CN110532958B - FingerPrint identification method for equipment based on FingerPrint browser information acquisition - Google Patents
FingerPrint identification method for equipment based on FingerPrint browser information acquisition Download PDFInfo
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- CN110532958B CN110532958B CN201910816543.3A CN201910816543A CN110532958B CN 110532958 B CN110532958 B CN 110532958B CN 201910816543 A CN201910816543 A CN 201910816543A CN 110532958 B CN110532958 B CN 110532958B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/13—Sensors therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1347—Preprocessing; Feature extraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
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Abstract
The invention relates to a device FingerPrint identification method based on FingerPrint browser information acquisition, which comprises the steps of acquiring device information through FingerPrint JS2, transmitting the device information to a server for performing first-class rejection feature matching, performing second-class feature matching if the first-class rejection feature matching result is matching, performing variable feature matching if the second-class feature matching result is that the score is higher than a second-class feature threshold, and transmitting the result to the next link if the variable feature matching result is that the difference accords with the variable feature threshold range. Compared with the prior art, the method has the advantages of high equipment fingerprint identification accuracy, realization of cross-browser equipment fingerprint identification, realization of intercommunication between HTML 5-based equipment fingerprint identification and SDK-based equipment fingerprint identification and the like.
Description
Technical Field
The invention relates to the technical field of equipment FingerPrint identification, in particular to an equipment FingerPrint identification method based on FingerPrint browser information acquisition.
Background
FingerPrint is the most popular browser device fingerprinting open source framework on the market today. The method is realized based on a pure JS script, can embed an application program without traces, obtains passively collected browser information and hardware information which can be collected by a browser, and finally gives a Hash value as a unique identifier through the collected information.
However, in the existing market, a terminal device can be installed with multiple browsers, so that FingerPrint hash values of different browsers of the same device are different, and even different versions of the same browser have different FingerPrint hash values. Meanwhile, the device fingerprint identification method based on the SDK and the device fingerprint identification method based on the HTML5 cannot identify the device of the other party. This is contrary to the goal of device fingerprinting, which in turn leads to an extended bias for subsequent analytical computing services.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a FingerPrint identification method of equipment based on FingerPrint browser information acquisition.
The purpose of the invention can be realized by the following technical scheme:
a FingerPrint identification method of equipment based on information acquisition of a Fingerprint browser comprises the steps of acquiring equipment information through Fingerprint JS2, transmitting the equipment information to a server to carry out first-order rejection feature matching, carrying out second-order feature matching if the first-order rejection feature matching result is matching, carrying out variable feature matching if the second-order feature matching result is that the score is higher than a second-order feature threshold value, identifying the result as matching if the variable feature matching result is that the difference value accords with the range of the variable feature threshold value, and transmitting the result to the next link.
Further, the identification method also comprises the step of carrying out equipment library warehousing recording when a negative vote feature matching result is not matched, and transmitting the unmatched world result to the next link.
Further, the identification method further comprises the step of performing equipment library warehousing recording when the secondary feature matching result is that the score is lower than the secondary feature threshold value, and transmitting the unmatched world result to the next link.
Further, the identification method further comprises the step of performing equipment library warehousing record when the variable feature matching result is that the difference value exceeds the variable feature threshold range, and transmitting the unmatched world result to the next link.
Further, the one-ticket veto feature comprises screen resolution, model, operating system, GPU graphic processor, touch screen coefficient and WebGL drawing protocol.
Further, the secondary features comprise browser core version, audio frequency, memory information, core number, platform, language, fonts font, time zone, storage space support, plugins plug-ins and canvas.
Further, the secondary feature matching specifically includes: if each feature is successfully matched, the score of the secondary features is increased by 10 points, the matching is circulated until all the features are matched and total scores are obtained, the total scores are multiplied by 10 and divided by the total feature number to obtain scores, and the scores are higher or lower than the two-feature threshold value.
Further, the two-feature threshold is at least 70.
Further, the variable characteristics comprise Gps positioning information, gravity sensing information and network types.
Further, the variable characteristic threshold range includes a variable characteristic threshold range for Gps positioning information and a variable characteristic threshold range for gravity sensing information, the variable characteristic threshold range for Gps positioning information is that a Gps positioning information corresponding amount is greater than 200, and the variable characteristic threshold range for gravity sensing information is that a gravity sensing information corresponding amount is greater than 20.
Compared with the prior art, the invention has the following advantages:
(1) The method collects the equipment information through the finger print JS2 and then transmits the equipment information to the server for carrying out the first-order rejection feature matching, if the first-order rejection feature matching result is matching, the second-order feature matching is carried out, if the second-order feature matching result is that the score is higher than the second-order feature threshold value, the variable feature matching is carried out, and if the variable feature matching result is that the difference value accords with the variable feature threshold value range, the identification is successful and the equipment information is returned, thereby improving the accuracy of the equipment fingerprint identification.
(2) In the method, the intercommunication between the equipment fingerprint identification based on the HTML5 and the equipment fingerprint identification based on the SDK can be realized by performing multi-stage exhaustive matching listing on the first-class rejection characteristic, the second-class characteristic and the variable characteristic.
(3) In the method, the fingerprintJS2 architecture is adopted and optimized to obtain a new identification method, so that the equipment fingerprint identification of the cross-browser can be realized.
Drawings
FIG. 1 is a schematic overall flow diagram of the present invention;
fig. 2 is a schematic view of a specific process design according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
Examples
As shown in fig. 1, the invention is a flow diagram of a finger print recognition method of a device based on FingerPrint browser information acquisition, and the invention acquires more device objective information (such as network type, GPS, etc.) based on FingerPrint acquired data, and abandons the Hash algorithm carried by the FingerPrint, and calculates the identifier by adopting another set of autonomous algorithm.
The method comprises the following steps:
1. partially rewriting the finger print frame and collecting more objective information of the equipment
a) The method comprises the following steps "one-vote veto" feature: screen resolution, model, operating System, gpu, touch Screen coefficient, webgl
b) The method comprises the following steps Secondary characteristics: browser kernel version, audio frequency, memory size, kernel number, platform, language, fonts, time zone, storage support, plugins, canvas
c) The method comprises the following steps Variable characteristics: gps, gravity sensing, network type
2. Storing the matched effective data according to identification degree classification
a) The method comprises the following steps The "one-vote-overrule" feature is first matched. If no matching record exists in the warehouse, the device is a new device, and warehousing records are carried out;
b) The method comprises the following steps If there is a matching record in the library, then the secondary features are matched. And scoring the equipment, and taking the equipment with the score lower than the secondary characteristic threshold value as new equipment for warehousing.
c) The method comprises the following steps And if the score is higher than the secondary feature threshold value, performing variable feature matching. If the variable characteristic difference value exceeds the variable characteristic threshold range, the device is regarded as a new device; and if the variable characteristic difference value accords with the variable characteristic threshold range, the variable characteristic difference value is regarded as the same equipment, and equipment information is returned.
Fig. 2 is a schematic diagram of a specific process design in this embodiment, the secondary feature matching specifically includes: and if each feature is successfully matched, increasing the secondary feature score by 10 points, circularly matching until all features are matched, obtaining a total score, multiplying the total score by 10, and dividing the total score by the total feature number to obtain a score, wherein the score is higher or lower than a secondary feature threshold value, and the secondary feature threshold value is 70.
The variable characteristic threshold range comprises a variable characteristic threshold range for the Gps positioning information and a variable characteristic threshold range for the gravity sensing information, the variable characteristic threshold range for the Gps positioning information is a Gps positioning information corresponding quantity, i.e., a distance/time difference is greater than 200, and the variable characteristic threshold range for the gravity sensing information is a gravity sensing information corresponding quantity, i.e., a value difference/time difference is greater than 20.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A FingerPrint identification method of equipment based on FingerPrint browser information acquisition is characterized in that the identification method comprises the steps of acquiring equipment information through FingerPrint JS2 and then transmitting the equipment information to a server for performing a negative characteristic matching, performing a secondary characteristic matching if the negative characteristic matching result is matching, performing variable characteristic matching if the secondary characteristic matching result is that the score is higher than a secondary characteristic threshold value, and determining that the identification result is matching if the variable characteristic matching result is that the difference value meets the variable characteristic threshold value range and transmitting the result to the next link;
the ticket rejection characteristics comprise screen resolution, model, operating system, GPU (graphic processing unit) graphics processor, touch screen coefficient and WebGL drawing protocol;
the secondary characteristics comprise browser core version, audio frequency, memory information, core number, platform, language, fonts font, time zone, storage space support, plugins plug-in and canvas;
the variable characteristics comprise Gps positioning information, gravity sensing information and network types.
2. The device FingerPrint identification method based on FingerPrint browser information collection as claimed in claim 1, wherein the identification method further comprises performing device library warehousing recording when a matching result of a negative characteristic is not matched, and transmitting the unmatched identification result to the next link.
3. The device FingerPrint identification method based on FingerPrint browser information collection as claimed in claim 1, wherein the identification method further comprises performing device library warehousing recording when the secondary feature matching result is that the score is lower than the secondary feature threshold, and transmitting the unmatched identification result to the next link.
4. The device FingerPrint identification method based on FingerPrint browser information collection as claimed in claim 1, wherein the identification method further comprises performing device library warehousing recording when the variable feature matching result is that the difference exceeds the variable feature threshold range, and transmitting the unmatched identification result to the next link.
5. The device FingerPrint identification method based on FingerPrint browser information acquisition as claimed in claim 1, wherein said secondary feature matching specifically comprises: and if each feature is successfully matched, increasing the secondary feature score by 10 points, circularly matching until all features are matched, obtaining a total score, multiplying the total score by 10, and dividing the total score by the total feature number to obtain a score, wherein the score is higher or lower than the secondary feature threshold value.
6. A fingerprinting browser information collection-based device FingerPrint identification method as claimed in claim 5, wherein said two-feature threshold is at least 70.
7. The fingerprintingbased equipment FingerPrint identification method for FingerPrint browser information acquisition as claimed in claim 1, wherein the variable characteristic threshold range comprises a variable characteristic threshold range for Gps positioning information and a variable characteristic threshold range for gravity sensing information, the variable characteristic threshold range for Gps positioning information is that Gps positioning information corresponding quantity is greater than 200, and the variable characteristic threshold range for gravity sensing information is that gravity sensing information corresponding quantity is greater than 20.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017020447A1 (en) * | 2015-07-31 | 2017-02-09 | 宇龙计算机通信科技(深圳)有限公司 | Fingerprint recognition method and device |
| CN106951765A (en) * | 2017-03-31 | 2017-07-14 | 福建北卡科技有限公司 | A kind of zero authority mobile device recognition methods based on browser fingerprint similarity |
| CN107066974A (en) * | 2017-04-17 | 2017-08-18 | 东南大学 | The terminal device recognition methods that a kind of anti-browser fingerprint changes |
| CN107748878A (en) * | 2017-11-13 | 2018-03-02 | 苏州大成电子科技有限公司 | A kind of fingerprint identification method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10630793B2 (en) * | 2017-10-19 | 2020-04-21 | Reflektion, Inc. | Browser fingerprinting |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017020447A1 (en) * | 2015-07-31 | 2017-02-09 | 宇龙计算机通信科技(深圳)有限公司 | Fingerprint recognition method and device |
| CN106951765A (en) * | 2017-03-31 | 2017-07-14 | 福建北卡科技有限公司 | A kind of zero authority mobile device recognition methods based on browser fingerprint similarity |
| CN107066974A (en) * | 2017-04-17 | 2017-08-18 | 东南大学 | The terminal device recognition methods that a kind of anti-browser fingerprint changes |
| CN107748878A (en) * | 2017-11-13 | 2018-03-02 | 苏州大成电子科技有限公司 | A kind of fingerprint identification method |
Non-Patent Citations (2)
| Title |
|---|
| 一种面向渐变浏览器指纹的识别方法;张雨清等;《计算机工程与应用》;20170426(第07期);全文 * |
| 浏览器指纹技术的研究与应用;杨立鹏等;《计算机技术与发展》;20171115(第03期);全文 * |
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