CN112492609A - Wi-Fi signal fluctuation-based IoT equipment safety automatic pairing method and device - Google Patents
Wi-Fi signal fluctuation-based IoT equipment safety automatic pairing method and device Download PDFInfo
- Publication number
- CN112492609A CN112492609A CN202011421301.3A CN202011421301A CN112492609A CN 112492609 A CN112492609 A CN 112492609A CN 202011421301 A CN202011421301 A CN 202011421301A CN 112492609 A CN112492609 A CN 112492609A
- Authority
- CN
- China
- Prior art keywords
- equipment
- paired
- signal
- pairing
- channel state
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000001914 filtration Methods 0.000 claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 17
- 230000009467 reduction Effects 0.000 claims abstract description 15
- 238000000605 extraction Methods 0.000 claims description 18
- 238000001228 spectrum Methods 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 8
- 238000005311 autocorrelation function Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 6
- 230000005484 gravity Effects 0.000 claims description 6
- 238000011946 reduction process Methods 0.000 claims 2
- 230000009471 action Effects 0.000 abstract description 7
- 238000010408 sweeping Methods 0.000 description 8
- 239000000284 extract Substances 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 241000219122 Cucurbita Species 0.000 description 1
- 235000009852 Cucurbita pepo Nutrition 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- 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
- H04L9/0875—Generation of secret information including derivation or calculation of cryptographic keys or passwords based on channel impulse response [CIR]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L2209/00—Additional information or applications relating to cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
- H04L2209/80—Wireless
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
- H04W84/10—Small scale networks; Flat hierarchical networks
- H04W84/12—WLAN [Wireless Local Area Networks]
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention relates to and discloses an IoT (Internet of things) equipment safety automatic pairing method based on Wi-Fi signal fluctuation, which comprises the following steps: controlling the equipment to be paired and original safety equipment in the trust chain to simultaneously transmit a Wi-Fi data packet with a specified format to the Wi-Fi equipment; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal; carrying out noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; judging whether the feature key of the equipment to be paired is the same as that of the original safety equipment or not, and if so, automatically pairing the equipment to be paired; and if not, not allowing the equipment to be paired. By the method and the device, the user does not need to input passwords and other actions participating in pairing, and only the IoT equipment is taken into a room to be automatically paired, so that the method and the device are more suitable for an IoT scene of interconnection of everything in the future.
Description
Technical Field
The invention relates to the technical field of IoT equipment pairing, in particular to an IoT equipment safety automatic pairing method and device based on Wi-Fi signal fluctuation.
Background
Currently, with the development of society, internet of things (IoT) devices have increasingly entered people's lives. These IoT devices provide significant value to smart home operations, but the data they create typically contains privacy sensitive information for users within the home. Therefore, securing wireless communication among IoT devices is a key capability that all home internet of things need to deploy. Of great importance, the newly deployed IoT devices must be able to establish secure connections with existing devices through encryption keys, thereby preventing man-in-the-middle and protocol manipulation attacks. However, existing solutions, which require user participation in protocols (e.g. entering passwords), may temporarily solve the problem of new device access within a portion of the system, but are not feasible in many cases. The main reason is that the number of IoT devices in a home is expected to increase from around ten to hundreds of thousands in the next decade, which would greatly increase the burden on the homeowner if human participation is required at the time of access. Secondly, most emerging internet of things devices do not have a user interface, so that it is very difficult for a homeowner to directly input a password or manage the devices.
Although there are some solutions at present, such as configuring the IoT device with a preloaded key, configuring a user interface, or pairing dedicated hardware (e.g., NFC, RFID, etc.), this will burden the device manufacturer, limit the operability of the IoT device, and delay the innovation of the IoT device. At present, there is a pairing method based on IoT device sensors, which extracts entropy from the surrounding environment by using sensors configured in a large number of IoT devices, and converts the entropy into randomness to form the basis of a symmetric key. For example, mutual authentication may be performed using sensors to sense sound or light at home, short audio frequencies, using implanted heart sensors, or using accelerometers of on-road trucks. However, these methods must utilize devices with the same sensor, including the same sensor type, vendor chip set, and calibration method, to extract a valid symmetric key. The existing IoT equipment has abundant and various sensors and strong heterogeneity, and the methods are only suitable for special conditions, have no universality and are difficult to popularize and use on a large scale. To address these issues, there are researchers who have proposed a context-based IoT device pairing method. They utilize sensors on multiple heterogeneous IoT devices, capture events that occur in the room, generate symmetric keys using time differences of event contexts, and gradually increase confidence over time. The method considers that the interior of a room is safe, and because people outside the room are difficult to capture all details of time, the generated time difference is incomplete, so that a complete key is difficult to obtain, and the safety of the method is formed. This approach solves the problem of heterogeneity of IoT devices, but there are two problems in practical use. The first problem is that when a newly accessed internet of things device is not provided with a sensor or the configured sensor is difficult to be obviously triggered by a common event (such as a temperature sensor), the method cannot be used. A second problem is that the method detects the time difference of fluctuation based on the context of the event, i.e. only the detected event with a certain repeatability is kept, and the event that only causes the transient response of the sensor is selected to be directly discarded, which wastes the effective information captured by many sensors. A third problem is that the common events that occur in a room and cause a significant time difference in context are rare, such as walking, talking, etc., and in practical situations, most of the keys will be generated by a vibration sensor and a sound sensor, etc., but for actions such as smoking, etc., the common sensors will not be significantly changed, which results in that the time taken for the keys to reach a sufficient confidence level may be too long without active participation of people.
Disclosure of Invention
The purpose of the invention is: the method and the device for automatically pairing the IoT equipment based on Wi-Fi signal fluctuation can build a connected bridge between heterogeneous IoT equipment by using Wi-Fi functions configured in the IoT equipment, and realize full-automatic, rapid and safe IoT equipment connection by detecting the fluctuation of Wi-Fi signals caused by actions in a space, extracting characteristics and generating a symmetric key used for pairing.
In order to achieve the above object, the present invention provides an IoT device secure automatic pairing method based on Wi-Fi signal fluctuation, including:
controlling the equipment to be paired and original safety equipment in the trust chain to simultaneously transmit a Wi-Fi data packet with a specified format to the Wi-Fi equipment; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal;
carrying out noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; wherein the feature extraction comprises: extracting time domain information and frequency domain information in different time periods;
judging whether the feature key of the equipment to be paired is the same as that of the original safety equipment or not, and if so, automatically pairing the equipment to be paired; and if not, not allowing the equipment to be paired.
Further, the time domain information includes: a form factor, a pulse factor, a kurtosis factor, a margin factor, a short-time energy, and a short-time autocorrelation function; the frequency domain information includes: center of gravity frequency, mean square frequency, fundamental frequency, frequency spectrum, energy spectrum, and wavelet coefficients.
Further, the noise reduction processing includes: fast Fourier Transform (FFT), Short Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT); the filtering process includes: gaussian filtering and kalman filtering.
An embodiment of the present invention further provides an IoT device security auto-pairing apparatus based on Wi-Fi signal fluctuation, including: the device comprises a data processing module, a feature extraction module and a judgment module; wherein,
the data processing module is used for controlling the equipment to be paired and the original safety equipment in the trust chain to simultaneously transmit a Wi-Fi data packet with a specified format to the Wi-Fi equipment; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal;
the characteristic extraction module is used for carrying out noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; wherein the feature extraction comprises: extracting time domain information and frequency domain information in different time periods;
the judging module is used for judging whether the feature key of the equipment to be paired is the same as the feature key of the original safety equipment or not, and if so, automatically pairing the equipment to be paired; and if not, not allowing the equipment to be paired.
Further, the time domain information includes: a form factor, a pulse factor, a kurtosis factor, a margin factor, a short-time energy, and a short-time autocorrelation function; the frequency domain information includes: center of gravity frequency, mean square frequency, fundamental frequency, frequency spectrum, energy spectrum, and wavelet coefficients.
Further, the noise reduction processing includes: fast Fourier Transform (FFT), Short Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT); the filtering process includes: gaussian filtering and kalman filtering.
An embodiment of the present invention further provides a computer terminal device, which is characterized by including:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a Wi-Fi signal fluctuation-based IoT device secure auto-pairing method as any of the above.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the Wi-Fi signal fluctuation-based IoT device security auto-pairing method according to any of the above.
Compared with the prior art, the IoT equipment safety automatic pairing method and the IoT equipment safety automatic pairing device based on Wi-Fi signal fluctuation have the beneficial effects that:
1. the user does not need to participate: by the method and the device, the user does not need to input passwords and other actions participating in pairing, and only the IoT equipment is taken into a room to be automatically paired, so that the method and the device are more suitable for an IoT scene of interconnection of everything in the future;
2. and (3) rapid pairing: the invention has no limit to the event causing the pairing, as long as the event can be detected and the required symmetric key is generated, the equipment does not need to wait for the occurrence of the detectable event, and the pairing can be completed in a short time after the user brings the equipment into a room;
3. and (3) safe pairing: the Wi-Fi signal is used, the indoor action is used for introducing the environment entropy into the signal and generating the key, the environment entropy can be completely extracted only in the security domain of the room, an attacker outside the room can not completely extract the environment entropy, and the pairing security is guaranteed;
4. has universality: the IoT equipment is paired by adopting Wi-Fi signals, and as the IoT equipment is generally provided with a Wi-Fi module, the use of the IoT equipment is equivalent to no limitation on IoT equipment components, and similar methods usually require that the IoT equipment is provided with a corresponding sensor.
Drawings
Fig. 1 is a schematic flowchart of an IoT device secure automatic pairing method based on Wi-Fi signal fluctuation according to a first embodiment of the present invention;
fig. 2 is a schematic overall architecture diagram of an IoT device security auto-pairing method based on Wi-Fi signal fluctuation according to a first embodiment of the present invention;
fig. 3 is a schematic diagram of a specific usage scenario in an IoT device security auto-pairing method based on Wi-Fi signal fluctuation according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an IoT device security auto-pairing apparatus based on Wi-Fi signal fluctuation according to a second 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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
The first embodiment of the present invention:
as shown in fig. 1 to fig. 3, an IoT device secure automatic pairing method based on Wi-Fi signal fluctuation provided by an embodiment of the present invention includes at least the following steps:
s101, controlling equipment to be paired and original safety equipment in a trust chain to simultaneously transmit a Wi-Fi data packet with a specified format to the Wi-Fi equipment; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal;
it should be noted that the Wi-Fi device is a device that has the capability of transmitting and receiving Wi-Fi signals and has sufficient computing capability, and the most common security terminal is a gateway that controls all IoT devices, or in a special case, any security device with sufficient computing capability in the trust chain may serve as a security terminal;
it should be noted that, for the security device in the trust chain, specifically, refer to: the device which has been authenticated by the symmetric key has a Wi-Fi module. When the equipment to be paired sends a pairing request, the safety equipment transmits a data packet with a specified format to the safety terminal, analyzes the key, then takes the key as a credible key verified by the symmetric key, and compares the key with an incredible key analyzed from a new terminal. The method has the precondition that at least one safety device is arranged in the trust chain, if not, the first device needs to be added manually by a user;
it should be noted that, for the trust chain, specifically, refer to: after the devices provide security verification and are successfully paired, namely, the devices join the trust chain consisting of all the security devices, and after the devices have the qualification of generating the trusted key, the devices to be paired also take the responsibility of generating the trusted key when joining. According to different security requirements, when the untrusted key of the device to be paired is successfully matched with k (k is 1, 2, …, n) trusted keys of the secure device, the device to be paired is added into the trust chain, becomes the secure device, and is considered to be successfully paired.
S102, carrying out noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; wherein the feature extraction comprises: extracting time domain information and frequency domain information in different time periods;
it should be noted that, for the noise reduction and filtering treasured gourd, specifically, the following is referred to: the method is responsible for eliminating basic noise in the channel state information, and according to different characteristic value extraction requirements, a plurality of denoising methods and filtering methods can be used, such as Fast Fourier Transform (FFT), Short Time Fourier Transform (STFT), Discrete Wavelet Transform (DWT), Kalman filtering, Gaussian filtering and the like, and the characteristic extraction is carried out on the denoised result;
it should be noted that, for feature extraction, it specifically refers to: and extracting the characteristic value of the CSI information after noise reduction according to a preset characteristic extraction rule, wherein the time domain and frequency domain characteristics of the waveform can be extracted, or a machine learning method can be used for extracting the characteristics, and the extracted characteristic value string is generated into a characteristic key. An example is given here: presetting the time difference t between wave crests with the amplitude larger than A as the minimum composition of the key, determining to obtain p sections of time difference according to the confidence coefficient to obtain a key, and generating the key as { t1, t2, …, tp }. At this time, if an attacker outside the room wants to intercept the key, Wi-Fi fluctuation information with high enough precision must be obtained, but the Wi-Fi fluctuation information cannot be realized due to the obstruction of an outer wall, and a corresponding key cannot be generated as long as a value in tn is wrong, and only the security equipment in the room can obtain a complete key and use the complete key as a trusted key;
s103, judging whether the feature key of the equipment to be paired is the same as that of the original safety equipment or not, and automatically pairing the equipment to be paired if the feature key of the equipment to be paired is the same as that of the original safety equipment; and if not, not allowing the equipment to be paired.
It should be noted that, for determining whether the feature key of the device to be paired is the same as the feature key of the original secure device, the following specific steps are performed: the idea of symmetric keys is adopted, trusted keys of at most n (n is more than or equal to 1) security devices are compared with untrusted keys generated by the devices to be paired, if k (k is 1, 2, …, n) trusted keys are the same as the untrusted keys of the devices to be paired, the devices to be paired are considered as the security devices, and are brought into a trust chain, and pairing is successful.
In one embodiment of the present invention, the time domain information includes: a form factor, a pulse factor, a kurtosis factor, a margin factor, a short-time energy, and a short-time autocorrelation function; the frequency domain information includes: center of gravity frequency, mean square frequency, fundamental frequency, frequency spectrum, energy spectrum, and wavelet coefficients.
In one embodiment of the present invention, the noise reduction processing includes: fast Fourier Transform (FFT), Short Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT); the filtering process includes: gaussian filtering and kalman filtering.
For a better understanding of the invention, it may be specifically understood by the following examples:
as shown in fig. 3, it is a specific embodiment of an IoT device security self-pairing method based on Wi-Fi signal fluctuation. The safety terminal is an intelligent gateway for controlling all IoT equipment in a room, the safety equipment 1 is an intelligent television in the room, the safety equipment 2 is an intelligent sound box, the safety equipment 3 is an intelligent desk lamp, and the new equipment to be paired is an intelligent floor sweeping robot. The intelligent gateway emits a Wi-Fi hotspot to serve as an AP (access point), an original intelligent television, an intelligent sound box and an intelligent desk lamp in a room are connected with the intelligent gateway through Wi-Fi, and meanwhile, the intelligent floor sweeping robot serves as new equipment to be paired and is just brought into the room by a homeowner. The specific process of application is as follows:
1. the power supply of the intelligent sweeping robot is started, and the Wi-Fi connected with the intelligent gateway is automatically connected;
2. the intelligent gateway sends instructions to the newly accessed equipment intelligent sweeping robot and the safety equipment intelligent television, intelligent sound box and intelligent desk lamp in the room, and the equipment sends a data packet with a specified format to the intelligent gateway after receiving the instructions;
3. after receiving the data packet, a signal analysis module of the intelligent gateway extracts CSI information of the electromagnetic wave and sends the CSI information to a noise reduction module;
4. the Gaussian filter of the noise reduction module performs preliminary filtering on the amplitude of the CSI, and if the fluctuation is judged to be large enough, namely a motion event occurs in the packet sending time, the process is continued, and the filtered signal is sent to the feature extraction module;
5. the characteristic extraction module obtains the position of each peak according to a threshold value, and calculates the time difference between the peaks to obtain a characteristic value string;
6. the key generation module combines a plurality of characteristic values according to the confidence requirement to generate a corresponding key with sufficient length;
7. the key comparison module compares an untrusted key of the intelligent floor sweeping robot with trusted keys of the intelligent television, the intelligent sound box and the intelligent desk lamp, and finds that the untrusted key is overlapped with the keys of the intelligent sound box and the intelligent desk lamp, namely, the intelligent floor sweeping robot is judged to be really in a room and is considered as safety equipment;
8. the intelligent gateway transmits the information to all safety devices in the trust chain and the intelligent sweeping robot to be paired through the Wi-Fi module, and the intelligent sweeping robot is added into the trust chain and is paired successfully.
Compared with the prior art, the IoT equipment safety automatic pairing method based on Wi-Fi signal fluctuation has the beneficial effects that:
1. the user does not need to participate: by the method and the device, the user does not need to input passwords and other actions participating in pairing, and only the IoT equipment is taken into a room to be automatically paired, so that the method and the device are more suitable for an IoT scene of interconnection of everything in the future;
2. and (3) rapid pairing: the invention has no limit to the event causing the pairing, as long as the event can be detected and the required symmetric key is generated, the equipment does not need to wait for the occurrence of the detectable event, and the pairing can be completed in a short time after the user brings the equipment into a room;
3. and (3) safe pairing: the Wi-Fi signal is used, the indoor action is used for introducing the environment entropy into the signal and generating the key, the environment entropy can be completely extracted only in the security domain of the room, an attacker outside the room can not completely extract the environment entropy, and the pairing security is guaranteed;
4. has universality: the IoT equipment is paired by adopting Wi-Fi signals, and as the IoT equipment is generally provided with a Wi-Fi module, the use of the IoT equipment is equivalent to no limitation on IoT equipment components, and similar methods usually require that the IoT equipment is provided with a corresponding sensor.
Second embodiment of the invention:
as shown in fig. 4, an IoT device security auto-pairing apparatus 200 based on Wi-Fi signal fluctuation provided in an embodiment of the present invention includes: a data processing module 201, a feature extraction module 202 and a judgment module 203; wherein,
the data processing module 201 is configured to control the device to be paired and the original security device in the trust chain to transmit a Wi-Fi data packet in a specified format to the Wi-Fi device at the same time; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal;
the feature extraction module 202 is configured to perform noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; wherein the feature extraction comprises: extracting time domain information and frequency domain information in different time periods;
the judging module 203 is configured to judge whether a feature key of the device to be paired is the same as a feature key of the original security device, and if yes, automatically pair the device to be paired; and if not, not allowing the equipment to be paired.
In one embodiment of the present invention, the time domain information includes: a form factor, a pulse factor, a kurtosis factor, a margin factor, a short-time energy, and a short-time autocorrelation function; the frequency domain information includes: center of gravity frequency, mean square frequency, fundamental frequency, frequency spectrum, energy spectrum, and wavelet coefficients.
In one embodiment of the present invention, the noise reduction processing includes: fast Fourier Transform (FFT), Short Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT); the filtering process includes: gaussian filtering and kalman filtering.
Third embodiment of the invention:
the embodiment of the invention provides computer terminal equipment, which comprises one or more processors; a memory coupled to the processor for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement a Wi-Fi signal fluctuation-based IoT device secure auto-pairing method as any of the above.
The fourth embodiment of the present invention:
an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements any one of the above IoT device security auto-pairing methods based on Wi-Fi signal fluctuation.
In summary, according to the present invention, the change of the electromagnetic wave Channel State Information (CSI) when a motion event occurs in a room can be utilized to extract corresponding features after denoising the information, and a key is generated by utilizing a feature value, so that only devices in the room can generate the same key, thereby implementing IoT device pairing based on Wi-Fi signals.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and substitutions can be made without departing from the technical principle of the present invention, and these modifications and substitutions should also be regarded as the protection scope of the present invention.
Claims (8)
1. An IoT device security automatic pairing method based on Wi-Fi signal fluctuation is characterized by comprising the following steps:
controlling the equipment to be paired and original safety equipment in the trust chain to simultaneously transmit a Wi-Fi data packet with a specified format to the Wi-Fi equipment; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal;
carrying out noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; wherein the feature extraction comprises: extracting time domain information and frequency domain information in different time periods;
judging whether the feature key of the equipment to be paired is the same as that of the original safety equipment or not, and if so, automatically pairing the equipment to be paired; and if not, not allowing the equipment to be paired.
2. The Wi-Fi signal fluctuation-based IoT device security auto-pairing method in accordance with claim 1, wherein the time domain information comprises: a form factor, a pulse factor, a kurtosis factor, a margin factor, a short-time energy, and a short-time autocorrelation function; the frequency domain information includes: center of gravity frequency, mean square frequency, fundamental frequency, frequency spectrum, energy spectrum, and wavelet coefficients.
3. The Wi-Fi signal fluctuation-based IoT device secure auto-pairing method according to claim 1, wherein the noise reduction process comprises: fast Fourier Transform (FFT), Short Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT); the filtering process includes: gaussian filtering and kalman filtering.
4. An IoT device security auto-pairing apparatus based on Wi-Fi signal fluctuation, comprising: the device comprises a data processing module, a feature extraction module and a judgment module; wherein,
the data processing module is used for controlling the equipment to be paired and the original safety equipment in the trust chain to simultaneously transmit a Wi-Fi data packet with a specified format to the Wi-Fi equipment; the Wi-Fi equipment preprocesses the Wi-Fi data packet to obtain channel state information of a Wi-Fi signal;
the characteristic extraction module is used for carrying out noise reduction and filtering processing on the channel state information of the Wi-Fi signal; extracting the characteristics of the channel state information of the processed Wi-Fi signal and generating a corresponding characteristic key; wherein the feature extraction comprises: extracting time domain information and frequency domain information in different time periods;
the judging module is used for judging whether the feature key of the equipment to be paired is the same as the feature key of the original safety equipment or not, and if so, automatically pairing the equipment to be paired; and if not, not allowing the equipment to be paired.
5. The Wi-Fi signal fluctuation-based IoT device security auto-pairing apparatus according to claim 4, wherein the time domain information comprises: a form factor, a pulse factor, a kurtosis factor, a margin factor, a short-time energy, and a short-time autocorrelation function; the frequency domain information includes: center of gravity frequency, mean square frequency, fundamental frequency, frequency spectrum, energy spectrum, and wavelet coefficients.
6. The Wi-Fi signal fluctuation-based IoT device security auto-pairing apparatus according to claim 4, wherein the noise reduction process comprises: fast Fourier Transform (FFT), Short Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT); the filtering process includes: gaussian filtering and kalman filtering.
7. A computer terminal device, comprising:
one or more processors;
a memory coupled to the processor for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the Wi-Fi signal fluctuation-based IoT device secure auto-pairing method of any of claims 1-3.
8. A computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the Wi-Fi signal fluctuation-based IoT device security auto-pairing method of any of claims 1-3.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011421301.3A CN112492609B (en) | 2020-12-07 | 2020-12-07 | Wi-Fi signal fluctuation-based IoT equipment safety automatic pairing method and device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011421301.3A CN112492609B (en) | 2020-12-07 | 2020-12-07 | Wi-Fi signal fluctuation-based IoT equipment safety automatic pairing method and device |
Publications (2)
Publication Number | Publication Date |
---|---|
CN112492609A true CN112492609A (en) | 2021-03-12 |
CN112492609B CN112492609B (en) | 2021-05-18 |
Family
ID=74940490
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202011421301.3A Active CN112492609B (en) | 2020-12-07 | 2020-12-07 | Wi-Fi signal fluctuation-based IoT equipment safety automatic pairing method and device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112492609B (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113993134A (en) * | 2021-12-27 | 2022-01-28 | 广州优刻谷科技有限公司 | IoT (Internet of things) equipment secure access method and system based on RFID (radio frequency identification) signals |
Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103402200A (en) * | 2013-07-11 | 2013-11-20 | 北京邮电大学 | Secret key generation method based on wireless channel characteristics in frequency division duplex system |
CN104618900A (en) * | 2015-02-02 | 2015-05-13 | 青岛海尔智能家电科技有限公司 | Network access method for intelligent device, intelligent device and mobile terminal |
CN104901795A (en) * | 2015-05-12 | 2015-09-09 | 南京邮电大学 | Physical layer key extraction method based on channel characteristic |
CN105101467A (en) * | 2015-07-14 | 2015-11-25 | 清华大学 | Automatic equipment pairing method based on wireless signal intensity |
CN105933895A (en) * | 2016-05-04 | 2016-09-07 | 海尔优家智能科技(北京)有限公司 | Transmission method of WIFI network configuration data, intelligent device, and intelligent terminal |
CN106102055A (en) * | 2016-07-11 | 2016-11-09 | 西安电子科技大学 | The wireless channel key generation method of feature based distribution transformation |
CN106302039A (en) * | 2016-07-29 | 2017-01-04 | 海尔优家智能科技(北京)有限公司 | A kind of method and apparatus of security control intelligent appliance |
CN109068284A (en) * | 2018-09-28 | 2018-12-21 | 深圳大学 | The physical layer authentication method and system connected based on group between internet of things equipment |
CN109245885A (en) * | 2018-11-02 | 2019-01-18 | 美的集团股份有限公司 | Cryptographic key negotiation method, equipment, storage medium and system |
CN110418336A (en) * | 2019-07-11 | 2019-11-05 | 厦门亿联网络技术股份有限公司 | A kind of WiFi equipment batch is automatic to match network method, terminal device and storage medium |
US20200169886A1 (en) * | 2018-11-23 | 2020-05-28 | Samsung Eletrônica da Amazônia Ltda. | Secure method for configuring internet of things (iot) devices through wireless technologies |
CN111542042A (en) * | 2020-05-08 | 2020-08-14 | 深圳市银河风云网络***股份有限公司 | Automatic security authentication network access method for short-distance Internet of things |
US20200367316A1 (en) * | 2019-05-16 | 2020-11-19 | Apple Inc. | Self-Organizing Device |
-
2020
- 2020-12-07 CN CN202011421301.3A patent/CN112492609B/en active Active
Patent Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103402200A (en) * | 2013-07-11 | 2013-11-20 | 北京邮电大学 | Secret key generation method based on wireless channel characteristics in frequency division duplex system |
CN104618900A (en) * | 2015-02-02 | 2015-05-13 | 青岛海尔智能家电科技有限公司 | Network access method for intelligent device, intelligent device and mobile terminal |
CN104901795A (en) * | 2015-05-12 | 2015-09-09 | 南京邮电大学 | Physical layer key extraction method based on channel characteristic |
CN105101467A (en) * | 2015-07-14 | 2015-11-25 | 清华大学 | Automatic equipment pairing method based on wireless signal intensity |
CN105933895A (en) * | 2016-05-04 | 2016-09-07 | 海尔优家智能科技(北京)有限公司 | Transmission method of WIFI network configuration data, intelligent device, and intelligent terminal |
CN106102055A (en) * | 2016-07-11 | 2016-11-09 | 西安电子科技大学 | The wireless channel key generation method of feature based distribution transformation |
CN106302039A (en) * | 2016-07-29 | 2017-01-04 | 海尔优家智能科技(北京)有限公司 | A kind of method and apparatus of security control intelligent appliance |
CN109068284A (en) * | 2018-09-28 | 2018-12-21 | 深圳大学 | The physical layer authentication method and system connected based on group between internet of things equipment |
CN109245885A (en) * | 2018-11-02 | 2019-01-18 | 美的集团股份有限公司 | Cryptographic key negotiation method, equipment, storage medium and system |
US20200169886A1 (en) * | 2018-11-23 | 2020-05-28 | Samsung Eletrônica da Amazônia Ltda. | Secure method for configuring internet of things (iot) devices through wireless technologies |
US20200367316A1 (en) * | 2019-05-16 | 2020-11-19 | Apple Inc. | Self-Organizing Device |
CN110418336A (en) * | 2019-07-11 | 2019-11-05 | 厦门亿联网络技术股份有限公司 | A kind of WiFi equipment batch is automatic to match network method, terminal device and storage medium |
CN111542042A (en) * | 2020-05-08 | 2020-08-14 | 深圳市银河风云网络***股份有限公司 | Automatic security authentication network access method for short-distance Internet of things |
Non-Patent Citations (4)
Title |
---|
SHUBHAM SALONI ET AL.: "WiFi-Aware as a Connectivity Solution for IoT", 《2016 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS AND APPLICATIONS (IOTA)》 * |
XI LUO ET.AL: "A Lightweight Privacy-Preserving Communication Protocol for Heterogeneous IoT Environment", 《IEEE ACCESS》 * |
厉正吉: "物联网终端安全技术挑战与机遇", 《移动通信》 * |
杨亚军,陈秀真,马进: "基于对称多项式的智能家居设备安全认证方案研究", 《计算机应用研究》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113993134A (en) * | 2021-12-27 | 2022-01-28 | 广州优刻谷科技有限公司 | IoT (Internet of things) equipment secure access method and system based on RFID (radio frequency identification) signals |
Also Published As
Publication number | Publication date |
---|---|
CN112492609B (en) | 2021-05-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Han et al. | Do you feel what I hear? Enabling autonomous IoT device pairing using different sensor types | |
US11074033B2 (en) | Access control and validation using sonic tones | |
Yan et al. | Sok: A minimalist approach to formalizing analog sensor security | |
US10645579B2 (en) | Account login method, apparatus, and system | |
US7949879B2 (en) | Secure password entry | |
US8385824B2 (en) | Procedure for headset and device authentication | |
WO2018036198A1 (en) | Control method and apparatus for smart household, home gateway, and mobile terminal | |
WO2017031850A1 (en) | User identity authentication method, device, system and smart home | |
US20180241577A1 (en) | Proximity-Based Security | |
Gao et al. | Deaf-aid: Mobile IoT communication exploiting stealthy speaker-to-gyroscope channel | |
CN112492609B (en) | Wi-Fi signal fluctuation-based IoT equipment safety automatic pairing method and device | |
Saxena et al. | Analysis of security attacks in a smart home networks | |
US20080072313A1 (en) | Method of Establishing Security Permissions | |
JP2016129010A (en) | Hearing device with service mode and related method | |
US10638318B2 (en) | Optical chaos based wireless device fingerprinting | |
US11284256B2 (en) | Method and system for automatic access to WI-FI network | |
Mei et al. | Listen!: Audio-based smart iot device pairing protocol | |
KR101243101B1 (en) | Voice one-time password based user authentication method and system on smart phone | |
Ramani et al. | Ndnviber: Vibration-assisted automated bootstrapping of iot devices | |
CN107371160B (en) | Method and equipment for carrying out wireless connection pre-authorization on user equipment | |
Ji et al. | Authenticating smart home devices via home limited channels | |
KR101310043B1 (en) | Voice one-time password based user authentication method on smart phone | |
KR20230128328A (en) | Physical access control system with security relay | |
US20170127266A1 (en) | Method for activating a configuration mode of a device | |
CN115134773A (en) | Method and apparatus for verifying wireless access card authenticity and proximity |
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 | ||
GR01 | Patent grant | ||
GR01 | Patent grant |