CN102291713A - Method for reducing influence of master user simulation attack - Google Patents
Method for reducing influence of master user simulation attack Download PDFInfo
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- CN102291713A CN102291713A CN2011102421232A CN201110242123A CN102291713A CN 102291713 A CN102291713 A CN 102291713A CN 2011102421232 A CN2011102421232 A CN 2011102421232A CN 201110242123 A CN201110242123 A CN 201110242123A CN 102291713 A CN102291713 A CN 102291713A
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Abstract
The invention relates to a method for reducing influence of master user simulation attack. According to the invention, in the method, cognitive radio users relatively disperse in space are selected to participate in cooperation spectrum sensing, and the detection method of MME (mobility management entity) is used to reduce influence of the undetected master user simulation attack on the cooperation spectrum sensing. The method comprises the following concrete steps: establishing a location correlation matrix among the cognitive radio users according to a shadow fading correlation model; selecting the cognitive radio users with relatively low location correlation to participate in the cooperation sensing; and finally making an overall decision by a fusion center through a detection method based on the maximum and minimum characteristic values of a sampled signal covariance matrix. The method has the advantages that the prior information of the master user does not need to be obtained and the background noise power is unnecessary to know, and has relatively high robustness on the uncertainty of noise.
Description
Technical field
Patent of the present invention belongs to the cognitive radio security fields, relates to a kind ofly under relevant shadow fading and main user's associated transmissions signal, alleviates omission master subscriber simulation and attacks method to cooperation frequency spectrum perception performance impact.
Background technology
Cognitive radio (Cognitive Radio) technology can effectively be utilized frequency spectrum resource, alleviate rare and the situation that the availability of frequency spectrum is low of current frequency spectrum resource, it makes the operating position of the perception surrounding environment intermediate frequency spectrum resource that the radio subscriber possess cognitive function can intelligence, and find not by " frequency spectrum cavity-pocket " of main user (Primary User) use, under the prerequisite that does not influence main telex network, insert these " frequency spectrum cavity-pockets " in the mode of waiting for an opportunity and finish communication.
Cognitive radio technology is when striving for the efficient utilization of frequency spectrum resource, a lot of distinctive security threats have also been introduced, main subscriber simulation such as physical layer is attacked, even the perception frequency band is not by main CU, but because main subscriber simulation assailant is by having high degree of flexibility, realizing that based on software air interface simulated main customer signal characteristic sends signal, make cognitive radio users perceive stronger main subscriber signal, its sensing results will be made frequency band by the judgement of main CU so, thereby reduce the availability of frequency spectrum.
Based on the frequency spectrum detection technology of energy have realize simple, main subscriber signal is needed the minimum characteristics of prior information, under independent same distribution signal scene, have a wide range of applications; But energy measuring can't be distinguished main subscriber signal and noise, detects poor-performing when signal to noise ratio is relatively lower, and influenced or the like by the uncertainty of ambient noise.By increasing the performance that sampling number can improve energy measuring to a certain extent, but sampling signal to noise ratio (Signal-to-Noise Ratio as the user, SNR) reach certain thresholding, be also referred to as SNR Wall, increase sampling number in any case and also can not detect main subscriber signal; Exactly because the development of cooperation frequency spectrum cognition technology has just been facilitated in this circumscribed existence of energy measuring.
The cooperation frequency spectrum perception is adopted energy measuring to carry out frequency spectrum perception by a plurality of cognitive radio users cooperations to improve perceptual performance, reducing single uncertainty from user's sensing results, thereby reaches better perceptual performance.Yet in the perception of energy measuring cooperation frequency spectrum, main subscriber simulation assailant understands the simulated main customer signal characteristic and transmits, make that the close cognitive user of distance is identical with the energy that receives from main user transmitter from the energy that the assailant receives, thereby reach the purpose of attacking a plurality of cognitive radio users.Therefore these may can not be improved the performance of whole cooperation frequency spectrum perception by the sensing results of the cognitive radio users of omission master subscriber simulation assailant attack.
In addition, in most of practical application scenes, the reception sampled signal of single cognitive radio users has more intense autocorrelation; Because the position correlation of shadow fading has more intense cross correlation between the reception sampled signal of a plurality of cognitive radio users, therefore, it is not optimum adopting energy detection method simultaneously.And based on receiving sampled signal covariance matrix maximum, minimal eigenvalue (Maximum-minimum eigenvalue, MME) detection method is owing to have same advantage with energy detection technique, and to insensitive for noise, be fit to detect coherent signal, application scenarios is more widely arranged.
Summary of the invention
The present invention is directed under the actual scene of relevant shadow fading in position and associated transmissions signal, the partner user that proposes a kind of position-based correlation is selected and is received the detection method of sampled signal covariance maximum, minimal eigenvalue based on partner user, alleviates omission master subscriber simulation and attacks purpose to cooperation frequency spectrum perception Effect on Performance to reach.The present invention participates in the cooperation frequency spectrum perception by the cognitive radio users of disperseing relatively on the described method selection space, and adopts the detection method of MME to reduce the attack of omission master subscriber simulation to cooperation frequency spectrum perception Effect on Performance.
Among the present invention, cognitive radio users independent sample target frequency bands obtains local sensing results, the data fusion center is collected the local sensing results of each cognitive radio users and these sensing results is merged, and make the judgement whether main user takies frequency spectrum according to fusion results, obtain the court verdict of cooperative sensing.Data fusion center and each cognitive radio users are carried out interacting message by control channel, cognitive radio users utilizes control channel to send local sensing results and related control information mutually, and the data fusion center utilizes control channel to select the cooperative sensing user, sends the court verdict of cooperative sensing and related control information mutually.
Among the present invention, traditional dualism hypothesis model is adopted at the data fusion center,
H 0Represent the current target frequency bands that detects not by the hypothesis of main CU,
H 1Be expressed as the hypothesis that the current target frequency bands that detects is being used by main user.The data fusion center is to the judgement of frequency spectrum operating position, judges exactly currently to be
H 0Suppose to set up still
H 1Suppose to set up.Eigenvalue of maximum Distribution Theorem and minimal eigenvalue thresholding theorem based on Random Matrices Theory are adopted to the judgement of frequency spectrum operating position in the data fusion center, under fixing false alarm probability, obtain the optimal judgement thresholding.
Patent of the present invention is according to the position correlation matrix between the shadow fading correlation models structure cognitive radio users, the less cognitive radio users of chosen position correlation participates in cooperative sensing then, and last fusion center adopts based on the detection method that receives sampled signal covariance matrix maximum, minimal eigenvalue and makes whole judgement.Described shadow fading correlation models is meant in cognitive radio networks, because part cognitive user position distance is closer, on locational space, be subjected to blocking of identical barrier easily, the shadow fading that the local perception of each cognitive radio users is experienced is no longer separate, the shadow fading correlation that adjacent cognitive radio users experienced is presented as exponential form, promptly
Wherein,
dRepresent two distances between the cognitive radio users,
φBe the expression specific wireless communication environments envirment factor of expression shade degree of correlation down, generally, in suburban environment
φ ≈0.002, in urban environment
φ ≈0.1204.
The concrete steps of the inventive method are:
Step 1: in perception, each cognitive radio users is carried out independent sample to target frequency bands in the cognitive radio networks, obtains local sensing results
X j , as follows
Wherein
jExpression the
jIndividual cognitive radio users,
Represent in perception
jIndividual cognitive radio users is
iNoise during inferior the sampling,
Represent in perception
jIndividual cognitive radio users
iThe main subscriber signal that inferior sampling obtains,
NThe expression cognitive radio users is carried out the needed sampling number of perception.Wherein 1≤
j≤
J, 1≤
i≤
N(
JThe number of cognitive radio users in the expression cognitive radio networks).
Step 2: the data fusion center is according to the position of each cognitive radio users and the envirment factor of shade degree of correlation
φ, make up correlation matrix, select to participate in the cognitive radio users of cooperation then according to the position correlation selection algorithm.The general selection
J/ 2≤
M<
J(
MThe cognitive radio users number of expression actual participation cooperation frequency spectrum perception).Wherein, the system of selection of position-based correlation selects the concrete steps of partner user as follows:
A) initialization cooperation frequency spectrum perception user number
j=
J
B) relatively
jWith
M, if
j≤
M, forward step g to; If
j=
M + 1, forward step e to;
C) from correlation matrix, remove two cognitive radio users of position correlation maximum, and make
j=
j-2;
D) relatively
jWith
M, if
j=
M, forward step g to;
j M+ 1, to step c;
E) from correlation matrix, find two cognitive radio users of position correlation maximum, be designated as CR respectively
m And CR
n , calculate CR
m , CR
n With other
jPosition correlation sum between the cognitive radio users of-2 participation cooperations is designated as respectively
ρ m With
ρ n
F) relatively
ρ m With
ρ n , if
ρ m ρ n , remove cognitive no electric user CR
m , and order
j=
j-1; Otherwise remove cognitive radio users CR
n , and order
j=
j-1;
G) select to finish.
Step 3: according to system's false alarm probability of cognitive radio networks requirement
P Fa With the Random Matrices Theory relevant knowledge,
H 0Suppose down, by
P Fa =P (
λ Max γ λ Min) can get the cognitive radio system decision threshold
γFor:
Wherein
F 1Be single order Tracy-Widom cumulative distribution function,
The inverse function of expression single order Tracy-Widom cumulative distribution function,
LIt is the smoothing parameter that the data fusion center is selected.
Step 4: the data fusion center participates in cooperating by the control channel request
MIndividual cognitive radio users sends its local sensing results, obtains the perception vector
The data fusion center is according to smoothing parameter then
L, make up the cooperative sensing smoothing matrix
The data fusion center makes up the covariance matrix that receives sampled signal according to the cooperative sensing smoothing matrix
Step 5: covariance matrix is tried to achieve at the data fusion center
Maximum, minimal eigenvalue be respectively:
λ MaxWith
λ Min, and with the decision threshold of system
γRelatively make judgement: if
λ Max/
λ Min γ, then adjudicate this frequency range just occupied, cognitive radio users can not be communicated by letter with this frequency range; Otherwise adjudicating this frequency range does not have occupiedly, and cognitive radio users can be communicated by letter with this frequency range.
The advantage of patent of the present invention is:
1. the present invention need not obtain main user's prior information, also need not Background Noise Power, and the uncertainty of noise is had stronger robustness.
2. the present invention adopts the cognitive wireless radio cooperation user choosing method of position-based correlation, and a cognitive radio users that the chosen position correlation is less participates in cooperative sensing,
H 1Suppose down, alleviated the shadow fading correlation the detection Effect on Performance,
H 0Suppose down, alleviated the influence that omission master subscriber simulation is attacked.Simultaneously, also reduced based on the part communication overhead in the perception of Random Matrices Theory cooperation frequency spectrum.
Description of drawings
Fig. 1 is the cognitive radio networks schematic diagram;
Fig. 2 is whole cooperative sensing flow chart;
Fig. 3 is the partner user system of selection flow chart of position-based correlation;
Fig. 4 is a MME detection method flow chart.
Embodiment
Below in conjunction with accompanying drawing, further specify the present invention and alleviate the specific implementation process of omission master subscriber simulation attack cooperation frequency spectrum perception performance impact method.
As Fig. 1, cognitive radio networks by a data fusion center, main subscriber simulation assailant and
JIndividual cognitive radio users constitutes.What main user transmitter was launched is coherent signal.In addition, owing to there is identical barrier etc. to block, the signal that cognitive radio users receives has position correlation.And main subscriber simulation is attacked and is attacked cognitive radio users as much as possible with the energy of minimum, makes energy that cognitive radio users obtains from main subscriber simulation assailant and equates from the energy that main user obtains.Main subscriber simulation attack can also simulated main customer other features.Carry out information interaction by control channel between data fusion center and each cognitive radio users.
As Fig. 2, whole cognitive wireless radio cooperation perception comprises following step:
(a) cognitive radio users
j(
j=1,2 ...,
J) carry out local perception, the independent sample target frequency bands obtains local sensing results
X j
Wherein
jExpression the
jIndividual cognitive radio users,
Represent in perception
jIndividual cognitive radio users is
iNoise during inferior the sampling,
Represent in perception
jIndividual cognitive radio users
iThe main subscriber signal that inferior sampling obtains,
NThe expression cognitive radio users is carried out the needed sampling number of perception.Wherein 1≤
j≤
J, 1≤
i≤
N(
JThe number of cognitive radio users in the expression cognitive radio networks).
(b) cognitive radio networks merges control centre's employing position correlation partner user system of selection, selects
M(
J/ 2≤
M<
J) cognitive radio users of individual actual participation cooperation;
(c) data fusion center requests
MThe cognitive radio users of individual selected participation cooperative sensing sends its local sensing results to the data fusion center;
(d) the MME detection method is adopted according to the local sensing results of the partner user of receiving in the data fusion center, makes the total system judgement, and court verdict is broadcast to each cognitive radio users.
As Fig. 3, the partner user of position-based correlation is selected flow process, at first according to the empirical function formula (1) of relevant shadow fading, positional information with each cognitive radio users, make up the position correlation matrix between the cognitive radio users, the selection of partner user specifically comprises following step then:
(a) initialization cooperation frequency spectrum perception user number
j=
J
(b) relatively
jWith
M, if
j≤
M, forward step g to; If
j=
M + 1, forward step e to;
(c) from correlation matrix, remove two cognitive radio users of position correlation maximum, and make
j=
j-2;
(d) relatively
jWith
M, if
j=
M, forward step g to;
j M+ 1, to step c;
(e) from correlation matrix, find two cognitive radio users of position correlation maximum, be designated as CR respectively
m And CR
n , calculate CR
m , CR
n With other
jPosition correlation sum between the cognitive radio users of-2 participation cooperations is designated as respectively
ρ m With
ρ n
(f) relatively
ρ m With
ρ n , if
ρ m ρ n , remove cognitive no electric user CR
m , and order
j=
j-1; Otherwise remove cognitive radio users CR
n , and order
j=
j-1;
(g) select to finish.
As Fig. 4, MME detection method flow chart, concrete steps are as follows:
(a) the data fusion center is according to the false alarm probability of cognitive radio networks system
P Fa And the random matrix correlation theory, try to achieve the whole decision threshold of cognitive radio networks
γFor
,
Wherein
F 1Be single order Tracy-Widom cumulative distribution function,
LBe the smoothing parameter that the data fusion center is selected,
MBe the user's number that participates in the cooperation frequency spectrum perception,
NIt is the sampling number of a perception;
(b) the data fusion center is according to the local sensing results of the perception of partner user that receives, and smoothing parameter
L, make up smoothly vector of cooperative sensing
,
Wherein
iThe of a perception of expression
iInferior sampling;
(c) the data fusion center is smoothly vectorial according to cooperative sensing
, obtain perception
NThe covariance matrix of inferior sampled signal
,
Wherein represent conjugate transpose;
(d) covariance matrix is tried to achieve at the data fusion center
Maximum, minimal eigenvalue, be respectively:
λ MaxWith
λ Min, and according to the decision threshold of system
γMake judgement: if
λ Max/
λ Min γ, then adjudicate this frequency range just occupied; Otherwise adjudicating this frequency range does not have occupied.And the broadcasting court verdict is given each cognitive radio users.
Claims (1)
1. extenuate the method that main subscriber simulation is attacked influence for one kind, it is characterized in that this method may further comprise the steps:
Step 1. is in perception, and each cognitive radio users is carried out independent sample to target frequency bands in the cognitive radio networks, obtains local sensing results
X j , as follows
Wherein
jExpression the
jIndividual cognitive radio users,
Represent in perception
jIndividual cognitive radio users is
iNoise during inferior the sampling,
Represent in perception
jIndividual cognitive radio users
iThe main subscriber signal that inferior sampling obtains,
NThe expression cognitive radio users is carried out the needed sampling number of perception; Wherein 1≤
j≤
J, 1≤
i≤
N,
JThe number of cognitive radio users in the expression cognitive radio networks;
Step 2. data fusion center is according to the position of each cognitive radio users and the envirment factor of shade degree of correlation
φ, make up correlation matrix, select to participate in the cognitive radio users of cooperation then according to the position correlation selection algorithm, position-based correlation selection algorithm selects the concrete steps of partner user as follows:
A) initialization cooperation frequency spectrum perception user number
j=
J
B) relatively
jWith
M, if
j≤
M, forward step g to; If
j=
M+ 1, forward step e to;
C) from correlation matrix, remove two cognitive radio users of position correlation maximum, and make
j=
j-2;
D) relatively
jWith
M, if
j=
M, forward step g to;
j M+ 1, to step c;
E) from correlation matrix, find two cognitive radio users of position correlation maximum, be designated as CR respectively
m And CR
n , calculate CR
m , CR
n With other
jPosition correlation sum between the cognitive radio users of-2 participation cooperations is designated as respectively
ρ m With
ρ n
F) relatively
ρ m With
ρ n , if
ρ m ρ n , remove cognitive no electric user CR
m , and order
j=
j-1; Otherwise remove cognitive radio users CR
n , and order
j=
j-1;
G) select to finish;
System's false alarm probability that step 3. requires according to cognitive radio networks
P Fa With the Random Matrices Theory relevant knowledge,
H 0Suppose down, by
P Fa =P (
λ Max γ λ Min) can get the cognitive radio system decision threshold
γFor:
Wherein
F 1Be single order Tracy-Widom cumulative distribution function,
The inverse function of expression single order Tracy-Widom cumulative distribution function,
LIt is the smoothing parameter that the data fusion center is selected;
Step 4. data fusion center participates in cooperating by the control channel request
MIndividual cognitive radio users sends its local sensing results, obtains the perception vector
The data fusion center is according to smoothing parameter then
L, make up the cooperative sensing smoothing matrix
,
The data fusion center makes up the covariance matrix that receives sampled signal according to the cooperative sensing smoothing matrix
Covariance matrix is tried to achieve at step 5. data fusion center
Maximum, minimal eigenvalue be respectively:
λ MaxWith
λ Min, and with the decision threshold of system
γRelatively make judgement: if
λ Max/
λ Min γ, then adjudicate this frequency range just occupied, cognitive radio users can not be communicated by letter with this frequency range; Otherwise adjudicating this frequency range does not have occupiedly, and cognitive radio users can be communicated by letter with this frequency range.
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Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
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CN103781089A (en) * | 2014-01-27 | 2014-05-07 | 苏州大学 | Method for selecting cognitive users in coordinated spectrum sensing |
CN103916859A (en) * | 2014-03-17 | 2014-07-09 | 上海交通大学 | Detection method for cognizing users maliciously occupying channels in wireless network |
CN105554739A (en) * | 2015-12-08 | 2016-05-04 | 浙江大学 | Primary user emulation attack detection method based on channel multipath delay differences |
CN112260779A (en) * | 2020-09-25 | 2021-01-22 | 广东电网有限责任公司江门供电局 | Signal detection method for small mobile master user |
CN115085833A (en) * | 2022-06-14 | 2022-09-20 | 重庆大学 | Multi-antenna-oriented two-step cooperative narrowband spectrum detection method |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1882158A (en) * | 2006-05-11 | 2006-12-20 | 电子科技大学 | Realization method for mixed network structure in cognitive radio |
CN101257698A (en) * | 2007-02-28 | 2008-09-03 | 华为技术有限公司 | Method for sensing multi-channel, cognition radio system, base station as well as user terminal |
-
2011
- 2011-08-23 CN CN201110242123.2A patent/CN102291713B/en not_active Expired - Fee Related
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1882158A (en) * | 2006-05-11 | 2006-12-20 | 电子科技大学 | Realization method for mixed network structure in cognitive radio |
CN101257698A (en) * | 2007-02-28 | 2008-09-03 | 华为技术有限公司 | Method for sensing multi-channel, cognition radio system, base station as well as user terminal |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
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CN103781089A (en) * | 2014-01-27 | 2014-05-07 | 苏州大学 | Method for selecting cognitive users in coordinated spectrum sensing |
CN103781089B (en) * | 2014-01-27 | 2016-08-24 | 苏州大学 | The system of selection of cognitive user in a kind of cooperation spectrum perception |
CN103916859A (en) * | 2014-03-17 | 2014-07-09 | 上海交通大学 | Detection method for cognizing users maliciously occupying channels in wireless network |
CN103916859B (en) * | 2014-03-17 | 2017-06-13 | 上海交通大学 | The detection method of cognition wireless network malice busy channel user |
CN105554739A (en) * | 2015-12-08 | 2016-05-04 | 浙江大学 | Primary user emulation attack detection method based on channel multipath delay differences |
CN105554739B (en) * | 2015-12-08 | 2018-09-28 | 浙江大学 | Primary user based on channel multi-path delay inequality emulates attack detection method |
CN112260779A (en) * | 2020-09-25 | 2021-01-22 | 广东电网有限责任公司江门供电局 | Signal detection method for small mobile master user |
CN115085833A (en) * | 2022-06-14 | 2022-09-20 | 重庆大学 | Multi-antenna-oriented two-step cooperative narrowband spectrum detection method |
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