CN115052291B - Method for resisting malicious intelligent reflecting surface interference attack - Google Patents
Method for resisting malicious intelligent reflecting surface interference attack Download PDFInfo
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- CN115052291B CN115052291B CN202210599161.1A CN202210599161A CN115052291B CN 115052291 B CN115052291 B CN 115052291B CN 202210599161 A CN202210599161 A CN 202210599161A CN 115052291 B CN115052291 B CN 115052291B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/12—Detection or prevention of fraud
- H04W12/121—Wireless intrusion detection systems [WIDS]; Wireless intrusion prevention systems [WIPS]
- H04W12/122—Counter-measures against attacks; Protection against rogue devices
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/03—Protecting confidentiality, e.g. by encryption
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/04—Key management, e.g. using generic bootstrapping architecture [GBA]
- H04W12/041—Key generation or derivation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a method for resisting malicious intelligent reflecting surface interference attack, which comprises the following steps: the two communication parties perform more than one channel detection in the coherent time; separating the signals from each path in the channel from the received signal each time the channel is detected; according to the signals of the separated paths, calculating the channel characteristic estimated value of each path in each channel detection to obtain the channel characteristic sequence of each path; obtaining the channel characteristic change frequency of each path according to the channel characteristic sequence of the path, and judging whether the path is attacked or not; and generating a physical layer key according to the secure path which is not attacked, and continuing the encrypted communication on the secure path by the two communication parties based on the physical layer key. The invention can detect whether the system is attacked by the phase, and can effectively resist the phase attack under the scene of the phase attack, reduce the bit inconsistency rate after the attack, and ensure that both communication parties can continue to carry out key generation and secure communication.
Description
Technical Field
The invention belongs to the technical field of signal security, and particularly relates to a method for resisting malicious intelligent reflecting surface interference attack.
Background
In recent years, wireless communication technology has been rapidly developed, which brings great convenience to the work and life of human beings, and particularly under the blowout development of various applications such as mobile internet, internet of things and mobile electronic payment, a transmission channel of the wireless communication technology becomes an important medium for transmitting various sensitive information, wherein various sensitive information including personal information, fund security, privacy security and the like is involved. However, the conventional communication encryption method cannot meet the requirements of the current high-speed and low-delay network, so that the physical layer key generation technology and the intelligent reflector technology are generated. However, the existing technology of combining physical layer key generation technology with smart reflective surfaces focuses mainly on increasing randomness of communication environment and solving the problem of quasi-static key generation rate, and does not consider the case when smart reflective surfaces are used for attack by attackers.
Disclosure of Invention
The invention aims to: in order to solve the problem that an intelligent reflecting surface is controlled by an attacker and used for carrying out random phase attack on a legal communicator in the prior art, the invention discloses a method for resisting malicious intelligent reflecting surface interference attack, and the method for resisting the malicious intelligent reflecting surface interference attack is realized.
The technical scheme is as follows: in order to achieve the above purpose, the invention adopts the following technical scheme:
a method for resisting malicious intelligent reflection surface interference attack comprises the following steps:
s1, the two communication parties mutually transmit pilot signals in the coherent time to perform more than one channel detection;
s2, when each channel detection is carried out, signal separation is carried out on the obtained received signals, and signals from each path in the channel are separated from the received signals;
s3, calculating channel characteristic estimated values of each path during each channel detection according to signals of each path separated during each channel detection, so as to obtain channel characteristic sequences of each path;
s4, obtaining the channel characteristic change frequency of each path according to the channel characteristic sequence of the path, and judging whether the path is attacked or not according to the channel characteristic change frequency;
s5, generating a physical layer key according to the secure path which is not attacked, and continuing to encrypt communication on the secure path by the two communication parties based on the physical layer key.
Preferably, in the step S4, a K-point DFT is performed on the channel feature sequence of each path, K is the total number of channel detection, and the value with the largest energy after the K-point DFT is performed on the channel feature sequence is taken as the channel feature variation frequency of the corresponding path.
Preferably, in the step S4, the channel characteristic change frequency of each path is compared:
if the channel characteristic change frequencies of all paths are smaller than or equal to a preset threshold value, the fact that no paths are attacked by phase in the channel is indicated, and all paths are safe paths;
if the channel characteristic change frequency of the existing path is larger than a preset threshold value, the corresponding path in the channel is subjected to phase attack, the attacked path is abandoned, and the rest other paths are all safe paths.
Preferably, in the step S3, for the kth signal detection:
assuming that the signal of the separated nth path is y n Then it can be expressed as:
y n =h n s+n n
where s is the transmitted pilot signal, n n Is the additive Gaussian white noise corresponding to the nth path, h n For the channel characteristics corresponding to the nth path, z n =h n s is a noise-free receiving signal of the nth path;
let the actual received signal y n I.e. noisy and noiseless received signals z n The sum of variances of (2) is the minimum, namely:
min||h n s-y n || 2
the channel characteristic estimate for the nth path is:
setting the channel characteristic estimated value of the nth path in the kth channel detection asChannel characteristic sequence of nth path in K times of signal detection process
Preferably, in step S2, a multiple signal classification algorithm is used to separate the signals of each path in the channel from the obtained received signals.
The beneficial effects are that: the invention has the following remarkable beneficial effects:
1. the invention starts from the scene that the intelligent reflecting surface is controlled by an attacker to perform phase attack, and realizes a method for generating the security key under the phase attack of two communication parties: whether the system is subjected to random phase attack or not is detected, and under the scene that an attacker controls the intelligent reflecting surface to carry out phase attack, the phase attack can be effectively resisted, the bit inconsistency rate after being attacked is reduced, and the two communication parties can be ensured to continue key generation and safety communication;
2. the method detects the channel for multiple times in the coherent time, detects the change frequency of the channel characteristics of each path, finds out the path under phase attack, discards the path under attack, generates the key by using the channel characteristics of the rest safety paths, ensures the safety of both communication parties, completes the whole process according to the real-time channel characteristics in the coherent time, has timely processing capability, and simultaneously applies the path detection and path separation technology to the field of resisting phase attack under the generation of the physical layer key, thereby enhancing the safety and reliability of the generation of the physical layer key.
Drawings
FIG. 1 is a flow chart of a method for protecting against malicious smart reflector interference attacks according to one embodiment of the present invention;
FIG. 2 is a DFT-based attack path detection result for one embodiment of the present invention;
fig. 3 is a comparison of systematic bit inconsistency performance before and after phase attack protection according to an embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings.
Assuming that both parties are Alice and Bob, when Alice and Bob perform legal communication, the communication system is a time division multiplexing multi-antenna system, and Alice and Bob generate a key by using a channel between them.
Assuming that an active attacker with an intelligent reflecting surface is Eve, eve continuously carries out phase attack on a communication system for legal communication between Alice and Bob: the active attacker Eve controls the Intelligent Reflection Surface (IRS) so that the IRS's reflection phases are different when Alice and Bob detect channels respectively, to reduce the key generation rate, but the active attacker Eve does not have eavesdropping capability.
Based on the situation, the invention discloses a method for resisting the interference attack of a malicious intelligent reflecting surface, which comprises the steps that two communication parties conduct channel detection for a plurality of times in the coherent time, a MUSIC path separation algorithm is used for distinguishing signals of different paths in a channel to obtain channel characteristic sequences of the different paths in the coherent time, the channel characteristic sequences of the different paths are subjected to change frequency detection, a path with high-frequency change of the channel characteristic, namely a path under phase attack, is found, the path under phase attack is abandoned, a safety path is reserved, a physical layer key is generated according to the safety path in the channel, encryption communication is continued on the safety path, and finally the resistance to the interference attack of the malicious intelligent reflecting surface is realized. As shown in fig. 1, the method specifically comprises the following steps:
step S1: the two communication parties transmit pilot signals to each other for a plurality of times in the coherent time, and channel detection is performed.
The mutual transmission of pilot signals by the two parties must be within the coherence time, since the characteristics of the channels extracted by Alice and Bob of the two parties by the received signals during the coherence time are identical and remain substantially unchanged, due to the reciprocity of the channels.
Step S2: and when each time of channel detection, the two communication parties respectively perform signal separation on the acquired received signals, and separate the signals from each path in the channel from the received signals.
In one embodiment of the invention, a multiple signal classification (Multiple Signal Classification, MUSIC) algorithm is used to separate signals from multiple paths in a channel.
Assuming that during the kth channel detection, the Alice end sends a pilot signal s to the Bob end, and the received signal obtained by the Bob end is X, a mathematical model of a Direction-of-Arrival (DOA) of the narrowband far-field signal is:
X=AS+N
wherein:
received signal x= [ X ] 1 ,x 2 ,…,x m ,…,x M ] T M is the number of Bob end antenna units, x m The obtained receiving signal is the m-th antenna unit of the Bob end;
transmission signal s= [ S ] 1 ,s 2 ,…,s n ,…,s N ] T N is the number of paths included in the channel between Alice end and Bob end, s n Pilot signal transmitted for the nth path,s n =s,n=1,2,…,N;
Channel matrix a= [ a (θ) 1 ),a(θ 2 ),…,a(θ n ),…,a(θ N )],θ n Is the direction of arrival angle, a (θ n ) Is the steering vector for the nth path,λ represents the wavelength of the pilot signal, d is the spacing between every two antenna elements, typically d=λ/2;
noise matrix n= [ N ] 1 ,n 2 ,…,n m ,…,n M ] T ,n m Is the noise of the mth antenna unit at the Bob end.
Solving a covariance matrix R of a received signal X:
R=E[XX H ]=AE[SS H ]A H +E[NN H ]=AR S A H +R N
wherein R is S R is a signal correlation matrix S =E[SS H ],R N Is a noise correlation matrix, R N =σ 2 I,σ 2 And I is an identity matrix, which is noise power.
Eigenvalue lambda of covariance matrix R i Sorting 1.ltoreq.i.ltoreq.M by size, i.e.lambda 1 ≥λ 2 ≥…≥λ M Not less than 0, characteristic value lambda i The corresponding feature vector is v i The N largest eigenvalues and corresponding eigenvectors are regarded as signal part space, the rest M-N eigenvalues and corresponding eigenvectors are regarded as noise part space, and a noise matrix U is obtained N The method comprises the following steps:
A H v i =0,i=N+1,N+2,…,M
U N =[v N+1 ,v N+2 ,…,v M ]
constructing a MUSIC power spectrum function:
the denominator in this is the steering vector a (θ) and the noise matrix U N When a (θ) is equal to U N The denominator is zero when the columns of (a) are orthogonal, but because of the presence of noise it is effectively a minimum, therefore P MUSIC There is a peak value, from which θ is varied, and the direction of arrival angle of each path signal is estimated by finding the peak.
Thus constructing a spectrum and performing a minimum optimization search:
thus, the arrival direction angle of the signal of each path in the channel is obtained when the kth channel is detected. Furthermore, the direction of arrival angle of the signals of each path in the channel can be obtained when each channel is detected, so that the signals of each path in the channel are separated from the received signals when each channel is detected.
S3: and calculating the channel characteristic estimated value of each path during each channel detection according to the signals of each path separated during each channel detection, thereby obtaining the channel characteristic sequence of each path.
Suppose Alice's end is at t k And (3) carrying out the kth channel detection at any time, namely transmitting a kth pilot signal s, k=1, 2, … and K to the Bob end through each path in the channel, wherein K is the total number of channel detection, and an active attacker Eve can also obtain the pilot signal due to the disclosure of the pilot signal. At this time, the Bob end performs channel estimation according to signals of each path obtained from the received signal, and obtains channel characteristics of each path.
The least squares algorithm is used here for channel estimation, by finding an estimate, so that the variance of the true measured value from this estimate is minimized. The pilot signal sent by the Alice terminal is s, and the channel between the Alice terminal and the Bob terminal has N pathsThe corresponding channel characteristics are respectively denoted as h 1 ,h 2 ,...,h N 。
Assuming that the signal of the separated nth path is y n Then it can be expressed as:
y n =h n s+n n
wherein n is n Is the additive Gaussian white noise corresponding to the nth path, h n For the channel characteristics corresponding to the nth path, z n =h n s is the noise-free received signal of the nth path.
Let the actual received signal y n I.e. noisy and noiseless received signals z n The sum of variances of (2) is the minimum, namely:
min||h n s-y n || 2
the final optimal solution is:
the nth path is at the t th path obtained through the process k Channel characteristic estimated value in time kth channel detectionNext, bob ends at t k+1 =t k +t e Transmitting pilot signal s to Alice terminal at moment, wherein t e Is a minimum value, so that t i+1 And t i The nth path is obtained at the t-th path through the process in the coherent time k+1 Channel characteristic estimated value +.1-th channel detection at time instant>Namely, according to the signals of each path separated during each channel detection, the channel characteristic estimated value +.>
Let h n For the channel characteristic sequence of the nth path in the K signal detection processes, then
S4: and carrying out Fourier transformation on the channel characteristic sequence of each path in the K signal detection processes to obtain the channel characteristic change frequency of each path, and judging whether the corresponding path is attacked or not and whether the corresponding path is a safety path or not according to the channel characteristic change frequency.
Since there is little change in the channel characteristics of the path that is not attacked during the coherence time, there is little change in the channel characteristics during the K channel probing. When the channel detection is carried out on the attacked path in the coherence time, the channel characteristic change frequency of the attacked path is far higher than that of the unaddressed path due to the random phase shift of the change of the intelligent reflecting surface. As shown in fig. 2, the channel characteristics of the attacked path vary significantly.
At this time, the channel characteristic sequence of each path has K channel characteristics, and K point DFTs are respectively performed on the channel characteristic sequence of each path, so that the variation condition of the channel characteristic of each path can be obtained, and the value with the maximum energy after K point DFTs are performed on the channel characteristic sequence is taken as the channel characteristic variation frequency f of the corresponding path.
Comparing the channel characteristic change frequency f of each path:
if the channel characteristic change frequencies F of all paths are in a reasonable range, namely are smaller than or equal to a threshold value F, the fact that no paths are attacked by phase in the channel is indicated, and all paths are safe paths is indicated, wherein the threshold value F is selected according to the actual condition of a communication system;
if the channel characteristic change frequency F of the existing path exceeds a reasonable range, namely the channel characteristic change frequency F of the existing path is larger than a threshold value F, the corresponding path in the channel is subjected to phase attack, the attacked path is abandoned, and the rest other paths are all safe paths.
S5: and generating a physical layer key according to the secure path, and continuing to carry out encrypted communication on the secure path, so as to realize the defense of the malicious intelligent reflecting surface against interference attack.
Furthermore, in one embodiment of the present invention, bit inconsistency rate (BDR) is used to evaluate the effect of combating phase attacks. Bit inconsistency rate is defined as the proportion of inconsistent bits in the total number of bits generated by both communicating parties depending on the channel characteristics of the channel. Fig. 3 shows bit inconsistency rates of systems before and after the two communication parties resist the phase attack in the test, and it can be seen that after the method of the invention is adopted to resist the attack of malicious intelligent reflecting surface interference, the bit inconsistency rate of the communication system is obviously lower than the situation of not resisting the attack of malicious intelligent reflecting surface interference, thereby proving the effectiveness of the method of the invention.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (5)
1. The method for resisting the malicious intelligent reflecting surface interference attack is characterized by comprising the following steps of:
s1, the two communication parties mutually transmit pilot signals in the coherent time to perform more than one channel detection;
s2, when each channel detection is carried out, signal separation is carried out on the obtained received signals, and signals from each path in the channel are separated from the received signals;
s3, calculating channel characteristic estimated values of each path during each channel detection according to signals of each path separated during each channel detection, so as to obtain channel characteristic sequences of each path;
s4, obtaining the channel characteristic change frequency of each path according to the channel characteristic sequence of the path, and judging whether the path is attacked or not according to the channel characteristic change frequency;
s5, generating a physical layer key according to the secure path which is not attacked, and continuing to encrypt communication on the secure path by the two communication parties based on the physical layer key.
2. The method for resisting interference attack of malicious intelligent reflecting surface according to claim 1, wherein in the step S4, K-point DFT is performed on the channel characteristic sequence of each path, K is the total number of channel detection, and the value with the largest energy after K-point DFT is performed on the channel characteristic sequence is taken as the channel characteristic variation frequency of the corresponding path.
3. The method for protecting against attack by malicious smart reflective surface according to claim 1, wherein in the step S4, the channel characteristic variation frequency of each path is compared:
if the channel characteristic change frequencies of all paths are smaller than or equal to a preset threshold value, the fact that no paths are attacked by phase in the channel is indicated, and all paths are safe paths;
if the channel characteristic change frequency of the existing path is larger than a preset threshold value, the corresponding path in the channel is subjected to phase attack, the attacked path is abandoned, and the rest other paths are all safe paths.
4. The method of claim 1, wherein in step S3, for the kth signal detection:
assuming that the signal of the separated nth path is y n Then it can be expressed as:
y n =h n s+n n
where s is the transmitted pilot signal, n n Is the additive Gaussian white noise corresponding to the nth path, h n For the channel characteristics corresponding to the nth path, z n =h n s is a noise-free receiving signal of the nth path;
let the actual received signal y n I.e. noisy and noiseless received signals z n The sum of variances of (2) is the minimum, namely:
min||h n s-y n || 2
the channel characteristic estimate for the nth path is:
setting the channel characteristic estimated value of the nth path in the kth channel detection asChannel characteristic sequence of nth path in K times of signal detection process
5. A method of combating a malicious smart reflector interference attack according to claim 1, wherein in step S2, a multi-signal classification algorithm is used to separate the signals of each path in the channel from the received signals obtained.
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