CN112104459A - Key generation method based on channel fingerprints and auxiliary data - Google Patents
Key generation method based on channel fingerprints and auxiliary data Download PDFInfo
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- CN112104459A CN112104459A CN202010945573.7A CN202010945573A CN112104459A CN 112104459 A CN112104459 A CN 112104459A CN 202010945573 A CN202010945573 A CN 202010945573A CN 112104459 A CN112104459 A CN 112104459A
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- 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
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Abstract
The invention discloses an end-to-end key generation method based on channel fingerprints and auxiliary data, which comprises the following steps: a sending end generates a random key; the transmitting end traverses the channel characteristic data and judges whether the data falls into a quantization interval or not; the transmitting end quantizes the channel characteristic data by using a zero leakage quantization method; the sending end obtains an auxiliary data generating function, calculates an auxiliary data value and sends the auxiliary data value to the receiving end; the receiving end traverses the auxiliary data and restores the channel characteristic data; and the receiving end judges whether the restored channel characteristic data is equal to the channel characteristic data detected by the receiving end, if the restored channel characteristic data is equal to the channel characteristic data detected by the receiving end, the secret key is restored according to the maximum likelihood algorithm if the restored channel characteristic data is not equal to the channel characteristic data, and finally the generated secret key is obtained. The invention processes the channel characteristic data through the corresponding algorithm, generates the key, extracts the corresponding auxiliary data, enhances the key randomness and the consistency rate of the end-to-end communication equipment, and ensures higher communication safety.
Description
Technical Field
The invention relates to the field of information security, in particular to a key generation method based on channel fingerprints and auxiliary data.
Background
Wireless communication is increasingly applied to various industries, which brings high efficiency and convenience to daily life of people, but brings along with the safety problem which needs to be solved urgently. For example, wireless networks communicate by broadcasting, without a clear boundary, so that the content transmitted by the wireless networks is more easily intercepted, and the position where the wireless signals reach may be attacked; the network structure of wireless communication is often in dynamic change, and the difference of different network structures is large, so that the generated key is difficult to make centralized decision and management; the wireless communication terminal has mobility, physical defense measures such as a firewall and the like cannot be applied, once a wireless network is attacked, the position of an attacker is difficult to locate due to uncertainty of terminal movement, and the implementation difficulty of a security management scheme is high. Therefore, it is important to secure wireless communication.
The traditional security mechanism needs a fixed key management center to provide keys for both communication parties, however, since the openness, mobility and topology of the wireless network are often limited by dynamic changes, the wireless network has difficulty in managing and distributing keys through the fixed key management center. In recent years, in order to solve the problem of difficulty in key distribution in wireless networks, scholars have proposed a wireless physical layer key generation technique. The technology utilizes channel reciprocity to collect channel characteristics in coherent time to generate a key, avoids key distribution, has the characteristics of low calculation complexity and high safety, but the generated key is highly correlated with the channel characteristics and has low randomness. Therefore, the scholars propose a fuzzy extractor structure, which utilizes the auxiliary data to generate a secret key, can effectively enhance the randomness of the key and ensure the safety of wireless communication. However, the auxiliary data generated by the conventional fuzzy extractor is related to the key, and the key information is leaked, so that a new fuzzy extractor structure is urgently needed.
Disclosure of Invention
In view of the problems in the prior art, the present invention provides a key generation method based on channel fingerprint and auxiliary data. The structure of the traditional fuzzy extractor is improved by using symmetric encryption, error correcting codes and one-way hash functions, and the concept of zero-leakage auxiliary data is provided, so that the randomness and the consistency rate of keys are improved, and the safety of a communication system is ensured.
The purpose of the invention is realized by the following technical scheme:
a key generation method based on channel fingerprint and auxiliary data is characterized by comprising the following steps:
(1) generating a random key;
(2) the transmitting end traverses the channel characteristic data and judges whether the data falls into a quantization interval or not;
(3) the transmitting end quantizes the channel characteristic data by using a zero leakage quantization method;
(4) the sending end obtains an auxiliary data generating function, calculates an auxiliary data value and sends the auxiliary data value to the receiving end;
(5) the receiving end traverses the auxiliary data and restores the channel characteristic data;
(6) and the receiving end judges whether the restored channel characteristic data is equal to the channel characteristic data detected by the receiving end, if the restored channel characteristic data is equal to the channel characteristic data detected by the receiving end, the secret key is restored according to the maximum likelihood algorithm if the restored channel characteristic data is not equal to the channel characteristic data, and finally the generated secret key is obtained.
Further, the random key in step (1) is generated by using an RNG random number generator.
Further, the quantization interval in the step (2) is calculated according to quantiles.
Further, the zero-leakage quantization method in step (3) requires that the receiving end receives the auxiliary data to recover the secret key, but the eavesdropper cannot recover the secret key even if the eavesdropper intercepts the auxiliary data.
Further, in step (4), the auxiliary data generating function monotonically increases in each quantization interval, and any output value in each quantization interval has a variable corresponding to it, so that the cumulative distribution function of the channel characteristic data is selected as the auxiliary data generating function.
Further, in the step (5), the channel characteristic data is obtained by performing inverse function reduction on the auxiliary data generating function, is an estimated value, and is slightly different from the channel characteristic data measured by the receiving end.
Further, if the restored channel characteristic data is equal to the channel characteristic data detected by the user, directly restoring the secret key according to the located quantization interval in the step (6); if not, the key needs to be restored by using a maximum likelihood algorithm, i.e. the probability of which quantization interval the helper data falls in is the greatest.
The invention improves the structure of the traditional fuzzy extractor by utilizing symmetric encryption, error correcting codes and one-way hash functions, provides a concept of zero-leakage auxiliary data, and further improves the recovery success rate and the safety of the secret key. The key generation technology uses an error correcting code to improve the reliability of key reduction, thereby improving the information entropy of the key and enhancing the randomness of the key.
Compared with the prior art, the invention has the beneficial effects that:
when the continuous source contains sensitive information, the generated secret key can not leak the sensitive information of the continuous source, the privacy of the continuous source is protected, and meanwhile, a specific continuous source can generate a random secret key. In addition, the key generation method uses the error correcting code to improve the reliability of key reduction, thereby improving the information entropy of the key and enhancing the randomness of the key. Since the auxiliary data and the key are irrelevant, the key cannot be restored even if the auxiliary data transmitted in the channel is intercepted by an eavesdropper, and the communication safety of both communication parties is further ensured.
Experiments show that compared with the existing continuous source key generation technical method, the method of the invention can further improve the randomness of the key and the reliability of the reduction.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a graph of bit error rate for different variance, key bit numbers using the method of the present invention and other methods that do not use zero-leakage auxiliary data;
fig. 3 is a graph of the key agreement rate for recovering different numbers of bits after eavesdropping on the helper data using the method of the present invention.
Detailed Description
A key generation method based on channel fingerprint and auxiliary data, as shown in fig. 1, includes the following steps:
(1) generating a random key;
in specific implementation, the key is generated by the RNG random number generator and is used for encrypting the communication system.
(2) The transmitting end traverses the channel characteristic data and judges whether the data falls into a quantization interval or not;
in this embodiment, the transmitting end sequentially traverses the acquired channel characteristic data; the quantization interval is
In the formula, s is the number of key bits,
distribution function, p, representing channel characteristic datat＝1/t。
(3) The transmitting end quantizes the channel characteristic data by using a zero leakage quantization method;
in a specific implementation, the step (3) specifically includes whether the currently traversed channel feature data falls into a quantization interval represented by the key, and if the currently traversed channel feature data falls into the quantization interval, the currently traversed channel feature data is quantized into a corresponding quantization value, and if the currently traversed channel feature data does not fall into the quantization interval, the currently traversed channel feature data is discarded.
(4) The sending end obtains an auxiliary data generating function, calculates an auxiliary data value and sends the auxiliary data value to the receiving end;
step (4) specifically assumes that the auxiliary data generating function g is in each quantization region AsLi monotonically increasing, g (x)s)＝g(xt)＝w，xsAnd xtRespectively belong to different quantization regions
The auxiliary data generating function g is then defined in a simple manner:
and the channel characteristic data is sequentially brought into an auxiliary data generating function to obtain auxiliary data, and then the auxiliary data is sent to a receiving end.
(5) The receiving end traverses the auxiliary data and restores the channel characteristic data;
the step (5) specifically includes that the receiving end brings the received auxiliary data value into an inverse function of an auxiliary data generation function to obtain channel characteristic data, and the specific steps are as follows:
x＝g-1(w)
(6) the receiving end judges whether the restored channel characteristic data is equal to the self detection data or not, if the restored channel characteristic data is equal to the self detection data, the secret key is restored directly, and if the restored channel characteristic data is not equal to the self detection data, the secret key is restored according to a maximum likelihood algorithm, and finally the generated secret key is obtained;
the step (6) specifically comprises, according to a maximum likelihood algorithm:
to simplify the process of recovering the key, a threshold τ is definedsIf τ iss≤y≤τs+1Then reconstruct
Knowing tau0Infinity and τNInfinity. According to a defined noise model, symmetrical attenuationWeak noise
Is a monotonically decreasing function with point y ═ τsThe probability of being reduced at the boundary of the s and s-1 regions is equal, i.e.
Because of the fact that
So the threshold τsCan be obtained by the following formula:
the attenuation parameter lambda is normally assumed to be 1. For a key s with a bit number of 1, e.g. N-2, zero-leakage assistance data is reduced to calculate a single threshold τ1Calculated threshold τ1No information about the key is revealed. When the continuous source mean is 0, the threshold τ may be assumed1When the channel characteristic measurement value Y is negative, it is quantized to key 0, and when it is positive, it is quantized to key 1, and the restoration process is completed.
FIG. 2 is a graph of bit error rate for different variance, key bit numbers using the method of the present invention and other methods that do not use zero-leakage auxiliary data; fig. 3 is a graph of the key agreement rate for recovering different numbers of bits after eavesdropping on the helper data using the method of the present invention.
By the method, the zero-leakage auxiliary data is used for key agreement, the randomness of the key and the success rate of key restoration can be well improved, and information leakage can be better prevented and controlled to an eavesdropper.
The above disclosure is only illustrative of the preferred embodiments of the present invention, and should not be taken as limiting the scope of the invention, which is defined by the appended claims.
Claims (9)
1. A key generation method based on channel fingerprint and auxiliary data is characterized by comprising the following steps:
(1) generating a random key;
(2) the transmitting end traverses the channel characteristic data and judges whether the data falls into a quantization interval or not;
(3) the transmitting end quantizes the channel characteristic data by using a zero leakage quantization method;
(4) the sending end obtains an auxiliary data generating function, calculates an auxiliary data value and sends the auxiliary data value to the receiving end;
(5) the receiving end traverses the auxiliary data and restores the channel characteristic data;
(6) and the receiving end judges whether the restored channel characteristic data is equal to the channel characteristic data detected by the receiving end, if the restored channel characteristic data is equal to the channel characteristic data detected by the receiving end, the secret key is restored according to the maximum likelihood algorithm if the restored channel characteristic data is not equal to the channel characteristic data, and finally the generated secret key is obtained.
2. The method of claim 1, wherein the channel fingerprint and helper data based key generation method comprises: the random key in step (1) is generated by using an RNG random number generator.
3. The method of claim 1, wherein the channel fingerprint and helper data based key generation method comprises: calculating the quantization interval in the step (2) according to quantiles; the quantization interval is:
in the formula, s is the number of key bits,
distribution function, p, representing channel characteristic datat＝1/t。
4. The method of claim 1, wherein the channel fingerprint and helper data based key generation method comprises: in the zero-leakage quantization method in step (3), the key can be restored after the receiving end receives the auxiliary data, but the key cannot be restored even if the eavesdropper intercepts the auxiliary data.
5. The method of claim 1, wherein the channel fingerprint and helper data based key generation method comprises: in the step (4), the auxiliary data generating function is monotonically increased in each quantization interval, and any output value in each quantization interval has a variable corresponding to the output value, so that the cumulative distribution function of the channel characteristic data is selected as the auxiliary data generating function.
6. The method of claim 5, wherein the channel fingerprint and the helper data are based on: the auxiliary data are obtained as follows: let it be assumed that the auxiliary data generating function g is in each quantization region AsLi monotonically increasing, g (x)s)＝g(xt)＝w，xsAnd xtRespectively belong to different quantization regions
The auxiliary data generating function g is then defined in a simple manner:
and the channel characteristic data is sequentially brought into an auxiliary data generating function to obtain auxiliary data.
7. The method of claim 1, wherein the channel fingerprint and helper data based key generation method comprises: the channel characteristic data in the step (5) is obtained by the inverse function reduction of the auxiliary data generating function, is an estimated value, and is slightly different from the channel characteristic data measured by the receiving end.
8. The method of claim 1, wherein the channel fingerprint and helper data based key generation method comprises: if the restored channel characteristic data is equal to the channel characteristic data detected by the user, directly restoring the secret key according to the quantization interval where the data is located in the step (6); if not, the key is restored using a maximum likelihood algorithm, i.e. the probability of which quantization interval the helper data falls within is the greatest.
9. The method of claim 8, wherein the channel fingerprint and the helper data are based on: the step (6) specifically comprises, according to a maximum likelihood algorithm:
to simplify the process of recovering the key, a threshold τ is definedsIf τ iss≤y≤τs+1Then reconstruct
Knowing tau0Infinity and τNInfinity. Symmetrical attenuating noise according to a defined noise model
Is a monotonically decreasing function with point y ═ τsThe probability of being reduced at the boundary of the s and s-1 regions is equal, i.e.
Because of the fact that
Therefore, it is not only easy to useThreshold τsCan be obtained by the following formula:
the attenuation parameter λ is normally assumed to be 1; for a key s with a bit number of 1, e.g. N-2, zero-leakage assistance data is reduced to calculate a single threshold τ1Calculated threshold τ1Will not reveal any information about the key; when the continuous source mean is 0, the threshold τ may be assumed1When the channel characteristic measurement value Y is negative, it is quantized to key 0, and when it is positive, it is quantized to key 1, and the restoration process is completed.
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