CN113158157B - Method for extracting equipment fingerprint information in wired network card signal - Google Patents
Method for extracting equipment fingerprint information in wired network card signal Download PDFInfo
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- CN113158157B CN113158157B CN202110352971.2A CN202110352971A CN113158157B CN 113158157 B CN113158157 B CN 113158157B CN 202110352971 A CN202110352971 A CN 202110352971A CN 113158157 B CN113158157 B CN 113158157B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- G—PHYSICS
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- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/602—Providing cryptographic facilities or services
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
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Abstract
The invention discloses a method for extracting equipment fingerprint information in a wired network card signal, which comprises the following steps: carrying out normalization processing and judgment on an input signal to obtain a judgment signal; performing clock extraction of rising edges and falling edges on the judgment signals, and synchronizing a local clock to obtain a synchronous clock; sampling the decision signal by using a synchronous clock to obtain an ideal waveform synchronous with a local clock; taking the ideal waveform signal as the filtering input of the adaptive filter, and processing the ideal waveform signal to enable the ideal signal to approach to a received signal by a minimum mean square error after filtering, wherein the parameter of the adaptive filter at the moment is the equipment fingerprint of the network card; and then extracting fingerprints from the input signals of a plurality of time periods to obtain stable network card equipment fingerprints. The invention can realize the extraction of the device fingerprint information in the wired network card, obtain the device fingerprint with both stability and identifiability, further realize the identity authentication of the terminal device and the security of network access.
Description
Technical Field
The invention relates to the technical field of equipment fingerprint extraction of physical layer signals, in particular to an equipment fingerprint information extraction method of a wired network card by using an adaptive filter.
Background
With the rapid development of computer technology, people increasingly depend on networks in daily life, and ethernet is the most common computer network in real life. Statistically, the ethernet mode occupies approximately 80% of the world's network nodes, with almost all computers being equipped with ethernet controllers. While the development of the ethernet technology brings convenience to the life of people, due to the wide connectivity of the ethernet technology, the security of network information and property is greatly threatened, so that the results of illegal access to network resources, threatened communication privacy of people, intrusion of computers and the like are caused. Therefore, how to ensure the security and reliability of the ethernet connection becomes an important issue for guaranteeing the security of users in the network.
In the aspect of guaranteeing the security of the wired network, the security of the system is realized mainly by implementing access control on the terminal, avoiding illegal access, protecting the equipment per se and preventing malicious codes from invading. In terms of secure access to network devices, the solutions proposed by researchers at present can be roughly divided into two categories. The first type is to identify and judge information such as an IP address, an MAC address, and the like of a terminal connected to an ethernet structure. The address information of the terminal is compared with data in the database of the control terminal to determine whether to allow the terminal to access the network, and particularly, it is more common to use the MAC address as the identification method. Both IP and MAC addresses are easily changed. The second type is a digital certificate mode, in which the identity information of the user is verified and authenticated by means of a username and a password, etc. The user identity can be verified through the digital certificate, but the digital certificate technology is more complicated to use in the system, and the risk of stealing and embezzlement also exists. Therefore, the traditional wired network security access mode has more or less defects.
The invention provides a method for extracting a physical fingerprint of a wired network card based on terminal equipment, which is used for effectively identifying a terminal by the physical fingerprint of the network card. Network technology has been developed so far, and a network card internally includes many electronic components such as capacitors, inductors, and other digital logic circuits. Due to the manufacturing process and errors in manufacturing, and the like, the components inevitably have certain errors between the component parameters and the standard values thereof. Thus the same input signal through different network cards will produce different outputs with the physical details of the network cards. The output signal of the network card is analyzed, and the change details generated by the physical characteristics of the network card can be extracted to be used as the fingerprint of the network card. The device fingerprint can hardly be cloned and bound with the terminal device one by one and can not be tampered, so that the safety problem that information such as IP/MAC addresses and the like is easily tampered can be solved. Because the characteristic information of the network card device fingerprint is very fine, an effective and fine technical means is needed to extract the stably identifiable fingerprint information.
Disclosure of Invention
The invention aims to provide a method for extracting equipment fingerprint information in a wired network card signal, aiming at overcoming the unsafe problem that an IP address/MAC address is taken as the identity of a computer terminal. The invention extracts the fingerprint information of the network card which can be used for characteristic identification aiming at the signals sent by the network card detected at the exchange side, and the fingerprint information has good stability of the same individual and difference of different individuals.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method for extracting device fingerprint information in a wired network card signal comprises the following steps:
step 1, signal acquisition: collecting signals from a terminal network card at the side of the exchange, storing differential signal sampling values, and carrying out amplitude normalization processing on the differential signal sampling values to obtain x (n);
step 2, judging: truncating a segment of the input signal containing M symbols { x m (n), M =0,1, \ 8230;, M-1}, which is decided to obtain an input symbol sequence y m (n), the sequence being a multilevel sequence;
and step 3, symbol synchronization: for the symbol sequence after decision { y m (n) taking the rising and falling edges, respectively, and combining them together to form a pulse train { p } m (n) spreading the width of each pulse sequence to 1/2 of the width of one symbol to form a front and rear edge pulse sequence { q) } m (n) }; generating a local clock CLK of length M symbols at the same rate as the symbol rate m (n); the local clock signals of N symbol lengths are XOR-ed with the leading and trailing edge pulse sequences and accumulated, i.e.
Cyclically shifting the local clock until the accumulated value S is minimum, and recording the local clock signal CLK OPT (n)；
Step 4, resampling the input signal: to synchronize the local clock CLK OPT (n) logical inversion to obtain
Using the signal to input symbol sequence y m (n) resampling to obtain { z } m (n)}；
Step 5, adaptive filtering: will { z m (n) signal and { x } m (n) the signal is fed to an adaptive filter, where { x } m (n) as input signal for filter, { z } m (n) as a reference signal; using the minimum mean square error of the output of the filter and a reference signal as an iteration control signal of the self-adaptive filter; when the adaptive filter converges, the adaptive filter coefficients { a } 0 ,a 1 ,…,a L-1 The device fingerprint information in the wired network card signal is obtained, wherein L is the effective length of the filter;
step 6, taking the average value of the fingerprints: repeating the steps 1 to 5 for K times, and taking the average value of the coefficients of the K groups of adaptive filters as the fingerprint output of the wired network card, namely
Further, in the step 1, the signal acquisition is to acquire two complete paths of differential signals of the wired network card on a line between the terminal network card and the switch in an oversampling manner, and shape the acquired differential signals according to the coding features of the network card standard protocol.
Further, in step 1, the operation of adding two paths of differential signals is performed on the collected idle time data between the hundred-megabyte limited network card and the switch.
Further, in the step 2, the decision threshold is set to a position of 1/2 of the average amplitude between the respective levels of the signal.
Further, in step 3, the local clock CLK is set m (n) and series of front and back porch pulses { q m (n) inputting the phase discriminator, if the output is 1 in advance of a half period, the output is-1 in lag of a half period, and 0 is completely synchronously output; accumulating the data results, if the result is greater than zero, indicating that the local clock lags behind the signal clock; otherwise, if the result is less than zero, the local clock leads the signal clock; according to the accumulated result, the local clock CLK is controlled m (n) adjusting, if the result is larger than zero, reducing the data points of the local clock to lead the data points; if the result is less than zero, increasing the data point of the local clock to lead the data point to be lagged; continuously taking the adjusted local clock as input, and adjusting the next section of data of the local clock according to the accumulation result to lead or lag the data; repeating the step, circularly shifting the local clock until the accumulation result is minimum; local clock CLK obtained at this time OPT (n) considered to be perfectly synchronized with the signal clock.
Further, in the step 5, the data waveform { x } m (n) passes through an adaptive filter to produce an output { X } m (n) }, i.e.:
wherein, a i ∈{a 0 ,a 1 ,…,a L-1 }；
{X m (n) and true output z m The error between (n) is e (n), i.e.:
e(n)＝{z m (n)}-{X m (n)}
and performing minimum mean square error operation on the error e (n), namely:
min[E(e 2 (n))]
using the error e (n) simultaneously on the filter coefficient a i Adjusting:
a′ i ＝a i +2μe(n)x(n)
the above-mentioned steps are repeated, and then,so that [ E (E) 2 (n))]The minimum value is reached; at this time, { X m (n) and true output z m (n) substantially the same, coefficients of the adaptive filter a 0 ,a 1 ,…,a L-1 L is the effective length of the filter; at this time, the filter coefficients of different network cards are considered to be different influences of different network cards on output signals, so that different results are generated and used as fingerprint information of the equipment.
Has the beneficial effects that: compared with the prior art, the invention has the following advantages:
(1) Compared with other equipment information authentication modes, the equipment fingerprint based on the wired network card signal has higher reliability and non-tamper property, and has higher security on the authentication of illegal equipment;
(2) The self-adaptive filter algorithm is used for extracting the fingerprint information of the equipment more accurately, and the interference of data and noise in the signal is effectively removed;
(3) The fingerprint extraction method is simple, can perform real-time extraction, and does not increase the operation burden in the use process.
The method for extracting the equipment fingerprint information in the wired network card signal can extract the terminal equipment fingerprint information in the signal passing through the wired network card, and can be used for identity authentication and identity authentication of the terminal.
Drawings
FIG. 1 is a schematic diagram of a network card fingerprint extraction process;
FIG. 2 is a schematic diagram of an input signal decision process;
FIG. 3 is a schematic diagram of data flow and local clock synchronization;
FIG. 4 is a schematic diagram of a fingerprint extraction algorithm;
fig. 5 is a diagram illustrating an extracted fingerprint signal, in which the horizontal axis represents ordinal numbers of coefficients and the vertical axis represents amplitudes of the coefficients.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the drawings as follows:
as shown in fig. 1, the method for extracting device fingerprint information in a wired network card signal of the present invention is characterized in that: the method comprises the following steps:
step 1, signal acquisition: collecting signals from a terminal network card at the side of the exchange, storing differential signal sampling values, and carrying out amplitude normalization processing on the differential signal sampling values to obtain x (n);
the signal acquisition is to acquire two paths of complete differential signals of a wired network card on a line between a terminal network card and an exchanger in an oversampling mode, and simultaneously, to shape the acquired differential signals according to the coding characteristics of a network card standard protocol, so as to adjust the acquired signals into standard waveforms, namely square waves;
and for idle-time data between the acquired hundred-megabyte limited network card and the switch, adding two paths of differential signals to effectively inhibit the influence of specific data on fingerprint extraction.
Step 2, judging: truncating a segment of the input signal containing M symbols { x m (n), M =0,1, \8230;, M-1}, which is decided to obtain an input symbol sequence y m (n), the sequence being a multilevel sequence; wherein the decision threshold is set to a position of 1/2 of the average amplitude between the respective levels of the signal, as shown in fig. 2.
And step 3, symbol synchronization: for the symbol sequence after decision { y m (n) taking the rising and falling edges, respectively, and combining them together to form a pulse train { p } m (n), and then expanding the width of each pulse sequence to make the width of each pulse sequence be 1/2 of the width of one symbol to form a front-back edge pulse sequence { q } m (n) }; generating a local clock CLK of length M symbols at the same rate as the symbol rate m (n); the local clock signals of N symbol lengths are XOR-ed with the leading and trailing edge pulse sequences and accumulated, i.e.
Cyclically shifting the local clock until the accumulated value S is minimum, and recording the local clock signal CLK OPT (n)；
Specifically, as shown in FIG. 3, the local clock CLK is divided m (n) and series of front and back porch pulses { q m (n) inputting the phase discriminator, outputting the phase discriminator if the phase discriminator leads by half a cycle1, outputting-1 after delaying for half period, and outputting 0 in complete synchronization; accumulating the data results, if the result is greater than zero, indicating that the local clock lags behind the signal clock; otherwise, if the result is less than zero, the local clock leads the signal clock; according to the accumulated result, the local clock CLK is controlled m (n) adjusting, if the result is greater than zero, reducing the data point of the local clock to lead the data point; if the result is less than zero, the data point of the local clock is increased to lag behind it.
Continuously taking the adjusted local clock as input, and adjusting the next section of data of the local clock according to the accumulation result to lead or lag the data; repeating the step, circularly shifting the local clock until the accumulation result is minimum; local clock CLK obtained at this time OPT (n) considered to be perfectly synchronized with the signal clock.
Step 4, resampling the input signal: to synchronize the local clock CLK OPT (n) logical inversion to obtain
Using the signal to input symbol sequence y m (n) resampling to obtain { z } m (n)}；
Step 5, adaptive filtering: will { z m (n) signal and { x } m (n) the signal is fed to an adaptive filter, where { x } m (n) as input signal for filter, { z } m (n) as a reference signal; using the minimum mean square error of the output of the filter and a reference signal as an iteration control signal of the self-adaptive filter; when the adaptive filter converges, the adaptive filter coefficients { a } 0 ,a 1 ,…,a L-1 The device fingerprint information in the wired network card signal is obtained, wherein L is the effective length of the filter;
specifically, as shown in FIG. 4, will { x } m (n) as input signal for filter, { z } m (n) as a reference signal.
Selecting proper self-adaptive filter order and step length according to signal characteristics, data waveform { x m (n) producing an output X after passing through an adaptive filter m (n) }, i.e.:
wherein, a i ∈{a 0 ,a 1 ,…,a L-1 }；
{X m (n) and true output z m The error between (n) is e (n), i.e.:
e(n)＝{z m (n)}-{X m (n)}
and performing minimum mean square error operation on the error e (n), namely:
min[E(e 2 (n))]
using the error e (n) simultaneously on the filter's coefficient a i Adjusting:
a′ i ＝a i +2μe(n)x(n)
selecting a suitable number of iterations and repeating the above steps so that [ E (E) ] 2 (n))]The minimum is reached; at this time, { X m (n) and true output z m (n) are substantially the same, coefficients of the adaptive filter { a } 0 ,a 1 ,…,a L-1 Where L is the effective length of the filter; at this time, the filter coefficients of different network cards are considered to be different influences of different network cards on output signals, so that different results are generated and used as fingerprint information of the equipment. The self-adaptive filter under the method simulates an output system of the network card signal and comprises the influence of a network card device on the output signal, so that the device can be considered as real and reliable device fingerprint information.
Step 6, taking the average value of the fingerprints: repeating the steps 1 to 5 for K times, and taking the average value of the coefficients of the K groups of adaptive filters as the fingerprint output of the wired network card, namely
The above description is only of the preferred embodiments of the present invention, and it should be 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 invention and these are intended to be within the scope of the invention.
Claims (6)
1. A method for extracting equipment fingerprint information in a wired network card signal is characterized by comprising the following steps: the method comprises the following steps:
step 1, signal acquisition: collecting signals from a terminal network card at the side of the exchange, storing differential signal sampling values, and carrying out amplitude normalization processing on the differential signal sampling values to obtain x (n);
step 2, judging: truncating a segment of the input signal containing M symbols { x m (n), M =0,1, \8230;, M-1}, which is decided to obtain an input symbol sequence y m (n), the sequence being a multilevel sequence;
step 3, symbol synchronization: for the symbol sequence after decision { y m (n) taking the rising and falling edges respectively and combining them together to form a pulse train { p } m (n), and then expanding the width of each pulse sequence to make the width of each pulse sequence be 1/2 of the width of one symbol to form a front-back edge pulse sequence { q } m (n) }; generating a local clock CLK of length M symbols at the same rate as the symbol rate m (n); XOR and accumulate the N symbol-length local clock signals with the leading and trailing edge pulse sequences, i.e.
Cyclically shifting the local clock until the accumulated value S is minimum, and recording the local clock signal CLK OPT (n)；
Step 4, resampling the input signal: to synchronize the local clock CLK OPT (n) logical inversion to obtain
Using the signal to input symbol sequence y m (n) resampling to obtain { z } m (n)}；
Step 5, adaptive filtering: will { z m (n) signal and { x } m (n) the signal is fed to an adaptive filter, where x m (n) as input signal of filter, { z } m (n) } as a reference signal; using the minimum mean square error of the output of the filter and a reference signal as an iteration control signal of the self-adaptive filter; when the adaptive filter converges, the adaptive filter coefficients { a } 0 ,a 1 ,…,a L-1 The device fingerprint information in the wired network card signal is obtained, wherein L is the effective length of the filter;
step 6, taking the average value of the fingerprints: repeating the steps 1 to 5 for K times, and taking the average value of the coefficients of the K groups of adaptive filters as the fingerprint output of the wired network card, namely
2. The method for extracting device fingerprint information in a wired network card signal according to claim 1, wherein: in the step 1, the signal acquisition is to acquire two complete paths of differential signals of the wired network card on a line between the terminal network card and the switch in an oversampling mode, and shape the acquired differential signals according to the coding characteristics of the network card standard protocol.
3. The method for extracting device fingerprint information in a wired network card signal according to claim 2, wherein: in the step 1, the two paths of differential signals are added to the acquired idle time data between the hundred-megabyte limited network card and the switch.
4. The method for extracting device fingerprint information in a wired network card signal according to claim 1, wherein: in the step 2, the decision threshold is set to be a position of 1/2 of the average amplitude between the levels of the signal.
5. The method for extracting device fingerprint information from a wired network card signal according to claim 1, wherein: in the step 3, the local clock CLK is set m (n) and series of front and back porch pulses { q m (n) inputting a phase discriminator, and if the output is advanced by half cycle and 1 is output, lagging by half cycle and outputting-1, and completely synchronously outputting 0; accumulating the data results, if the result is greater than zero, indicating that the local clock lags behind the signal clock; if the result is less than zero, the local clock leads the signal clock; according to the accumulated result, the local clock CLK is controlled m (n) adjusting, if the result is larger than zero, reducing the data points of the local clock to lead the data points; if the result is less than zero, increasing the data point of the local clock to lead the data point to be lagged; continuously taking the adjusted local clock as input, and adjusting the next section of data of the local clock according to the accumulation result to lead or lag the data; repeating the step, circularly shifting the local clock until the accumulation result is minimum; local clock CLK obtained at this time OPT (n) considered to be perfectly synchronized with the signal clock.
6. The method for extracting device fingerprint information from a wired network card signal according to claim 1, wherein: in step 5, the data waveform { x } m (n) passes through an adaptive filter to produce an output { X } m (n) }, i.e.:
wherein, a i ∈{a 0 ,a 1 ,…,a L-1 }；
{X m (n) and true output z m The error between (n) is e (n), i.e.:
e(n)＝{z m (n)}-{X m (n)}
and performing minimum mean square error operation on the error e (n), namely:
min[E(e 2 (n))]
using the error e (n) simultaneously on the filter's coefficient a i And (3) adjusting:
a′ i ＝a i +2μe(n)x(n)
the above steps are repeated so that [ E (E) 2 (n))]To achieveMinimum; at this time, { X m (n) and true output z m (n) substantially the same, coefficients of the adaptive filter a 0 ,a 1 ,…,a L-1 Where L is the effective length of the filter; at this time, the filter coefficients of different network cards are considered to be different influences of different network cards on the output signal, so that different results are generated and used as fingerprint information of the equipment.
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