CN111565383A - Method for eliminating channel characteristics and extracting radio frequency fingerprint of ZigBee device - Google Patents
Method for eliminating channel characteristics and extracting radio frequency fingerprint of ZigBee device Download PDFInfo
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- CN111565383A CN111565383A CN202010417406.5A CN202010417406A CN111565383A CN 111565383 A CN111565383 A CN 111565383A CN 202010417406 A CN202010417406 A CN 202010417406A CN 111565383 A CN111565383 A CN 111565383A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2602—Signal structure
- H04L27/261—Details of reference signals
- H04L27/2613—Structure of the reference signals
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2647—Arrangements specific to the receiver only
- H04L27/2649—Demodulators
- H04L27/265—Fourier transform demodulators, e.g. fast Fourier transform [FFT] or discrete Fourier transform [DFT] demodulators
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/06—Authentication
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/60—Context-dependent security
- H04W12/69—Identity-dependent
- H04W12/79—Radio fingerprint
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W8/00—Network data management
- H04W8/22—Processing or transfer of terminal data, e.g. status or physical capabilities
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Abstract
The invention discloses a method for eliminating channel characteristics and extracting radio frequency fingerprints suitable for ZigBee equipment, which comprises the following steps: receiving a signal sent by a ZigBee transmitter to be identified, and performing down-conversion on the received signal to obtain a baseband signal; preprocessing the baseband signal, and extracting a preamble signal and a frame head delimiter SFD in each frame of ZigBee signal; performing FFT (fast Fourier transform) on each preamble symbol to obtain a frequency domain signal of each preamble symbol; dividing the frequency domain signals of the 1 st to 8 th preamble symbols by the frequency domain signals of the 2 nd SFD symbols respectively to obtain 8 symbol frequency spectrum quotients, and finishing channel characteristic elimination; and taking the 8 symbol frequency spectrum quotients as radio frequency fingerprints of ZigBee for equipment identity authentication. The invention can eliminate the influence of the channel characteristics on the radio frequency fingerprint and improve the robustness.
Description
Technical Field
The invention relates to the field of information security, in particular to a method for eliminating channel characteristics and extracting radio frequency fingerprints, which is suitable for ZigBee equipment.
Background
The power difference of hardware elements inside the device can cause slight distortion of the transmitted signal. This distortion is unique and unclonable, as is the case with human fingerprints. This feature is therefore also referred to as the radio frequency fingerprint feature of the device and can thus be used for identification and authentication of the electromagnetic radiation source. Particularly, the device identification technology based on the physical fingerprint characteristics can accurately distinguish wireless devices even adopting the same frequency, bandwidth and modulation mode, and has very good practical value. Thus, an authentication system based on physical fingerprint features can authenticate the accessing own wireless device at the physical signal layer. Compared with the traditional equipment identity authentication method, the physical layer fingerprint technology can effectively resist attacks such as counterfeiting and tampering.
However, in the environment of wireless communication, the response of the wireless channel and the transmitted signal exhibit a linear convolution relationship, and therefore the characteristics of the wireless channel also cause signal distortion. Since most of the device physical fingerprint information and the transmitted signal are also in a convolution relationship. Signal distortion caused by the wireless channel is difficult to separate from signal distortion caused by the physical fingerprint of the device. Further, since the signal variation caused by the wireless channel is larger than the physical fingerprint of the device, when the transmitter passes through a different wireless channel, the channel influence may have a great influence on the extraction of the physical fingerprint feature of the device. How to eliminate the inevitable channel characteristic influence in actual communication and simultaneously retain the device physical fingerprint information is a practical problem to be solved.
ZigBee is a wireless network protocol for low-speed short-distance transmission, and the bottom layer is a media access layer and a physical layer which adopt IEEE 802.15.4 standard specifications. The method has the main characteristics of low speed, low power consumption, low cost, support of a large number of network nodes, support of various network topologies, low complexity, reliability and safety. The ZigBee device is widely applied to an Internet of things system, and the traditional encryption authentication mode is not suitable for identity authentication of the ZigBee device due to the requirement of low power consumption and battery power supply. Therefore, a method and a device for channel characteristic elimination and radio frequency fingerprint extraction suitable for ZigBee devices are urgently needed.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a method for eliminating channel characteristics and extracting radio frequency fingerprints, which is suitable for ZigBee equipment, can effectively eliminate the inevitable channel characteristic influence in actual communication, and simultaneously reserves the physical fingerprint information of the equipment.
The purpose of the invention is realized by the following technical scheme:
a method for eliminating channel characteristics and extracting radio frequency fingerprints suitable for ZigBee equipment comprises the following steps:
(1) receiving a signal sent by a target transmitter, and performing down-conversion on the received signal to obtain a baseband signal;
(2) preprocessing a baseband signal to extract a preamble signal and an SFD, wherein the preamble signal comprises 8 preamble symbols (0x00), and the SFD comprises two symbols (0x07 and 0x 0A);
(3) performing FFT (fast Fourier transform) on each preamble symbol to obtain a frequency domain signal of each preamble symbol;
(4) performing FFT on the second SFD symbol to obtain a frequency domain signal of the second SFD symbol;
(5) dividing the frequency domain signals of the 8 preamble symbols by the frequency domain signals of the 2 nd SFD symbol respectively to obtain 8 frequency domain signal quotients, and completing the separation of channel characteristics and equipment physical fingerprints;
(6) and taking the 8 frequency domain signal quotients as the physical fingerprints of the equipment for equipment identity authentication.
Further, the pretreatment in the step (2) comprises: and carrying out frequency rough estimation, frequency fine estimation, frequency compensation, time synchronization, phase synchronization and amplitude normalization in sequence.
Further, the preamble signal extracted in step (2) is specifically:
y(n)＝[y1(n),y2(n),...,y8(n)]
wherein y (n) is the extracted preamble signal, yiAnd (n) is the ith preamble symbol in the preamble signal.
The extracted 2 nd SFD signal is specifically: y iss(n)
Further, the frequency domain signal of the preamble symbol in step (3) is specifically:
in the formula (I), the compound is shown in the specification,
is a frequency domain signal of the ith preamble symbol, yi(n) is the ith preamble symbol in the preamble signal, and FFT () is the FFT transform function.
Further, the frequency domain signal of the second SFD symbol in step (4) is specifically:
further, the frequency domain preamble signal difference specifically is:
in the formula, omegai(k) For the ith frequency-domain signal quotient,
is the frequency domain signal of the ith preamble symbol.
The invention is realized by a separating device, and the separating device suitable for eliminating the channel characteristics of the ZigBee equipment and extracting the radio frequency fingerprint comprises:
the signal receiving module is used for receiving signals sent by a target transmitter;
the down-conversion module is used for performing down-conversion on the received signal to obtain a baseband signal;
a preprocessing module, for preprocessing the baseband signal and extracting a preamble frame header delimiter SFD signal, wherein the preamble signal comprises 8 preamble symbols (0x00), the SFD comprises two symbols (0x07 and 0x0A)
The FFT conversion module is used for carrying out FFT conversion on each leading symbol to obtain a frequency domain signal of each leading symbol;
the signal difference module is used for subtracting the frequency domain signal of the 2 nd SFD symbol from the frequency domain signal of the 8 leading symbols respectively to obtain 8 frequency domain leading signal differences so as to complete the separation of the channel characteristics and the physical fingerprint of the equipment;
and the fingerprint confirmation module is used for taking the 8 frequency domain signal quotients as equipment physical fingerprints and authenticating equipment identities.
The invention has the beneficial effects that: compared with the prior art, the invention has the following remarkable advantages: the method for obtaining the quotient of the preamble signal and the SFD symbol in the frequency domain effectively eliminates the influence of wireless channel characteristics on the extraction of the physical fingerprint characteristics of the equipment, and the channel robustness of the equipment authentication method based on the physical fingerprint characteristic technology of the equipment can be effectively improved by using the method.
Drawings
Fig. 1 is a schematic flowchart of an embodiment of a method for channel feature elimination and radio frequency fingerprint extraction suitable for a ZigBee device provided by the present invention.
Detailed Description
A method for channel characteristic elimination and radio frequency fingerprint extraction suitable for ZigBee devices is disclosed, as shown in FIG. 1, and comprises the following steps:
(1) receiving a signal sent by a target transmitter, and performing down-conversion on the received signal to obtain a baseband signal;
(2) preprocessing a baseband signal to extract a preamble signal and an SFD, wherein the preamble signal comprises 8 preamble symbols (0x00), and the SFD comprises two symbols (0x07 and 0x 0A);
wherein the pre-processing comprises: and carrying out frequency rough estimation, frequency fine estimation, frequency compensation, time synchronization, phase synchronization and amplitude normalization in sequence. The finally extracted preamble signal is specifically:
y(n)＝[y1(n),y2(n),...,y8(n)]
wherein y (n) is the extracted preamble signal, yiAnd (n) is the ith preamble symbol in the preamble signal.
The extracted 2 nd SFD signal is specifically: y iss(n)
(3) Performing FFT on each preamble symbol to obtain a frequency domain signal of each preamble symbol:
in the formula (I), the compound is shown in the specification,
is a frequency domain signal of the ith preamble symbol, yi(n) is the ith preamble symbol in the preamble signal, and FFT () is the FFT transform function.
(4) Performing FFT on the second SFD symbol to obtain a frequency domain signal of the second SFD symbol:
further, the frequency domain preamble signal difference specifically is:
(5) dividing the frequency domain signals of the 8 preamble symbols by the frequency domain signals of the 2 nd SFD symbol respectively to obtain 8 frequency domain signal quotients, and completing the separation of channel characteristics and equipment physical fingerprints:
in the formula, omegai(k) For the ith frequency-domain signal quotient,
is the frequency domain signal of the ith preamble symbol.
(6) And taking the 8 frequency domain signal quotients as the physical fingerprints of the equipment for equipment identity authentication.
Ω(k)＝[Ω1(k),Ω2(k),...,Ω8(k)]And the method is used for equipment identity authentication.
The equipment identity authentication method comprises a plurality of methods such as a convolutional neural network, machine learning, deep learning, Euclidean distance, Mahalanobis distance, linear programming and the like.
The invention is realized by a separating device, and the separating device suitable for eliminating the channel characteristics of the ZigBee equipment and extracting the radio frequency fingerprint comprises:
the signal receiving module is used for receiving signals sent by a target transmitter;
the down-conversion module is used for performing down-conversion on the received signal to obtain a baseband signal;
a preprocessing module, for preprocessing the baseband signal and extracting a preamble frame header delimiter SFD signal, wherein the preamble signal comprises 8 preamble symbols (0x00), the SFD comprises two symbols (0x07 and 0x0A)
The FFT conversion module is used for carrying out FFT conversion on each leading symbol to obtain a frequency domain signal of each leading symbol;
the signal difference module is used for subtracting the frequency domain signal of the 2 nd SFD symbol from the frequency domain signal of the 8 leading symbols respectively to obtain 8 frequency domain leading signal differences so as to complete the separation of the channel characteristics and the physical fingerprint of the equipment;
and the fingerprint confirmation module is used for taking the 8 frequency domain signal quotients as equipment physical fingerprints and authenticating equipment identities.
Claims (8)
1. A method for eliminating channel characteristics and extracting radio frequency fingerprints suitable for ZigBee equipment is characterized by comprising the following steps:
(1) receiving a radio frequency signal sent by ZigBee equipment to be detected, and performing down-conversion on the received radio frequency signal to obtain a baseband signal;
(2) preprocessing a baseband signal, and extracting a preamble signal and a frame start delimiter (SFD) signal, wherein the preamble signal comprises 8 preamble symbols (0x00), and the SFD comprises two symbols (0x07 and 0x 0A);
(3) performing FFT (fast Fourier transform) on the 8 preamble symbols to obtain a frequency domain signal of each preamble symbol;
(4) performing FFT (fast Fourier transform) on the 2 nd SFD symbol to obtain a frequency domain signal of the 2 nd SFD symbol;
(5) dividing the frequency domain signals of the 8 leading symbols by the frequency domain signals of the 2 nd front SFD symbol respectively to obtain 8 frequency domain signal quotients, and completing the separation of channel characteristics and equipment physical fingerprints;
(6) and taking the 8 frequency domain signal quotients as the physical fingerprints of the equipment for equipment identity authentication.
2. The method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein: the pretreatment of the step (2) comprises the following steps: and carrying out frequency rough estimation, frequency fine estimation, frequency compensation, time synchronization, phase synchronization and amplitude normalization in sequence.
3. The method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein: the preamble signal extracted in the step (2) is specifically:
y(n)＝[y1(n),y2(n),...,y8(n)]
wherein y (n) is the extracted preamble signal, yi(n) is the ith preamble symbol in the preamble signal;
the extracted 2 nd SFD signal is specifically: y iss(n)。
4. The method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein: the frequency domain signal of the preamble symbol in the step (3) is specifically:
Yi f(k)＝FFT(yi(n)),i＝1,...,8
in the formula, Yi f(k) Is a frequency domain signal of the ith preamble symbol, yi(n) is the ith preamble symbol in the preamble signal, and FFT () is the FFT transform function.
5. The method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein: the frequency domain signal of the second SFD symbol in step (4) is specifically:
6. the method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein: in step (5), the frequency domain signal quotient is specifically:
in the formula, omegai(k) Is the ith frequency domain signal quotient, Yi f(k) Is the frequency domain signal of the ith preamble symbol.
7. The method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein: in the step (6), the equipment identity authentication method comprises a convolutional neural network, machine learning, deep learning, Euclidean distance, Mahalanobis distance and linear programming.
8. The method for channel characteristic elimination and radio frequency fingerprint extraction for ZigBee devices of claim 1, wherein:
receiving a signal sent by a target transmitter by using a signal receiving module;
adopting a down-conversion module to carry out down-conversion on the received signal to obtain a baseband signal;
preprocessing a baseband signal by using a preprocessing module, and extracting a preamble signal frame head delimiter (SFD) signal, wherein the preamble signal comprises 8 preamble symbols (0x00), and the SFD comprises two symbols (0x07 and 0x 0A);
performing FFT on each preamble symbol by adopting an FFT conversion module to obtain a frequency domain signal of each preamble symbol;
respectively subtracting the frequency domain signals of the 2 nd SFD symbol from the frequency domain signals of the 8 leading symbols by adopting a signal difference module to obtain 8 frequency domain leading signal differences, and completing the separation of channel characteristics and equipment physical fingerprints;
and the 8 frequency domain signal quotients are used as the physical fingerprints of the equipment by adopting a fingerprint confirmation module and are used for equipment identity authentication.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112101179A (en) * | 2020-09-10 | 2020-12-18 | 国网江苏省电力有限公司信息通信分公司 | Anti-channel interference transient radio frequency fingerprint feature extraction method |
| CN113343868A (en) * | 2021-06-15 | 2021-09-03 | 四川九洲电器集团有限责任公司 | Radiation source individual identification method and device, terminal and storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1502369A2 (en) * | 2002-04-22 | 2005-02-02 | Cognio, Inc. | System and method for management of a shared frequency band |
| CN102904724A (en) * | 2012-10-17 | 2013-01-30 | 南通大学 | Radio-frequency-fingerprint-based challenge-response authentication protocol method |
| CN103051458A (en) * | 2012-12-27 | 2013-04-17 | 南通大学 | Method for obtaining steady radio frequency fingerprints from BPSK (Binary Phase Shift Keying) signal |
| CN109302392A (en) * | 2018-09-28 | 2019-02-01 | 东南大学 | Authentication method based on wireless channel reciprocity and equipment physical fingerprint |
| CN109919015A (en) * | 2019-01-28 | 2019-06-21 | 东南大学 | A kind of radio-frequency fingerprint extraction and recognition methods based on more sampling convolutional neural networks |
| CN110061947A (en) * | 2019-03-28 | 2019-07-26 | 东南大学 | A kind of anti-multipath jamming radio-frequency fingerprint extracting method based on OFDM lead code |
-
2020
- 2020-05-18 CN CN202010417406.5A patent/CN111565383B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1502369A2 (en) * | 2002-04-22 | 2005-02-02 | Cognio, Inc. | System and method for management of a shared frequency band |
| CN102904724A (en) * | 2012-10-17 | 2013-01-30 | 南通大学 | Radio-frequency-fingerprint-based challenge-response authentication protocol method |
| CN103051458A (en) * | 2012-12-27 | 2013-04-17 | 南通大学 | Method for obtaining steady radio frequency fingerprints from BPSK (Binary Phase Shift Keying) signal |
| CN109302392A (en) * | 2018-09-28 | 2019-02-01 | 东南大学 | Authentication method based on wireless channel reciprocity and equipment physical fingerprint |
| CN109919015A (en) * | 2019-01-28 | 2019-06-21 | 东南大学 | A kind of radio-frequency fingerprint extraction and recognition methods based on more sampling convolutional neural networks |
| CN110061947A (en) * | 2019-03-28 | 2019-07-26 | 东南大学 | A kind of anti-multipath jamming radio-frequency fingerprint extracting method based on OFDM lead code |
Non-Patent Citations (2)
| Title |
|---|
| EMRE UZUNDURUKAN等: "Design of low-cost modular RF front end for RF fingerprinting of Bluetooth signals", 《 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)》 * |
| 李雨珊等: "适合终端的射频指纹信号特征提取及识别", 《通信技术》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112101179A (en) * | 2020-09-10 | 2020-12-18 | 国网江苏省电力有限公司信息通信分公司 | Anti-channel interference transient radio frequency fingerprint feature extraction method |
| CN113343868A (en) * | 2021-06-15 | 2021-09-03 | 四川九洲电器集团有限责任公司 | Radiation source individual identification method and device, terminal and storage medium |
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