Reliable alternate mapping key extraction method for multi-robot ad hoc networks and related apparatus
By using the reliability index of channel feature sequences to determine candidate intervals and alternately map them to generate keys in a multi-robot self-organizing network, the problems of key consistency and low generation rate are solved, and the security and speed are improved under high signal-to-noise ratio.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XI AN JIAOTONG UNIV
- Filing Date
- 2026-01-29
- Publication Date
- 2026-05-15
AI Technical Summary
Existing physical layer key generation schemes for multi-robot ad hoc networks suffer from insufficient key consistency and low generation rate when facing high-speed movement and hardware inconsistencies, posing a risk of information exchange. The quantization process in existing schemes introduces threshold errors and information loss, leading to security threats.
By acquiring channel feature sequences and sorting them according to amplitude, a reliability index is calculated to determine candidate intervals. An alternating mapping method is used to generate a mapping table. Key generation is performed by combining the encoded sequence and the original index. Error correction is performed by utilizing the reliability differences of channel features, thereby improving key consistency and generation rate.
It significantly improves key consistency under high signal-to-noise ratio conditions, reduces key inconsistency rate at eavesdropping terminals, enhances network system security and channel utilization, and ensures the speed and reliability of key generation.
Smart Images
Figure CN121585367B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of networking technology and relates to a reliable alternating mapping key extraction method and system for multi-robot self-organizing networks. Background Technology
[0002] Currently, robots are transitioning from individual operations to multi-robot collaboration and higher levels of autonomy. To achieve low-latency and highly reliable information exchange between different nodes, cluster self-organizing networks are widely adopted as a key technology for underlying communication. In this context, wireless links within the cluster exhibit characteristics such as high mobility, rapid topology changes, and short coherence times. Simultaneously, as a distributed intelligent system integrating communication, sensing, and computing, the open nature of this network also brings more complex security threats. Existing security systems based on high-level encryption face challenges such as high key distribution and management overhead and insufficient real-time performance when dealing with massive numbers of nodes and dynamic topologies. Therefore, there is an urgent need to establish new security protection mechanisms at the physical layer. Unlike cryptographic encryption techniques, physical layer security utilizes channel characteristics to extract keys without requiring third-party key distribution and management, providing security at the signal layer. However, under non-ideal factors such as high-speed robot movement and hardware inconsistencies, channel reciprocity may be compromised, becoming a major challenge for existing physical layer solutions.
[0003] To address this issue, existing research has focused on improving key source quality through preprocessing: one approach uses principal component analysis (PCA) to reduce the dimensionality of channel probe data, mapping the original samples to the principal component space to extract common features and suppress noise and interference; another approach utilizes discrete cosine transform (DCT) to extract reciprocal features in the frequency domain, leveraging energy concentration effects to select a small number of low-frequency coefficients as features for key generation, thereby mitigating the impact of non-ideals on key consistency to some extent. The commonality among these schemes is that they first perform linear transformation and dimensionality reduction on the original channel sequence, and then complete quantization and negotiation in the transform domain. Furthermore, some schemes involve sending a specified interaction sequence, adjusting the original channel sequence at the receiving end, and using soft decoding to extract a consistent security key.
[0004] While the above schemes improve key generation consistency to some extent, they still have the following shortcomings: Mainstream schemes still follow the basic process of physical layer key extraction: channel probing, feature quantization, key negotiation, and security amplification. The quantization stage inevitably introduces threshold errors and information loss, which leads to repeated information exchanges during the key negotiation stage, resulting in key leakage and threatening system security.
[0005] Furthermore, some studies skip the quantization stage and introduce soft decoding to enhance key consistency. However, due to the high probability of inconsistency in the tail bits, it is usually necessary to truncate the tail bits to ensure key consistency. In wireless links within a cluster, this scheme must truncate more tail bits to guarantee high key consistency, directly leading to a sharp decrease in the key generation rate. Summary of the Invention
[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a reliable alternating mapping key extraction method and related apparatus for multi-robot self-organizing networks. The method and related apparatus have high consistency in key generation, fast generation rate, and high security of the network system.
[0007] To achieve the above objectives, this invention discloses a reliable alternating mapping key extraction method for multi-robot ad hoc networks, comprising:
[0008] Obtain the channel feature sequence ha from the transmitting end, the channel feature sequence hb from the receiving end, and the encoded sequence kA from the transmitting end;
[0009] The channel features in the channel feature sequence ha are sorted in ascending order of amplitude to obtain the sorted vector hA and the original index idex of each position in the vector hA. The flip probability of each position in the sorted vector hA is calculated and the flip probability of each position in the sorted vector hA is used as the reliability index of each position in the sorted vector hA.
[0010] Candidate intervals are determined based on the reliability indices of each position in the sorted vector hA;
[0011] A mapping table S is generated by alternating sampling of the candidate interval, the encoded sequence kA, and the original index idex.
[0012] A security key kb is generated based on the mapping table S and the channel feature sequence hb.
[0013] Furthermore, the process of obtaining the channel feature sequence ha from the transmitting end and the channel feature sequence hb from the receiving end is as follows:
[0014] The transmitting end and the receiving end alternately transmit pilot signals within a coherent time period to obtain the channel characteristic sequence ha of the transmitting end and the channel characteristic sequence hb of the receiving end.
[0015] Furthermore, the process of obtaining the encoded sequence kA from the sending end is as follows:
[0016] The sending end generates a preset key ka, and performs convolutional coding on the preset key ka to obtain the encoding sequence kA of the sending end.
[0017] Furthermore, the flip probability P(i) of position i in the sorted vector hA is:
[0018]
[0019] in, Represents the standard normal distribution function. Indicates the noise variance. This represents the value of position i in the sorted vector hA.
[0020] Furthermore, the process of determining the candidate interval based on the reliability index of each position in the sorted vector hA is as follows:
[0021] A candidate set is constructed based on the reliability index of each position in the sorted vector hA;
[0022] Determine the boundary positions begin0 and end0 in the candidate set;
[0023] Candidate intervals are constructed based on the boundary positions begin0 and end0 in the candidate set.
[0024] Furthermore, the process of generating the security key kb based on the mapping table S and the channel feature sequence hb is as follows:
[0025] The channel feature sequence hb is permuted according to the mapping table S to obtain the sequence hb', and the sequence hb' is decoded to obtain the security key kb.
[0026] This invention discloses a reliable alternating mapping key extraction system for multi-robot self-organizing networks, comprising:
[0027] The acquisition module is used to acquire the channel feature sequence ha from the transmitting end, the channel feature sequence hb from the receiving end, and the encoding sequence kA from the transmitting end.
[0028] The calculation module is used to sort the channel features in the channel feature sequence ha according to the amplitude from smallest to largest, to obtain the sorted vector hA and the original index idex of each position in the vector hA, to calculate the flip probability of each position in the sorted vector hA, and to use the flip probability of each position in the sorted vector hA as the reliability index of each position in the sorted vector hA.
[0029] The determination module is used to determine the candidate interval based on the reliability index of each position in the sorted vector hA;
[0030] The first generation module is used to generate a mapping table S by alternating sampling of the candidate interval, the encoded sequence kA and the original index idex.
[0031] The second generation module is used to generate a security key kb based on the mapping table S and the channel feature sequence hb.
[0032] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the reliable alternating mapping key extraction method for the multi-robot ad hoc network.
[0033] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the reliable alternating mapping key extraction method for a multi-robot ad hoc network.
[0034] The present invention has the following beneficial effects:
[0035] In practical operation, the reliable alternating mapping key extraction method and related apparatus for multi-robot ad hoc networks of the present invention determines candidate intervals based on the reliability index of each position in the sorted vector hA to quantify the risk of errors occurring at that position during key extraction, providing a basis for subsequent mapping table generation. Then, a mapping table S is generated by alternating mapping using the candidate intervals, the encoded sequence kA, and the original index idex. Alternating mapping can maximize the error correction effect during path search, thereby achieving higher key consistency. Finally, a security key kb is generated based on the mapping table S and the channel feature sequence hb. The generation rate is fast, and the security of the network system is high. Attached Figure Description
[0036] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0037] Figure 1 This is a flowchart of the method of the present invention;
[0038] Figure 2 This is a schematic diagram of the sorted channel feature sequence;
[0039] Figure 3 This is a graph showing the change in key inconsistency rate as a function of signal-to-noise ratio.
[0040] Figure 4 This is a graph showing the change in key consistency rate as a function of channel correlation coefficient.
[0041] Figure 5 This is a graph showing how the key inconsistency rate changes with a threshold.
[0042] Figure 6 A graph showing the change in the number of keys generated as a function of a threshold.
[0043] Figure 7 This is a system structure diagram of the present invention. Detailed Implementation
[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0045] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.
[0046] Example 1
[0047] refer to Figure 1 This invention provides a reliable method for extracting alternating mapping keys in a multi-robot ad hoc network, comprising the following steps:
[0048] 1) Obtain the channel feature sequence ha from the transmitting end, the channel feature sequence hb from the receiving end, and the coding sequence kA from the transmitting end;
[0049] The transmitting end and the receiving end alternately transmit pilot signals within the coherent time, thereby obtaining the channel feature sequence ha of the transmitting end and the channel feature sequence hb of the receiving end, wherein the length of the channel feature sequence ha and the length of the channel feature sequence hb are both N.
[0050] The sending end generates a preset key ka, the length of which is Where R is the encoding rate, the preset key ka is convolutionally encoded to obtain the encoded sequence kA, the length of the encoded sequence kA is N; the receiving end uses Viterbi decoding.
[0051] 2) Sort each channel feature in the channel feature sequence ha according to the amplitude from smallest to largest to obtain the sorted vector hA and the original index idex of each position in the vector hA, and calculate the reliability index of each position in the sorted vector hA.
[0052] The transmitting end sorts the channel features in the channel feature sequence ha according to their amplitude from smallest to largest, obtaining the sorted vector hA and the original index idex of each position in the vector hA. Let the noise variance be... Calculate the flip probability for each position in the sorted vector hA, where the flip probability P(i) of position i in the sorted vector hA is:
[0053]
[0054] in, Represents the standard normal distribution function. Let represent the value at position i in the sorted vector hA. Intuitively, the larger the amplitude value of the channel feature sequence, the lower the probability of incorrect decoding due to noise, indicating that position i is more reliable. That is, the reliability index is:
[0055]
[0056] It should be noted that the reliability index and the flip probability are complementary to each other, and the channel reliability information they represent is equivalent. Therefore, P(i) will be used uniformly thereafter.
[0057] 3) Determine the candidate interval based on the reliability index of each position in the sorted vector hA;
[0058] A threshold thod is selected based on the signal-to-noise ratio of the real-time channel environment, and a candidate set is constructed. B ;
[0059]
[0060] Wherein, the candidate set B The set contains M elements, and the candidate set is recorded. B The boundary positions are begin0 and end0. Non-candidate indices are discarded directly. In the candidate set... B In this context, elements closer to the boundary have lower reliability, while elements closer to both ends have higher reliability, such as... Figure 2 As shown.
[0061] 4) Generate a mapping table S by alternating sampling of the candidate interval, the encoded sequence kA, and the original index idex;
[0062] refer to Figure 2 The candidate interval is divided into four boundary segments m, n, j, and k. Four pointers and a state indicator id are initialized, thus forming intervals mn, nj, and jk.
[0063]
[0064] The process of generating mapping table S is as follows:
[0065] From i to M, when kA[i] = 0, if id = 0, then S[i] = idex[m], m increases by 1, and id is set to 1; if id = 1, then S[i] = idex[n], n decreases by 1, and id is set to 0.
[0066] When kA[i] = 1, if id = 1, then S[i] = idex[j], j increases by 1, and id is set to 0; if id = 0, then S[i] = idex[k], k decreases by 1, and id is set to 1; if m ≥ n or j ≥ k, then the mapping table S is generated.
[0067] Where M is the number of elements in the candidate set, idex is the original index, id=0 indicates priority selection from the reliable side, and id=1 indicates priority selection from the unreliable side. By alternating between "reliable" and "unreliable" selection, this invention enables faster convergence to the correct path even with a large number of errors, significantly improving key consistency.
[0068] 5) Generate the security key kb based on the mapping table S and the channel feature sequence hb. The specific process is as follows:
[0069] The sending end sends the generated mapping table S to the receiving end;
[0070] The receiver permutes the channel feature sequence hb according to the mapping table S to obtain the sequence hb', and then decodes the sequence hb' to obtain the security key kb.
[0071] Verification test
[0072] To evaluate the differences between the present invention and existing technologies, a key extraction scheme based on soft decoding was selected as a benchmark. This scheme also employs convolutional codes and Viterbi decoding, and uses a truncation operation to ensure high key consistency. During the evaluation process, the number of keys generated by both schemes was kept constant under various signal-to-noise ratio conditions. The key inconsistency rates extracted from legitimate links were compared, and the results are as follows: Figure 3 As shown, from Figure 3 As can be seen, compared with the baseline scheme, the present invention can significantly improve the key consistency of legitimate users, and the gain of the present invention is further enhanced with the improvement of the signal-to-noise ratio. If the same number of keys is generated as in the present invention, the baseline scheme needs to truncate more tail bits to maintain consistency, thereby sacrificing channel utilization efficiency; while the present invention does not increase any communication overhead, and through the alternating selection and channel mapping mechanism, it distributes noise to different branch metrics, effectively improving channel utilization and key consistency.
[0073] To verify the security performance of this invention, the key consistency rate of the eavesdropping terminal under a given signal-to-noise ratio environment is analyzed. Assuming that the eavesdropping channel and the main channel have a certain spatial correlation, the channel can be modeled as follows:
[0074]
[0075] in, It is a legitimate channel; The correlation coefficient between the main channel and the eavesdropping channel; It follows a standard normal distribution.
[0076] The key consistency rates of Alice-Bob (legitimate link) and Alice-Eve (eavesdropping link) were evaluated under signal-to-noise ratio (SNR) conditions of 10dB and 20dB, and the results are as follows: Figure 4 As shown, experimental results indicate that under various channel correlation coefficients, the key consistency rate of the legitimate link is close to 1, while the consistency rate of the eavesdropping link remains around 0.5, approaching the level of random guessing. This demonstrates that even if the eavesdropper fully understands the mapping table, it is difficult to recover the legitimate key, thus verifying the security of this invention. With the increasing correlation coefficient between the main channel and the eavesdropping channel... While the consistency rate of the eavesdropping end increases slightly with the increase in channel correlation, it remains significantly lower than that of the legitimate end. This invention, to a certain extent, mitigates the security weakening effect of channel correlation. Therefore, this invention significantly improves the key inconsistency rate of the eavesdropping end while ensuring key consistency at the legitimate end, thereby providing robust physical layer security for clustered self-organizing networks.
[0077] To evaluate the key extraction performance of legitimate links under different threshold conditions, both communicating parties discard samples with reliability indices exceeding a set threshold. A lower threshold retains fewer original channel features and results in a higher key consistency rate, but a correspondingly lower key generation rate. In practical communication, an appropriate threshold should be selected based on channel conditions. Taking a convolutional code with a code rate of 1 / 2 as an example, with a channel estimation sequence length N of 30000, the key inconsistency rate and the number of key generation operations under different thresholds are as follows: Figure 5 and Figure 6 As shown, by Figure 5 and Figure 6 It can be seen that as the threshold increases, the consistency of key acquisition on legitimate links decreases, but the number of keys generated increases accordingly. The higher the signal-to-noise ratio (SNR), the lower the impact of the threshold selection on the number of keys generated. Therefore, we can draw the following conclusions: under high SNR conditions, choose a higher threshold to ensure the number of keys generated; under low SNR conditions, choose a lower threshold to ensure the key consistency rate.
[0078] Example 2
[0079] refer to Figure 7The reliable alternating mapping key extraction system for multi-robot self-organizing networks of the present invention includes:
[0080] The acquisition module is used to acquire the channel feature sequence ha from the transmitting end, the channel feature sequence hb from the receiving end, and the encoding sequence kA from the transmitting end.
[0081] The calculation module is used to sort the channel features in the channel feature sequence ha according to the amplitude from smallest to largest, to obtain the sorted vector hA and the original index idex of each position in the vector hA, to calculate the flip probability of each position in the sorted vector hA, and to use the flip probability of each position in the sorted vector hA as the reliability index of each position in the sorted vector hA.
[0082] The determination module is used to determine the candidate interval based on the reliability index of each position in the sorted vector hA;
[0083] The first generation module is used to generate a mapping table S by alternating sampling of the candidate interval, the encoded sequence kA and the original index idex.
[0084] The second generation module is used to generate a security key kb based on the mapping table S and the channel feature sequence hb.
[0085] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.
[0086] Example 3
[0087] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a reliable alternating mapping key extraction method for a multi-robot ad hoc network. For example, the method includes: acquiring a channel feature sequence ha from a transmitting end, a channel feature sequence hb from a receiving end, and an encoding sequence kA from a transmitting end; sorting each channel feature in the channel feature sequence ha according to its amplitude from smallest to largest, obtaining a sorted vector hA and the original index idex of each position in the vector hA; calculating the flip probability of each position in the sorted vector hA; using the flip probability of each position in the sorted vector hA as a reliability index for each position in the sorted vector hA; determining candidate intervals based on the reliability indexes of each position in the sorted vector hA; generating a mapping table S by sampling alternating mapping according to the candidate intervals, the encoding sequence kA, and the original index idex; and generating a security key kb based on the mapping table S and the channel feature sequence hb. The memory may include main memory, such as high-speed random access memory (RAM), or non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which may be an industry-standard architecture bus, a peripheral component interconnection standard bus, or an extended industry-standard architecture bus. The bus can be categorized as an address bus, data bus, or control bus. The memory stores programs; specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor.
[0088] Example 4
[0089] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a reliable alternating mapping key extraction method for a multi-robot ad hoc network. For example, the method includes: acquiring a channel feature sequence ha from a transmitting end, a channel feature sequence hb from a receiving end, and an encoding sequence kA from a transmitting end; sorting each channel feature in the channel feature sequence ha according to its amplitude from smallest to largest, obtaining a sorted vector hA and an original index idex for each position in the vector hA; calculating the flip probability of each position in the sorted vector hA; using the flip probability of each position in the sorted vector hA as a reliability index for each position in the sorted vector hA; determining candidate intervals based on the reliability indexes of each position in the sorted vector hA; generating a mapping table S by sampling alternating mapping according to the candidate intervals, the encoding sequence kA, and the original index idex; and generating a security key kb based on the mapping table S and the channel feature sequence hb. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.
[0090] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.
[0091] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.
[0092] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.
Claims
1. A reliable method for extracting alternating mapping keys in a multi-robot ad hoc network, characterized in that, include: Obtain the channel feature sequence ha from the transmitting end, the channel feature sequence hb from the receiving end, and the encoded sequence kA from the transmitting end; The channel features in the channel feature sequence ha are sorted in ascending order of amplitude to obtain the sorted vector hA and the original index idex of each position in the vector hA. The flip probability of each position in the sorted vector hA is calculated and the flip probability of each position in the sorted vector hA is used as the reliability index of each position in the sorted vector hA. Candidate intervals are determined based on the reliability indices of each position in the sorted vector hA; A mapping table S is generated by alternating sampling of the candidate interval, the encoded sequence kA, and the original index idex. A security key kb is generated based on the mapping table S and the channel feature sequence hb. The flip probability P(i) of position i in the sorted vector hA is: in, Represents the standard normal distribution function. Indicates the noise variance. This represents the value at position i in the sorted vector hA; The process of determining the candidate interval based on the reliability index of each position in the sorted vector hA is as follows: A candidate set is constructed based on the reliability index of each position in the sorted vector hA; Determine the boundary positions begin0 and end0 in the candidate set; Construct candidate intervals based on the boundary positions begin0 and end0 in the candidate set; The process of generating the security key kb based on the mapping table S and the channel feature sequence hb is as follows: The channel feature sequence hb is permuted according to the mapping table S to obtain the sequence hb', and the sequence hb' is decoded to obtain the security key kb.
2. The reliable alternating mapping key extraction method for multi-robot self-organizing networks according to claim 1, characterized in that, The process of obtaining the channel feature sequence ha from the transmitting end and the channel feature sequence hb from the receiving end is as follows: The transmitting end and the receiving end alternately transmit pilot signals within a coherent time period to obtain the channel characteristic sequence ha of the transmitting end and the channel characteristic sequence hb of the receiving end.
3. The reliable alternating mapping key extraction method for multi-robot self-organizing networks according to claim 1, characterized in that, The process of obtaining the encoded sequence kA from the sending end is as follows: The sending end generates a preset key ka, and performs convolutional coding on the preset key ka to obtain the encoding sequence kA of the sending end.
4. A reliable alternating mapping key extraction system for multi-robot self-organizing networks, characterized in that, include: The acquisition module is used to acquire the channel feature sequence ha from the transmitting end, the channel feature sequence hb from the receiving end, and the encoding sequence kA from the transmitting end. The calculation module is used to sort the channel features in the channel feature sequence ha according to the amplitude from smallest to largest, to obtain the sorted vector hA and the original index idex of each position in the vector hA, to calculate the flip probability of each position in the sorted vector hA, and to use the flip probability of each position in the sorted vector hA as the reliability index of each position in the sorted vector hA. The determination module is used to determine the candidate interval based on the reliability index of each position in the sorted vector hA; The first generation module is used to generate a mapping table S by alternating sampling of the candidate interval, the encoded sequence kA and the original index idex. The second generation module is used to generate a security key kb based on the mapping table S and the channel feature sequence hb. The flip probability P(i) of position i in the sorted vector hA is: in, Represents the standard normal distribution function. Indicates the noise variance. This represents the value at position i in the sorted vector hA; The process of determining the candidate interval based on the reliability index of each position in the sorted vector hA is as follows: A candidate set is constructed based on the reliability index of each position in the sorted vector hA; Determine the boundary positions begin0 and end0 in the candidate set; Construct candidate intervals based on the boundary positions begin0 and end0 in the candidate set; The process of generating the security key kb based on the mapping table S and the channel feature sequence hb is as follows: The channel feature sequence hb is permuted according to the mapping table S to obtain the sequence hb', and the sequence hb' is decoded to obtain the security key kb.
5. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the reliable alternating mapping key extraction method for multi-robot ad hoc networks as described in any one of claims 1-3.
6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the reliable alternating mapping key extraction method for multi-robot ad hoc networks as described in any one of claims 1-3.