group control device recognition methods, device, equipment and computer readable storage medium |
| CN109688183B (en) * | 2018-08-20 | 2022-08-19 | 深圳壹账通智能科技有限公司 | Group control equipment identification method, device, equipment and computer readable storage medium |
| CN109145544A (en) * | 2018-09-05 | 2019-01-04 | 郑州云海信息技术有限公司 | A kind of human-computer behavior detection system and method |
| CN109635533A (en) * | 2018-12-07 | 2019-04-16 | 中国移动通信集团江苏有限公司 | Personal identification method, device, equipment and medium |
| CN112351006A (en) * | 2020-10-27 | 2021-02-09 | 杭州安恒信息技术股份有限公司 | Website access attack interception method and related components |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107330311A (en) | A kind of method and apparatus of man-machine identification | |
| JP6527590B2 (en) | System and method for detecting covert channel network intrusion based on offline network traffic | |
| CN109766700A (en) | Access control method and device, the storage medium, electronic device of file | |
| CN111866024B (en) | Network encryption traffic identification method and device | |
| CN106961419A (en) | WebShell detection methods, apparatus and system | |
| US10546130B1 (en) | Timed attestation process | |
| CN104506484A (en) | Proprietary protocol analysis and identification method | |
| CN103634317A (en) | Method and system of performing safety appraisal on malicious web site information on basis of cloud safety | |
| CN104123501B (en) | A kind of viral online test method based on many assessor set | |
| CN110661680A (en) | Method and system for detecting data stream white list based on regular expression | |
| CN104899499A (en) | Internet image search based Web verification code generation method | |
| CN103763104B (en) | A kind of method and system of dynamic authentication | |
| Rodofile et al. | Process control cyber-attacks and labelled datasets on S7Comm critical infrastructure | |
| CN110493142B (en) | Mobile application program behavior identification method based on spectral clustering and random forest algorithm | |
| CN115827610A (en) | Method and device for detecting effective load | |
| CN107294981B (en) | Authentication method and equipment | |
| CN109697163A (en) | Program testing method and equipment | |
| Garcia | Firmware modification analysis in programmable logic controllers | |
| CN115659346A (en) | Function testing method and device for multi-party secure computing platform | |
| US11537739B2 (en) | System and method for analyzing confidential data | |
| Su et al. | AndroGenerator: An automated and configurable android app network traffic generation system | |
| CN113886140A (en) | Artificial intelligence model output data judgment system based on credibility verification | |
| TWI667587B (en) | Information security protection method | |
| CN106650349B (en) | A kind of pair of identity card uses the safe method being monitored | |
| CN111625861A (en) | Block chain identification encryption system and method based on mobile internet platform |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20171107 |