CN108712253B - Counterfeit mobile terminal identification method and device based on fingerprint of mobile phone sensor - Google Patents
Counterfeit mobile terminal identification method and device based on fingerprint of mobile phone sensor Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords
- H04L9/0866—Generation of secret information including derivation or calculation of cryptographic keys or passwords involving user or device identifiers, e.g. serial number, physical or biometrical information, DNA, hand-signature or measurable physical characteristics
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0876—Network architectures or network communication protocols for network security for authentication of entities based on the identity of the terminal or configuration, e.g. MAC address, hardware or software configuration or device fingerprint
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2250/00—Details of telephonic subscriber devices
- H04M2250/12—Details of telephonic subscriber devices including a sensor for measuring a physical value, e.g. temperature or motion
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- H04W12/12—Detection or prevention of fraud
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Abstract
The invention provides a method and a device for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor, which comprises the following steps: the method comprises the steps of automatically generating a sensor fingerprint based on the device attributes of a sensor (including but not limited to an acceleration sensor, a gyroscope, a magnetic field sensor and the like) carried by the mobile phone and the signal characteristics generated by the sensor, and judging whether an application program access device is a personal computer terminal or a mobile terminal according to the sensor fingerprint. The method and the device provided by the invention can accurately judge the computer program disguised as the mobile terminal, ensure the legal benefits of an application program owner in the operation and popularization processes, and protect the assets of the application program owner from being stolen by illegal means such as wool production and the like to cause loss.
Description
Technical Field
The invention relates to the technical field of computers, the field of mobile phone equipment and sensors, and the field of data analysis. The method and the device are used for identifying the counterfeit mobile terminal on the PC by using the core characteristics of the mobile phone sensor by means of the equipment fingerprint technology.
Background
In the APP promotion activities and operation processes, mobile phone Application (APP) developers often run mobile phone APPs on mobile terminal equipment counterfeited by computer programs in black productions, and steal most of benefits originally issued to final customers in the promotion marketing activities by batch operation of script programs. For example: in the shared bicycle industry, a wool party runs a mobile phone APP on a Personal Computer (PC) terminal by using software such as an android simulator and a mobile phone information modifier, and then rides an ofo minibus and gets a red envelope distributed by the minibus without going home.
This unfair competitive behavior seriously impairs the interests of APP developers and other normal consumers, and destroys the fair network environment, violating the relevant laws of the state. Therefore, how to identify which application access devices are mobile phones and which access devices are fake mobile terminals is a technical problem that those skilled in the art need to solve.
Currently, International Mobile Equipment Identity (IMEI) is used to identify each independent Mobile phone in GSM Mobile networks, and can be used together with information such as a Mobile phone MAC address and an operating system as a method for identifying a counterfeit Mobile terminal. However, the information can be easily simulated by some mobile phone information modifier software, so that the mobile terminal of the mobile phone running on the PC has a high possibility of escaping from the detection of the real mobile phone. The method for identifying the counterfeit mobile terminal by the fixed equipment information is low in accuracy and poor in effect, and cannot solve the identification problem of the counterfeit mobile terminal.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: in order to overcome the identification problem caused by mobile phone information modifier software, the method and the device for identifying the counterfeit mobile terminal based on the fingerprint of the mobile phone sensor are provided, and the problem that a computer program cannot be accurately identified to be disguised as a mobile phone terminal in the prior art is solved.
In order to solve the above technical problems, an embodiment of the present invention provides a method and an apparatus for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor, including: the method comprises the steps of obtaining sensor equipment attributes of APP operation equipment and characteristic signals generated by a sensor, generating a sensor fingerprint according to the equipment attributes and the characteristic signals, and judging whether the application program operation equipment is a fake mobile phone terminal or not according to the sensor fingerprint.
The specific implementation mode of the invention also provides a counterfeit mobile terminal identification device based on the fingerprint of the mobile phone sensor, which comprises the following components: the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring the attribute of sensor equipment of APP running equipment and a characteristic signal generated by a sensor; the identification unit is used for automatically generating a sensor fingerprint according to the equipment attribute and the characteristic signal; and the judging unit is used for judging whether the APP operation equipment is a forged mobile terminal or not according to the sensor fingerprint.
A counterfeit mobile terminal identification method based on mobile phone sensor fingerprints is characterized by comprising the following steps:
(1) acquiring sensor equipment attribute information of APP operation equipment and a characteristic signal generated by a sensor; the equipment attributes of the sensors are the types and names of various sensors, the characteristic signals generated by the sensors are all output values of various sensors in continuous seconds, the acceleration sensors output multiple groups of acceleration values of three axes x, y and z, the gyroscope sensors output multiple groups of angular acceleration values of three axes x, y and z, and the temperature sensors and the pressure sensors output multiple groups of temperature values and multiple groups of pressure values respectively;
(2) generating a sensor fingerprint according to the sensor equipment attribute and the characteristic signal;
(3) and judging whether the type of the APP operation equipment is a mobile phone terminal forged by a Personal Computer (PC) or not according to the sensor fingerprint.
The method further comprises the following steps:
according to the obtained multiple groups of output values of the various sensors, a finite sequence is obtained through fast Fourier transform, a low-frequency sequence item is filtered through high-pass filtering, and then the standard deviation of the high-frequency sequence item is calculated to serve as the sensitivity index of the various sensors of the APP operation equipment; according to the obtained multiple groups of output values of the various sensors, the variance of the multiple groups of output values is counted to serve as a statistical index of the deviation of the various sensors of the APP operation equipment in the use process; generating fingerprint information of the sensors by utilizing various sensors and two indexes corresponding to the sensors, wherein the fingerprint format is sensor type 1, corresponding sensitivity index 1 and corresponding offset statistical index 1; the method comprises the following steps of sensor type 2, corresponding sensitivity index 2, corresponding deviation statistical index 2, and the like, until all types of sensors which can be obtained in the mobile phone are listed. Then, the sensor sensitivity index and the offset statistical index are processed through a Hash algorithm to obtain an MD5 value of the sensor, and the MD5 value is used as a final fingerprint of each type of sensor. The final fingerprint format is therefore sensor type 1, MD5 value 1, sensor type 2, MD5 value 2, and so on, until all types of sensors available in the handset are listed.
The method further comprises the following steps:
and comparing the generated various sensor fingerprints with various sensor fingerprints of the mobile phone forged on the PC, and if the MD5 values corresponding to the various sensors are all equal, determining that the equipment is a forged mobile terminal.
The various sensors include, but are not limited to, acceleration sensors, gyroscope sensors, magnetic field sensors, pressure sensors, temperature sensors, distance sensors, and orientation sensors.
The invention relates to a counterfeit mobile terminal identification device based on a mobile phone sensor fingerprint, which comprises:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring the equipment attribute of a sensor of APP operation equipment and the characteristic signal generated by the sensor, the equipment attribute of the sensor is the type and name of the sensor, and the characteristic signal generated by the sensor is all output values of various sensors in continuous seconds;
the identification unit is used for automatically generating a sensor fingerprint according to the equipment attribute and the characteristic signal;
and the judging unit is used for judging whether the APP operation equipment is a forged mobile terminal on the Personal Computer (PC) or not according to the sensor fingerprint.
The identification unit specifically includes:
the sensitivity calculation module is used for calculating the sensitivity indexes of various sensors, obtaining a finite sequence through fast Fourier transform according to the obtained multiple groups of output values of the various sensors, and calculating the standard deviation of high-frequency sequence items after high-pass filtering to serve as the sensitivity indexes of the various sensors;
the offset calculation module is used for calculating offset statistical indexes in the use process of various sensors, and calculating the variance of the output values as the offset indexes according to the obtained multiple groups of output values of various sensors;
the fingerprint generation module generates fingerprint information of the sensors according to various sensors and two corresponding indexes thereof, wherein the fingerprint format is sensor type 1, corresponding sensitivity index 1 and corresponding offset statistical index 1; the method comprises the following steps of sensor type 2, corresponding sensitivity index 2, corresponding deviation statistical index 2, and the like, until all types of sensors which can be obtained in the mobile phone are listed. Then, the sensor type and the corresponding sensitivity index and the offset statistical index are processed through a Hash algorithm to obtain an MD5 value of the sensor, the MD5 value is used as a final fingerprint of various sensors, the final fingerprint format is sensor type 1, MD5 value 1, sensor type 2 and MD5 value 2, and so on until all types of sensors which can be obtained in the mobile phone are listed.
Compared with the prior art, the invention has the advantages that: according to the above embodiments of the present invention, the method and the apparatus for identifying a counterfeit mobile terminal have at least the following advantageous effects: firstly, various sensor indexes are calculated by utilizing the sensor equipment attribute of APP operation equipment and characteristic signals generated by a sensor, then, the fingerprint of the sensor is generated by the calculation result through a Hash algorithm, and the generated fingerprint is compared with the forged fingerprint of the mobile phone sensor on the PC, and finally, the identification of the mobile terminal operated on the PC is realized. The invention only adopts the data of the sensor without the attributes of other devices and systems to generate the fingerprint, so the invention has the advantages of less characteristics required by fingerprint generation and small data acquisition amount; meanwhile, the invention combines the fixed equipment attribute of the sensor and the changed characteristic signal as the characteristic basis of fingerprint generation, can avoid using mobile phone information modification software to avoid the occurrence of detection situation, has the advantage of high detection precision, can ensure the legal interests of APP developers, the affiliated mechanisms and normal consumers, maintains fair network environment, and inhibits network fraud and network black product flooding.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flowchart of an embodiment 1 of a method for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor according to an embodiment of the present invention;
fig. 2 is a flowchart of an embodiment 2 of a method for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor according to an embodiment of the present invention;
fig. 3 is a flowchart of an embodiment 3 of a method for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor according to an embodiment of the present invention;
fig. 4 is a schematic block diagram of an embodiment 1 of an apparatus for recognizing a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor according to an embodiment of the present invention;
fig. 5 is a block diagram schematically illustrating a structure of an identification unit in example 1 of an apparatus for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor according to an embodiment of the present invention.
Detailed Description
For the purpose of promoting a clear understanding of the objects, aspects and features of embodiments of the invention, reference will now be made to the drawings and detailed description, wherein the same are to be understood as being modified and obvious in view of the teachings of the present disclosure, and all changes and modifications that may be made thereto by those skilled in the art are intended to be included within the spirit and scope of the present disclosure.
The exemplary embodiments and descriptions of the present invention are provided to explain the present invention by way of a part of the embodiments and not by way of a whole application and not by way of limitation. In addition, the same or similar numbered elements/components used in the embodiments and the drawings are used to represent the same or similar parts.
As used herein, the terms "comprising," "including," "having," "containing," and the like are open-ended terms that mean including, but not limited to.
As used herein, directions are used, for example: front, back, left, right, up or down, etc., are simply directions with reference to the drawings. Accordingly, the directions used are for the sake of better explanation and are not intended to limit the invention.
As used herein, "and/or" includes any and all combinations of the described items.
Fig. 1 is a flowchart of an embodiment 1 of a method for identifying an counterfeit mobile terminal based on a mobile phone sensor fingerprint according to an embodiment of the present invention, and as shown in fig. 1, whether an access device is a mobile phone terminal operating on a PC is determined according to a sensor fingerprint generated by attributes and signal characteristics of a sensor device of an APP operating device.
In the specific embodiment shown in the figure, the identification method includes:
step 101: and acquiring the equipment attribute and the characteristic signal of various sensors of the APP operation equipment. In an embodiment of the present invention, the sensor may be a light (light) sensor, an acceleration (accelerometer) sensor, a gyroscope (gyro) sensor, a magnetic field (magnetic field) sensor, a gravity (gravity) sensor, a pressure (pressure) sensor, a temperature (temperature) sensor, a distance (proximity) sensor, a direction (orientation) sensor, and the like.
Step 102: and automatically generating a sensor fingerprint according to the attribute and the characteristic signal of the sensor equipment. In the specific embodiment of the invention, the sensor fingerprint belongs to the category of the device fingerprint, and inherits the characteristics of the device fingerprint, such as stability, difficult tampering, uniqueness and the like. But with the difference that the sensor fingerprint is not used as a unique identifier to distinguish between different device features, but rather as an identifier to distinguish between sensor features in different brands and models of handsets. For example, two mobile devices of the same brand, model and International Mobile Equipment Identity (IMEI) have different device fingerprints, but the same sensor fingerprint. The device fingerprint generally uses attributes such as IMEI, International Mobile Subscriber Identity (IMSI), MAC address, IP, screen resolution, geographic location information, and operating system information to identify device features. However, the mobile phone end running on the PC can simulate the features through a mobile phone information modifier, a location disguise device, and the like, thereby achieving the purpose of network fraud. Sensor data in a real mobile phone, such as temperature, pressure, acceleration and the like, are constantly changed originally, and the data are modified into fixed values by using modification software without any significance, so that the mobile terminal identification characteristic of the mobile phone forged on a PC (personal computer) by using the sensor data is more reliable than that of a traditional method depending on mobile phone equipment information and system information.
Step 103: and judging the type of the access equipment according to the generated sensor fingerprint.
Referring to fig. 1, the present invention uses various sensor data that frequently changes in the mobile phone to generate sensor fingerprints, rather than device fingerprints generated using generally fixed device information, and can effectively avoid the problem that the mobile phone running on the PC cannot be identified by means of modifying or forging mobile phone information, and inhibit the flooding of network fraud and network blackness, thereby protecting the legitimate interests of APP developers, their affiliated institutions, and normal consumers, and maintaining a fair network environment.
Fig. 2 is a flowchart of an embodiment 2 of a method for identifying a counterfeit mobile terminal based on a sensor fingerprint of a mobile phone according to an embodiment of the present invention, and as shown in fig. 2, various sensor indexes in mobile phone equipment are calculated first, and then the sensor fingerprint is generated by the indexes through a hash algorithm.
In the specific embodiment shown in the figure, step 102 specifically includes:
step 1021: and calculating various sensor indexes of the APP operation equipment. In the embodiment of the invention, the sensor indexes comprise sensitivity indexes and offset statistical indexes in the use process, and because the number and the types of the built-in sensors of different models are different, the two calculated indexes are respectively used for the data of various sensors in the mobile phone. For example, in a mobile phone with model a, the built-in sensors are three types of sensors in total, such as a light sensor, a distance sensor, an acceleration sensor, and the like, and the indexes to be calculated are sensitivity indexes of the three types of sensors, and offset statistical indexes of the three types of sensors in the use process, the sensitivity indexes of the sensors are obtained by calculating the standard deviation of the high-frequency sequence item from the characteristic signals in step 101 through fast fourier transform to obtain a finite sequence, filtering the low-frequency sequence item through high-pass filtering, and calculating the standard deviation of the high-frequency sequence item; the offset statistics for each type of sensor are derived from calculating the variance of the signature values as described in step 101.
Step 1022: and generating the sensor fingerprint by the two indexes through a Hash algorithm. In a specific embodiment of the present invention, according to the sensitivity index and the offset statistical index of each sensor described in step 1021, the sensor fingerprint format is sensor type 1, corresponding sensitivity index 1, and corresponding offset statistical index 1; the method comprises the following steps of sensor type 2, corresponding sensitivity index 2, corresponding deviation statistical index 2, and the like, until all types of sensors which can be obtained in the mobile phone are listed. Then, the sensor type, the sensitivity index corresponding to the sensor type and the statistical index of the offset are processed through a Hash algorithm to obtain an MD5 value of the sensor, and the MD5 value is used as a final fingerprint of each type of sensor. The final fingerprint format is therefore sensor type 1, MD5 value 1, sensor type 2, MD5 value 2, and so on, until all types of sensors available in the handset are listed.
Referring to fig. 2, sensor fingerprints are generated by calculating sensitivity indexes of various sensors and offset statistical indexes in the use process and then performing a hash algorithm on the indexes. The sensor fingerprint can be used as an identifier for identifying a counterfeit mobile terminal.
Fig. 3 is a flowchart of a third embodiment of a method for identifying a counterfeit mobile terminal based on a mobile phone sensor fingerprint according to the embodiment of the present invention, and as shown in fig. 3, generated fingerprints of various types of mobile phones are directly compared with fingerprints of various types of mobile phones counterfeit on a PC, so as to determine whether an APP running device is a real mobile phone terminal or a counterfeit mobile terminal on the PC. For example: the APP running device has three types of sensors in total, such as a gyroscope, an acceleration sensor, and a magnetic field sensor, and the fingerprints generated by the method in step 102 are a gyroscope MD5 value 1, an acceleration sensor MD5 value 2, and a magnetic field sensor MD5 value 3. And (3) matching the three MD5 values with a sensor fingerprint of a type corresponding to a counterfeit mobile terminal on a PC (personal computer) generated in advance, such as: the gyroscope MD5 value 4, the acceleration sensor MD5 value 5, and the magnetic field sensor MD5 value 6 are compared. And if the corresponding MD5 values of the three types of sensors are all equal, determining that the APP operation equipment is a fake mobile terminal of the mobile phone.
In the embodiment shown in the figure, step 103 specifically includes:
step 1031: in a specific embodiment of the present invention, the sensor fingerprint is not used to determine different types of cell phones, but rather to determine counterfeit mobile terminals on a PC, and is therefore directly compared to a pre-generated counterfeit cell phone sensor fingerprint. The following differences between a counterfeit cell phone sensor on a PC and a sensor in a real cell phone are present: firstly, a counterfeit mobile phone sensor on a PC cannot sense the change of the external environment, such as temperature, illumination, acceleration and the like, because the counterfeit mobile phone sensor is not a real component; secondly, although the fake sensor data on the PC can be modified by some software such as a sensor simulator, the modified data is often a fixed value and is difficult to change continuously, and the data of the sensor is often in continuous change due to the characteristic of mobile portability of a real mobile phone in the using process, so that the data of the sensor and the data of the real mobile phone show a significant difference in the variance of the collected data; finally, even if the real mobile phone is in a stationary state, the sensor data still changes due to the noise of the sensor itself and the slight vibration of the surrounding environment, and the counterfeit mobile phone sensor data on the PC can maintain a long-term stable state. For the above reasons, a counterfeit mobile phone on the PC will have the same fingerprint identifying such sensor features.
Step 1032: and if the sensor fingerprint is matched with the counterfeit mobile phone sensor fingerprint on the PC, judging that the APP operation equipment is a counterfeit mobile terminal on the PC. In the embodiment of the invention, the forged mobile phone sensor fingerprints on the PC are obtained by running programs simulating a mobile phone end on the PC, such as a hippocampal game, a night god, a national assistant and the like, then collecting various sensor data on the simulators, and then using the method represented by the step 102. As long as the MD5 values corresponding to various sensors are equal, the fingerprints are consistent, and the sensors of the APP operation equipment conform to the characteristics of the sensors of the mobile phones forged on the PC, so that the APP operation equipment can be judged to be the mobile phones forged on the PC rather than the real mobile phones.
Referring to fig. 3, by comparing the sensor fingerprint with the counterfeit mobile phone sensor fingerprint on the PC, the occurrence of using modifier software to escape detection conditions can be effectively avoided, and the flooding of network fraud and network black production can be suppressed, so that the legal interests of APP developers, organizations to which the APP developers belong and normal consumers can be protected, and a fair network environment can be maintained.
Fig. 4 is a schematic block diagram of an embodiment 1 of an apparatus for recognizing a counterfeit mobile terminal based on a mobile phone sensor fingerprint according to a specific embodiment of the present invention, and the apparatus shown in fig. 4 may be applied to the methods shown in fig. 1 to fig. 3, and generates a sensor fingerprint according to the obtained attributes and characteristic signals of the sensor device, so as to determine whether the APP running device is a counterfeit mobile terminal on a PC.
In the specific embodiment shown in the figure, the identification device of the forged mobile terminal includes an obtaining unit 1, an identifying unit 2 and a judging unit 3, where the obtaining unit 1 is configured to obtain device attributes and characteristic signals of various sensors of the APP running device; the identification unit 2 is used for generating a sensor fingerprint according to the equipment attribute and the characteristic signal; and the judging unit 3 is used for judging whether the APP operation equipment is a forged mobile terminal on the PC or not according to the sensor fingerprint.
Referring to fig. 4, the invention uses various sensor data that changes frequently in the mobile phone to generate the sensor fingerprint, rather than the device fingerprint generated only by using the generally fixed device information, can effectively avoid the problem that the mobile phone end running on the PC cannot identify through means of modifying and forging the mobile phone information, and inhibit the flooding of network fraud and network black products, thereby protecting the legal interests of APP developers, the affiliated institutions and normal consumers, and maintaining a fair network environment.
Fig. 5 is a schematic block diagram of an identification unit structure in embodiment 1 of an identification apparatus for a counterfeit mobile terminal based on a sensor fingerprint of a mobile phone according to an embodiment of the present invention, and as shown in fig. 5, sensor data of an APP running device is subjected to index calculation to generate a sensor fingerprint.
In the specific embodiment shown in the figure, the identification unit specifically includes an index calculation module 1 and a fingerprint generation module 2, where the index calculation module 1 is configured to calculate a sensitivity index and a deviation statistical index in a use process according to the sensor device attribute and the characteristic signal; the fingerprint generating module 2 is used for generating various sensor fingerprints according to the two indexes through a Hash algorithm.
As shown in fig. 5, by using the device attributes and characteristic signals of the sensor, rather than relying on only fixed and unchangeable device and system attributes, the occurrence of detection situations can be effectively avoided by using modifier software, and the flooding of network fraud and network blackout is suppressed, so that the legal interests of APP developers, the affiliated mechanisms and normal consumers are protected, and a fair network environment is maintained.
The specific embodiment of the invention provides a method and a device for identifying a counterfeit mobile terminal based on a fingerprint of a mobile phone sensor, and the method and the device only adopt the data of the sensor without the attributes of other equipment and systems to generate the fingerprint, so the method and the device have the advantages of less characteristics required by fingerprint generation and small data acquisition amount; meanwhile, the invention combines the fixed equipment attribute of the sensor and the changed characteristic signal as the characteristic basis of fingerprint generation, can avoid using mobile phone information to modify software to avoid the occurrence of detection situation, has the advantage of high detection precision, can effectively inhibit and ensure the legal interests of the owner of the application program in the process of operation and popularization, and protects the assets of the owner of the application program from being stolen by illegal means such as black birth weeding wool and the like to cause loss.
The foregoing is merely an illustrative embodiment of the present invention, and any equivalent changes and modifications made by those skilled in the art without departing from the spirit and principle of the present invention should fall within the protection scope of the present invention.
Claims (4)
1. A counterfeit mobile terminal identification method based on mobile phone sensor fingerprints is characterized by comprising the following steps:
(1) acquiring sensor equipment attribute information of APP operation equipment and a characteristic signal generated by a sensor; the equipment attributes of the sensors are the types and names of various sensors, the characteristic signals generated by the sensors are all output values of various sensors in continuous seconds, the acceleration sensors output multiple groups of acceleration values of three axes x, y and z, the gyroscope sensors output multiple groups of angular acceleration values of three axes x, y and z, and the temperature sensors and the pressure sensors output multiple groups of temperature values and multiple groups of pressure values respectively;
(2) generating a sensor fingerprint according to the sensor equipment attribute and the characteristic signal;
(3) judging whether the type of the APP operation equipment is a mobile phone end forged by a Personal Computer (PC) or not according to the sensor fingerprint;
the method further comprises the following steps:
according to the obtained multiple groups of output values of the various sensors, a finite sequence is obtained through fast Fourier transform, a low-frequency sequence item is filtered through high-pass filtering, and then the standard deviation of the high-frequency sequence item is calculated to serve as the sensitivity index of the various sensors of the APP operation equipment; according to the obtained multiple groups of output values of the various sensors, the variance of the multiple groups of output values is counted to serve as a statistical index of the deviation of the various sensors of the APP operation equipment in the use process; generating fingerprint information of the sensors by utilizing various sensors and two indexes corresponding to the sensors, wherein the fingerprint format is sensor type 1, corresponding sensitivity index 1 and corresponding offset statistical index 1; the method comprises the following steps that the sensor type 2 corresponds to a sensitivity index 2, the corresponding offset statistical index 2 corresponds to the sensitivity index 2, and the rest is done in the same way until all types of sensors which can be obtained in the mobile phone are listed; then, processing the sensitivity index and the offset statistical index of the sensor through a Hash algorithm to obtain an MD5 value of the sensor, wherein the MD5 value is used as a final fingerprint of each sensor; the final fingerprint format is therefore sensor type 1, MD5 value 1, sensor type 2, MD5 value 2, and so on, until all types of sensors available in the handset are listed.
2. A counterfeit mobile terminal identification method based on the fingerprint of the mobile phone sensor according to claim 1, wherein: the method further comprises the following steps:
and comparing the generated various sensor fingerprints with various sensor fingerprints of the mobile phone forged on the PC, and if the MD5 values corresponding to the various sensors are all equal, determining that the equipment is a forged mobile terminal.
3. A counterfeit mobile terminal identification method based on the fingerprint of the mobile phone sensor according to claim 1, wherein: the sensors comprise an acceleration sensor, a gyroscope sensor, a magnetic field sensor, a pressure sensor, a temperature sensor, a distance sensor and a direction sensor.
4. A counterfeit mobile terminal identification device based on mobile phone sensor fingerprints is characterized by comprising:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring the equipment attribute of a sensor of APP operation equipment and the characteristic signal generated by the sensor, the equipment attribute of the sensor is the type and name of the sensor, and the characteristic signal generated by the sensor is all output values of various sensors in continuous seconds;
the identification unit is used for automatically generating a sensor fingerprint according to the equipment attribute and the characteristic signal;
the judging unit is used for judging whether the APP operation equipment is a forged mobile terminal on the Personal Computer (PC) or not according to the sensor fingerprint;
the identification unit specifically includes:
the sensitivity calculation module is used for calculating the sensitivity indexes of various sensors, obtaining a finite sequence through fast Fourier transform according to the obtained multiple groups of output values of the various sensors, and calculating the standard deviation of high-frequency sequence items after high-pass filtering to serve as the sensitivity indexes of the various sensors;
the offset calculation module is used for calculating offset statistical indexes in the use process of various sensors, and calculating the variance of the output values as the offset indexes according to the obtained multiple groups of output values of various sensors;
the fingerprint generation module generates fingerprint information of the sensors according to various sensors and two corresponding indexes thereof, wherein the fingerprint format is sensor type 1, corresponding sensitivity index 1 and corresponding offset statistical index 1; the method comprises the following steps that the sensor type 2 corresponds to a sensitivity index 2, the corresponding offset statistical index 2 corresponds to the sensitivity index 2, and the rest is done in the same way until all types of sensors which can be obtained in the mobile phone are listed; then, the sensor type and the corresponding sensitivity index and the offset statistical index are processed through a Hash algorithm to obtain an MD5 value of the sensor, the MD5 value is used as a final fingerprint of various sensors, the final fingerprint format is sensor type 1, MD5 value 1, sensor type 2 and MD5 value 2, and so on until all types of sensors which can be obtained in the mobile phone are listed.
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| CN110990823B (en) * | 2019-11-13 | 2024-03-15 | 北京数字联盟网络科技有限公司 | Equipment fingerprint extraction method based on smart phone sensor |
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