CN109787757B - Non-uniform quantization method in physical layer key generation process - Google Patents

Non-uniform quantization method in physical layer key generation process Download PDF

Info

Publication number
CN109787757B
CN109787757B CN201910046556.7A CN201910046556A CN109787757B CN 109787757 B CN109787757 B CN 109787757B CN 201910046556 A CN201910046556 A CN 201910046556A CN 109787757 B CN109787757 B CN 109787757B
Authority
CN
China
Prior art keywords
quantization
rss
uniform quantization
uniform
mismatch rate
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.)
Active
Application number
CN201910046556.7A
Other languages
Chinese (zh)
Other versions
CN109787757A (en
Inventor
徐志江
程文锋
金文兵
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang Institute of Mechanical and Electrical Engineering Co Ltd
Original Assignee
Zhejiang Institute of Mechanical and Electrical Engineering Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Zhejiang Institute of Mechanical and Electrical Engineering Co Ltd filed Critical Zhejiang Institute of Mechanical and Electrical Engineering Co Ltd
Priority to CN201910046556.7A priority Critical patent/CN109787757B/en
Publication of CN109787757A publication Critical patent/CN109787757A/en
Application granted granted Critical
Publication of CN109787757B publication Critical patent/CN109787757B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

A non-uniform quantization method in the process of generating a physical layer security key is characterized in that the wireless signal strength RSS measured between two legal communication parties is modeled into two-dimensional Gaussian distribution with a correlation coefficient rho, and the correlation coefficient represents the degree of difference between the measured values of the two parties; carrying out standardization processing on RSS values obtained by respective measurement; and performing non-uniform quantization with the same 13-fold line PCM quantization method on the [0,1] interval of the RSS cumulative distribution function, and mapping the quantization endpoint values into an RSS domain through the inverse function of the RSS cumulative distribution function to serve as endpoints for RSS quantization. The invention utilizes the accumulated distribution of the channel information intensity RSS to carry out non-uniform quantization, has lower bit mismatch rate compared with the uniform quantization and provides better basis for the subsequent information coordination step.

Description

Non-uniform quantization method in physical layer key generation process
Technical Field
The invention relates to the technical field of wireless communication and information security, in particular to a non-uniform quantization method in a physical layer key generation process.
Background
With the continuous development of communication technology, wireless communication is increasingly taking an important position in human life. Due to the openness of an electromagnetic space and the radiation of electromagnetic signal transmission, a communication signal bearing important information is completely exposed in a free space, and the standardization of a wireless communication protocol enables mobile data to be easily intercepted by an illegal user in the transmission process, so that the leakage of personal important information such as user privacy, finance and the like is possibly caused. In physical layer secure communication, a secret key can be generated and shared between two wireless nodes through measurement and coding by utilizing the reciprocity characteristic of a wireless communication time division system. Because the wireless channels are different due to the different spatial positions of the eavesdropper and the legal communicator, the key acquired by the wireless channel based on the randomness has good randomness and confidentiality. The classic process of obtaining the shared key comprises channel measurement, quantization, information reconciliation and privacy enhancement.
The existing wireless network card can measure the wireless signal strength (RSS) of each frame without any modification, so RSS is the most commonly used wireless channel characteristic parameter. However, RSS is easier to obtain data, but this parameter provides rough information of the wireless channel, and there are often problems of low bit rate of the extracted key and high bit mismatch rate.
Disclosure of Invention
In order to reduce the bit mismatch rate of a quantization part in the key generation process, the invention provides a non-uniform quantization method in the physical layer key generation process.
In order to solve the technical problems, the invention provides the following technical scheme:
a non-uniform quantization method in a physical layer key generation process, the physical layer security-based key generation process comprising the steps of:
1) and (3) channel measurement: the method comprises the following steps that a legal communication party obtains a wireless signal strength RSS value fluctuating along with time between the legal communication party and the public communication party by measuring the received signal strength of a public channel;
2) and (3) quantification: converting the measured value into a string of key bits by a non-uniform quantization method, and standardizing the RSS values obtained by respective measurement; cumulative distribution function of RSS at [0,1] thereof]Within the interval, the interval is divided by the length of 1/2, 1/4, 1/8, 1/16 …, and the end point values (0, 1/2, 3/4, 7/8, 15/16, …, 1) are mapped into the RSS domain through the inverse function of the RSS cumulative distribution function, and are used as the end points (— infinity, 0) for RSS quantization,
Figure GDA0002939509080000021
Figure GDA0002939509080000022
… and + ∞);
3) information coordination: an information reconciliation protocol is applied to discard or correct differences in key bits between the two communicating parties.
4) And (3) secret enhancement: discarding partially identical bits or performing some bit conversion to strengthen the key, increase the entropy of the key and obscure the local information that an eavesdropper may acquire in the last information reconciliation step.
Further, RSS measured by both parties of legal communication is modeled into two-dimensional Gaussian distribution with a joint probability density function of
Figure GDA0002939509080000023
Wherein R isi,μi,
Figure GDA0002939509080000031
i belongs to { A, B } and respectively represents the random variable, corresponding mean value and variance of RSS obtained by the respective measurement of Alice and Bob of both communication parties; the correlation coefficient p is used to measure the degree of channel reciprocity, and is defined as
Figure GDA0002939509080000032
According to the reciprocity theorem of the channel, the RSS measured by the two communication parties in the coherence time of the wireless channel is the same; however, inconsistency in measurements is caused by channel noise, half-duplex nature of the wireless channel, and inconsistency of the physical devices; the size of the reciprocity degree is expressed by adopting a correlation coefficient, and when rho is 0, the uplink and downlink channels are mutually independent, so that reciprocity does not exist; when ρ is 1, it indicates that the uplink and downlink channels are completely reciprocal.
Further, a bit mismatch rate closed solution during two-level uniform quantization is deduced; by deducing and combining Mathematica numerical integration calculation, a quantization method of four-level uniform quantization with the highest bit mismatch rate is indicated, and the process is as follows:
for the case of two-level quantization, Alice and Bob of the two legal communication parties use the mean value μ of the RSS received by themselves as the quantization boundary, i.e. the quantization interval is S0,i＝(-∞,μi]，S1,i＝(μi,+∞),i＝{ A, B }, quantized in (S) in a two-dimensional Cartesian coordinate system formed by the RSSs of Alice and Bob0,A,S1,B) And (S)1,A,S0,B) In the interval, the quantization bits are mismatched, and the bit mismatch rate is:
Figure GDA0002939509080000033
in the formula (I), the compound is shown in the specification,
Figure GDA0002939509080000041
where ρ is a correlation coefficient representing the reciprocity of the channels;
wherein R isNA、RNBIs RA、RBObtained after standard normal distribution processing, namely:
Figure GDA0002939509080000042
wherein R isi,μi,
Figure GDA0002939509080000043
i belongs to { A, B } and respectively represents the random variable, corresponding mean value and variance of RSS of both communication parties;
for four-level quantization, gray coding is adopted for the corresponding quantization interval, and the mismatch rate is as follows:
Figure GDA0002939509080000044
in the formula, cxAnd cyAn endpoint variable representing the division of the RSS; pr (Q)RA≠QRB) Indicating that the RSSs of Alice and Bob are quantized, the quantization bit QRA、QRBA probability of inconsistency; for variable c in formulax、cyRespectively calculating the partial derivatives, making them be 0, finishing to obtain
Figure GDA0002939509080000045
And
Figure GDA0002939509080000051
wherein the complementary error function is defined as
Figure GDA0002939509080000052
C when equations (6) and (7) are simultaneously satisfied according to symmetryx＝cyC, thus obtaining
Figure GDA0002939509080000053
Performing numerical calculation and fitting on the formula (8), wherein the fitting equation is as follows:
c＝-2.3ρ4+3.4ρ3-1.9ρ2+0.3ρ+0.66 (9)
the quantization threshold c at the highest bit mismatch rate is substantially [0.6, 0.7 ]]Quantization threshold in intra-region, but uniform quantization scheme
Figure GDA0002939509080000054
Within this interval, uniform quantization is a quantization method with the highest key mismatch rate.
Further, for the four-level non-uniform quantization, after the received RSS is normalized by Alice and Bob of the two parties of the legal communication, the key mismatch ratio is:
Figure GDA0002939509080000055
wherein
Figure GDA0002939509080000056
Through Mathematica numerical integration calculation, compared with the bit mismatch rate obtained by a uniform quantization method, the mismatch rate of the proposed non-uniform quantization method is lower than that of the uniform quantization method.
The conception of the invention is as follows: the existing wireless network card can measure the channel information strength RSS value of each frame without any modification, so that RSS is the most commonly used wireless channel characteristic parameter. However, there is a problem that although RSS is easier to obtain data, this method only provides rough information of the wireless channel, and the bit rate of the extracted key is often low, and there is a high bit mismatch rate. Modeling wireless signal strength measurement values RSS of Alice and Bob into two-dimensional Gaussian distribution with a correlation coefficient rho, wherein the correlation coefficient represents the reciprocity degree of the measurement values of the Alice and the Bob; carrying out standardization processing on RSS values obtained by respective measurement; 0,1 of RSS cumulative distribution function after processing]In the interval, non-uniform quantization is performed in the same 13-fold PCM quantization method, namely quantization is performed according to the lengths of 1/2, 1/4, 1/8 and 1/16 …, and the endpoint values (0, 1/2, 3/4, 7/8, 15/16, … and 1) are mapped into an RSS domain through an inverse function of an RSS cumulative distribution function and are used as endpoints (— ∞,0 and 1/16 …) for RSS quantization,
Figure GDA0002939509080000061
Figure GDA0002939509080000062
… and + ∞); meanwhile, Gray coding is adopted for the quantized bits, and the bit mismatch rate is reduced.
The invention has the beneficial effects that: the channel information intensity RSS cumulative distribution is used for non-uniform quantization, and compared with uniform quantization, the bit mismatch rate is lower, so that a better basis is provided for the subsequent information coordination step.
Drawings
FIG. 1 is a diagram of four-level arbitrary quantization
FIG. 2 is a graph of four-level quantization threshold versus bit mismatch rate
FIG. 3 is a diagram illustrating quantization intervals corresponding to a four-level non-uniform quantization scheme
FIG. 4 is a diagram illustrating the relationship between different quantization methods and the correlation coefficient ρ
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1 to 4, a non-uniform quantization method in a physical layer key generation process includes the following steps:
1) and (3) channel measurement: the method comprises the following steps that two legal communication parties (called Alice and Bob) measure the received signal strength of a public channel so as to obtain an RSS value fluctuating along with time between the two parties;
2) and (3) quantification: converting the measured value into a string of key bits by a quantization method;
3) information coordination: although a signal preprocessing algorithm can be used to improve the cross-correlation of the channel measurements, there are still inconsistent key bits between Alice and Bob after quantization, i.e., there is a bit mismatch rate. Information reconciliation techniques can be used to correct for differences in the key bits generated at both ends;
4) and (3) secret enhancement: discarding partially identical bits or performing some bit conversion to strengthen the key, increase the entropy of the key and obscure the local information that an eavesdropper may acquire in the last information reconciliation step.
The quantization process in step 2), i.e. a non-uniform quantization method is proposed to reduce the bit mismatch rate between the two parties of the legal communication.
In the quantization process, the random process theory indicates that: given a cumulative distribution function of FX(x) The random variable X of (a), the constructor g (X) FX(x) So that the random variable Y ═ g (X) obeys [0,1 ═ g%]Uniformly distributed, i.e. Y ═ FX(X) to U (0, 1). Based on this, the uniform quantization method is: assuming a cumulative distribution function F of the RSSX(x) Known as in [0,1]]The upper equal interval is divided into M intervals, the end point for uniformly quantizing the received RSS is
Figure GDA0002939509080000071
Here, the
Figure GDA0002939509080000072
Is the inverse of the cumulative distribution function; RSS is modeled as a Gaussian distribution, so the constructor is
Figure GDA0002939509080000081
Wherein the error functions are complementary
Figure GDA0002939509080000082
RSS (in dB) for Alice and Bob is modeled as a normal distribution, i.e.
Figure GDA0002939509080000083
The RSS of the uplink and downlink channels has reciprocity, is modeled as two-dimensional Gaussian distribution, and has a joint probability density function of
Figure GDA0002939509080000084
Wherein R isi,μi,
Figure GDA0002939509080000085
i belongs to { A, B } and respectively represents the random variable, corresponding mean value and variance of RSS obtained by the respective measurement of Alice and Bob of both communication parties; the correlation coefficient rho is used for measuring the reciprocal degree of the channel, and is defined as
Figure GDA0002939509080000086
Wherein E [ X ] represents the desired operation on a random variable X;
here mui,
Figure GDA0002939509080000087
i ∈ { A, B } represents the mean and variance of received RSSs for Alice and Bob, respectively. According to the channel reciprocity theorem, the uplink and downlink channel measurements of the wireless link should be the same; however, due to channel noise, wireless communicationThe measured values are inconsistent due to factors such as the half-duplex property of the channel and the inconsistency of physical devices, so that the problem of quantization bit mismatch rate exists. Herein, the magnitude of the reciprocity degree is expressed using the correlation coefficient ρ; obviously, when ρ ═ 0 indicates that the uplink and downlink channels are independent of each other, reciprocity does not exist; when ρ is 1, it indicates that the uplink and downlink channels are completely reciprocal.
For the case of two-level quantization, Alice and Bob use the mean μ of the RSS received by themselves as the quantization boundary, i.e., the quantization interval is S0,i＝(-∞,μi],S1,i＝(μiAnd +∞) i ═ a, B }. In a two-dimensional Cartesian coordinate system formed by the RSSs of Alice and Bob, the quantization is in (S)0,A,S1,B) And (S)1,A,S0,B) In the interval, the quantization bits are mismatched, and the probability of mismatch is;
Figure GDA0002939509080000091
in the formula (I), the compound is shown in the specification,
Figure GDA0002939509080000092
where ρ is a correlation coefficient representing the reciprocity of the channels;
wherein R isNA、RNBIs RA、RBObtained after standard normal distribution processing, namely:
Figure GDA0002939509080000093
wherein R isi,μi,
Figure GDA0002939509080000094
And i epsilon { A, B } respectively represents a random variable, a corresponding mean value and a variance of RSS of two communication parties.
The bit mismatch rate for two-level quantization is therefore:
Figure GDA0002939509080000095
in the present implementation method, in the quantization process, referring to fig. 1, a relationship between a quantization endpoint and a mismatch ratio is derived by taking four-level quantization as an example. The quantization coding is assumed to be gray coding, i.e. adjacent regions differ by one bit. The corresponding quantization intervals are encoded as "00", "01", "11", and "10". R in FIG. 1NAAnd RNBThe standard treatment is carried out by the formula (5).
If R isNA∈(-∞,-cx) And the interval, the Alice code is '00'. At this time, let R beNB∈(-cy0), Bob encodes "01". Alice and Bob only have one quantization bit different from each other, and their corresponding probabilities are half of the integral of the joint probability density function of Alice and Bob over the interval, it can be relatively intuitively obtained with reference to fig. 1 that the bit mismatch rate of the four-level quantization is:
Figure GDA0002939509080000101
for any correlation coefficient rho, the value range of the quantization threshold c is set as [0, 3] (for Gaussian distribution, most values of random variables fall in the interval), then an equation (7) is substituted, and numerical integration is performed through Mathemica software to obtain a relationship curve between the quantization threshold and the mismatch rate under a cluster of different correlation coefficients as shown in FIG. 2. As can be seen with reference to fig. 2, as the quantization threshold c increases, the bit mismatch rate increases. When c is a certain value, the bit mismatch rate is maximum and then decreases.
For equation (7), the key mismatch ratio is given to the variable cx,cyThe partial derivatives were calculated and made to be 0. After finishing, obtaining
Figure GDA0002939509080000111
And
Figure GDA0002939509080000112
from the symmetry, if equations (8) and (9) hold at the same time, cx＝cyC, thus obtaining
Figure GDA0002939509080000113
Numerically calculating and fitting the formula (10), wherein the fitting equation is as follows:
c＝-2.3ρ4+3.4ρ3-1.9ρ2+0.3ρ+0.66 (9)
with reference to fig. 2, equation (11) represents the quantization threshold c at the maximum bit mismatch rate for different correlation coefficients. Especially when the correlation coefficient is relatively small, the quantization threshold value is basically 0.6, 0.7 when the mismatch ratio is maximum]Quantization threshold in intra-region, but uniform quantization scheme
Figure GDA0002939509080000114
Figure GDA0002939509080000115
Falling within this interval, uniform quantization is a quantization method with the largest bit mismatch rate.
Inspired by 13 broken line non-uniform quantization in the communication principle, when the RSS amplitude is small, the RSS is easily affected by channel noise, inconsistency of elements of a transmitter and a receiver, and the like, bits after quantization are unreliable, and a quantization interval is larger; on the contrary, when the RSS amplitude is large, the anti-interference capability is strong, the matching rate of the quantized bits is high, and the quantization interval can be small. Based on this, in order to improve the matching rate and the generation rate of bits, a non-uniform quantization method is proposed. After Alice and Bob normalize the received RSS, the quantization interval is divided as shown in FIG. 3, where
Figure GDA0002939509080000121
Figure GDA0002939509080000122
Referring to fig. 3, the bit mismatch ratio is:
Figure GDA0002939509080000123
wherein
Figure GDA0002939509080000124
The result of numerical integration of the bit mismatch rate at four-level quantization was calculated by Mathematica, as shown in fig. 4. As can be seen from fig. 4, the proposed non-uniform quantization method has a lower bit mismatch rate than the uniform quantization method with the same correlation coefficient.

Claims (4)

1. A non-uniform quantization method in a physical layer key generation process is characterized in that: the non-uniform quantization method includes the steps of:
1) and (3) channel measurement: the method comprises the following steps that a legal communication party obtains a wireless signal strength RSS value fluctuating along with time between the legal communication party and the public communication party by measuring the received signal strength of a public channel;
2) and (3) quantification: converting the measured value into a string of key bits by a non-uniform quantization method, and standardizing the RSS values obtained by respective measurement; cumulative distribution function of RSS at [0,1] thereof]Within the interval, the interval is divided by the length of 1/2, 1/4, 1/8, 1/16 …, and the end point values (0, 1/2, 3/4, 7/8, 15/16, …, 1) are mapped into the RSS domain through the inverse function of the RSS cumulative distribution function, and are used as the end points (— infinity, 0) for RSS quantization,
Figure FDA0002939509070000011
Figure FDA0002939509070000012
… and + ∞);
3) information coordination: applying an information reconciliation protocol to discard or correct the difference of the key bits between the two parties;
4) and (3) secret enhancement: discarding partially identical bits or performing some bit conversion to strengthen the key, increase the entropy of the key and obscure the local information that an eavesdropper may acquire in the last information reconciliation step.
2. A method of non-uniform quantization in a physical layer key generation process as claimed in claim 1, wherein: modeling RSS measured by both parties of legal communication into two-dimensional Gaussian distribution with joint probability density function of
Figure FDA0002939509070000013
Wherein R isi,μi,
Figure FDA0002939509070000014
i belongs to { A, B } and respectively represents the random variable, corresponding mean value and variance of RSS obtained by the respective measurement of Alice and Bob of both communication parties; the correlation coefficient p is used to measure the degree of channel reciprocity, and is defined as
Figure FDA0002939509070000021
Wherein E [ X ] represents the desired operation on a random variable X;
according to the reciprocity theorem of the channel, the RSS measured by the two communication parties in the coherence time of the wireless channel is the same; however, inconsistency in measurements is caused by channel noise, half-duplex nature of the wireless channel, and inconsistency of the physical devices; the size of the reciprocity degree is expressed by adopting a correlation coefficient, and when rho is 0, the uplink and downlink channels are mutually independent, so that reciprocity does not exist; when ρ is 1, it indicates that the uplink and downlink channels are completely reciprocal.
3. A method of non-uniform quantization in a physical layer key generation process as claimed in claim 2, characterized by: deducing a bit mismatch rate closed solution during two-level uniform quantization; by deducing and combining Mathematica numerical integration calculation, a quantization method of four-level uniform quantization with the highest bit mismatch rate is indicated, and the process is as follows:
for the case of two-level quantization, Alice and Bob of the two legal communication parties use the mean value μ of the RSS received by themselves as the quantization boundary, i.e. the quantization interval is S0,i＝(-∞,μi]，S1,i＝(μi, + ∞), i ═ a, B, in a two-dimensional cartesian coordinate system formed by the RSS of Alice and Bob, quantized in (S)0,A,S1,B) And (S)1,A,S0,B) In the interval, the quantization bits are mismatched, and the bit mismatch rate is:
Figure FDA0002939509070000022
in the formula (I), the compound is shown in the specification,
Figure FDA0002939509070000031
where ρ is a correlation coefficient representing the reciprocity of the channels;
wherein R isNA、RNBIs RA、RBObtained after standard normal distribution processing, namely:
Figure FDA0002939509070000032
wherein R isi,μi,
Figure FDA0002939509070000033
i belongs to { A, B } and respectively represents the random variable, corresponding mean value and variance of RSS of both communication parties;
for four-level quantization, gray coding is adopted for the corresponding quantization interval, and the mismatch rate is as follows:
Figure FDA0002939509070000034
in the formula, cxAnd cyAn endpoint variable representing the division of the RSS; pr (Q)RA≠QRB) Indicating that the RSSs of Alice and Bob are quantized, the quantization bit QRA、QRBA probability of inconsistency;
for variable c in formulax、cyRespectively calculating the partial derivatives, making them be 0, finishing to obtain
Figure FDA0002939509070000035
And
Figure FDA0002939509070000041
wherein the complementary error function is defined as
Figure FDA0002939509070000042
C when equations (6) and (7) are simultaneously satisfied according to symmetryx＝cyC, thus obtaining
Figure FDA0002939509070000043
Performing numerical calculation and fitting on the formula (8), wherein the fitting equation is as follows:
c＝-2.3ρ4+3.4ρ3-1.9ρ2+0.3ρ+0.66 (9)
the quantization threshold c at the highest bit mismatch rate is substantially [0.6, 0.7 ]]Quantization threshold in intra-region, but uniform quantization scheme
Figure FDA0002939509070000044
Within this interval, uniform quantization is a quantization method with the highest key mismatch rate.
4. A method of non-uniform quantization in a physical layer key generation process as claimed in claim 3, wherein: for the four-level non-uniform quantization, after the received RSS is normalized by Alice and Bob of the two legal communication parties, the key mismatch rate is:
Figure FDA0002939509070000045
wherein the content of the first and second substances,
Figure FDA0002939509070000046
through Mathematica numerical integration calculation, compared with the bit mismatch rate obtained by a uniform quantization method, the mismatch rate of the proposed non-uniform quantization method is lower than that of the uniform quantization method.
CN201910046556.7A 2019-01-18 2019-01-18 Non-uniform quantization method in physical layer key generation process Active CN109787757B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910046556.7A CN109787757B (en) 2019-01-18 2019-01-18 Non-uniform quantization method in physical layer key generation process

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910046556.7A CN109787757B (en) 2019-01-18 2019-01-18 Non-uniform quantization method in physical layer key generation process

Publications (2)

Publication Number Publication Date
CN109787757A CN109787757A (en) 2019-05-21
CN109787757B true CN109787757B (en) 2021-07-13

Family

ID=66501630

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910046556.7A Active CN109787757B (en) 2019-01-18 2019-01-18 Non-uniform quantization method in physical layer key generation process

Country Status (1)

Country Link
CN (1) CN109787757B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112104459B (en) * 2020-09-10 2023-05-12 国网江苏省电力有限公司信息通信分公司 Key generation method based on channel fingerprint and auxiliary data

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105282739A (en) * 2015-11-13 2016-01-27 西安交通大学 Point-to-point secret key negotiation method based on physical layer pilot frequency presetting
CN106027242A (en) * 2016-07-08 2016-10-12 东南大学 Wireless channel characteristic stepwise quantification method based on unitary transformation preprocessing
CN108768443A (en) * 2018-05-30 2018-11-06 中国人民解放军战略支援部队信息工程大学 Spread spectrum parameter agile method based on random signal
WO2018211675A1 (en) * 2017-05-18 2018-11-22 Nec Corporation Bit decomposition secure computation apparatus, bit combining secure computation apparatus, method and program

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105282739A (en) * 2015-11-13 2016-01-27 西安交通大学 Point-to-point secret key negotiation method based on physical layer pilot frequency presetting
CN106027242A (en) * 2016-07-08 2016-10-12 东南大学 Wireless channel characteristic stepwise quantification method based on unitary transformation preprocessing
WO2018211675A1 (en) * 2017-05-18 2018-11-22 Nec Corporation Bit decomposition secure computation apparatus, bit combining secure computation apparatus, method and program
CN108768443A (en) * 2018-05-30 2018-11-06 中国人民解放军战略支援部队信息工程大学 Spread spectrum parameter agile method based on random signal

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
《Efficient key generation leveraging channel reciprocity and balanced gray code》;Furui Zhan等;《Wireless Netw》;20170901;全文 *
《Fast and Practical Secret Key Extraction by Exploiting Channel Response》;Hongbo Liu等;《IEEE》;20130725;全文 *
《无线信道密钥生成方法研究》;宋晓青;《中国优秀硕士学位论文全文数据库信息科技辑》;20180415;全文 *
《物理层安全中无线信号强度的非均匀量化方案》;徐志江等;《高技术通讯》;20200515;全文 *
王晓敏.《 基于无线信道物理层特性的密钥生成方法的研究》.《中国优秀硕士学位论文全文数据库信息科技辑》.2020,全文. *

Also Published As

Publication number Publication date
CN109787757A (en) 2019-05-21

Similar Documents

Publication Publication Date Title
Ren et al. Secret key generation exploiting channel characteristics in wireless communications
Zhan et al. On the using of discrete wavelet transform for physical layer key generation
CN104901795A (en) Physical layer key extraction method based on channel characteristic
CN106102055B (en) Wireless channel key generation method based on feature distribution transformation
CN105792198B (en) Bioaugnentation wireless channel key generation method towards wireless body area network
CN104270240B (en) The Information hiding communication means and its device of multi-carrier modulation
US8483387B2 (en) Method for generating private keys in wireless networks
CN113395157B (en) Physical layer key extraction method based on quantization protection band
CN109787757B (en) Non-uniform quantization method in physical layer key generation process
Zhan et al. Efficient key generation leveraging wireless channel reciprocity for MANETs
Adil et al. On quantization for secret key generation from wireless channel samples
US9002011B2 (en) Method for generating consistent cryptographic key based on wireless channel features
Kipnis et al. Mean estimation from one-bit measurements
Treust et al. Strategic communication with side information at the decoder
CN109067501B (en) Polar code communication method and device based on degraded wiretap channel noise interference
Cheng et al. Towards an effective secret key generation scheme for imperfect channel state information
CN108683500B (en) WBAN privacy protection method based on channel characteristics
Keming et al. Research on Physical Layer Key Generation Based on Wireless Channel Characteristics in New Power System
Soni et al. Performance improvement of wireless secret key generation with colored noise for IoT
Badawy et al. Secret key generation based on channel and distance measurements
Chen et al. Improved channel quantization for secret key establishment in wireless systems
CN111065098B (en) Key generation method and system under fast frequency hopping communication system
CN114389805A (en) Post-processing method of CV-QKD based on Gaussian modulation coherent state
Kipnis et al. Mean estimation from adaptive one-bit measurements
CN114430550B (en) Wireless physical layer key generation method based on neural network model

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