Wireless communication encryption method combined with block chain technology

Abstract

The invention relates to the field of combination of wireless communication and block chain technology, and discloses a wireless communication encryption method combined with block chain technology, comprising the following steps: initializing system parameters including key length, security requirement, delay limit and resource budget; constructing an optimization objective function for optimizing encryption delay, block chain synchronization delay and resource consumption in wireless communication, and improving encryption security at the same time; constructing constraint conditions, wherein the constraint conditions comprise an encryption security lower limit, a delay limit and a resource budget; solving the optimization objective function by using a mathematical optimization model to obtain an optimal encryption and block chain configuration strategy; and establishing a multi-agent game model, and optimizing an interaction strategy of the wireless communication node and the block chain node. According to the method, encryption and block chain parameters are dynamically adjusted, a multi-body interaction strategy is optimized, and a mathematical optimization model is constructed, so that global optimization of security, delay and resource consumption and improvement of balance adaptive capacity are realized.

Description

Technical Field

[0001] The present invention relates to the field of combining wireless communication with blockchain technology, and specifically to a wireless communication encryption method combined with blockchain technology. Background Art

[0002] With the rapid development of wireless communication technology and blockchain technology, they have been widely used in scenarios such as the Internet of Things, financial payments, and drone networks. In these scenarios, secure data transmission and trusted storage have become indispensable requirements. Wireless communication systems provide efficient data transmission capabilities, while blockchain technology ensures data integrity and credibility with its decentralized and tamper-proof characteristics. However, in practical applications, the combination of the two faces complex performance trade-offs.

[0003] In the practice of combining wireless communication and blockchain technology, existing technologies have proposed a variety of solutions. For example, by adopting a fixed key encryption method, a certain degree of data security can be provided while reducing the computational complexity of the encryption process; by optimizing the blockchain consensus algorithm, the synchronization delay of the blockchain can be reduced to a certain extent; in addition, some technical solutions also improve the efficiency and throughput of the wireless communication and blockchain combined system by adjusting bandwidth allocation and the number of participating nodes. These technologies have significant advantages in specific scenarios and provide a reference for the performance optimization of distributed systems.

[0004] However, existing technologies still have obvious shortcomings in realizing the combination of wireless communication and blockchain. First, existing technologies lack flexibility in the design of encryption methods. The key length and encryption algorithm are often fixed, which makes it impossible to dynamically adapt to the security requirements of different scenarios. Secondly, blockchain performance optimization only focuses on a single indicator, such as latency or throughput, lacks systematic consideration of global performance, and is difficult to achieve balance among multiple objectives. In addition, the strategy optimization between nodes mostly adopts an isolated design, without fully considering the interaction between nodes, resulting in poor global performance coordination. Finally, the dynamic adaptability of existing technologies is limited. When faced with dynamic environments such as network delays, bandwidth fluctuations, or resource constraints, parameter configurations cannot be adjusted in a timely manner, which easily leads to performance degradation. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a wireless communication encryption method combined with blockchain technology, which solves the problems in the prior art such as the lack of flexibility of encryption schemes, the limitation of blockchain performance optimization to a single indicator, the lack of collaborative strategies between nodes, and the insufficient adaptability in dynamic environments.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a wireless communication encryption method combined with blockchain technology, comprising the following steps:

[0007] Initialize system parameters, including key length, security requirements, delay constraints, and resource budget;

[0008] Construct an optimization objective function to optimize encryption latency, blockchain synchronization latency, and resource consumption in wireless communications while improving encryption security;

[0009] Constructing constraints, wherein the constraints include a cryptographic security lower bound, a latency limit, and a resource budget;

[0010] Use mathematical optimization models to solve the optimization objective function and obtain the optimal encryption and blockchain configuration strategy;

[0011] Establish a multi-agent game model, optimize the interaction strategies of wireless communication nodes and blockchain nodes, and obtain the global optimal equilibrium strategy;

[0012] Implement dynamic policy adjustments to adjust encryption and blockchain parameters based on real-time changes in the communication environment.

[0013] Preferably, the optimization objective function includes:

[0014] Latency target, which is used to minimize the total latency in the encryption process, including blockchain consensus latency, encryption computation latency, and communication network latency;

[0015] Resource consumption goals, used to minimize the use of computing resources, communication bandwidth resources, and storage resources;

[0016] The security goal is to maximize the key entropy of communication encryption, thereby improving encryption security.

[0017] Preferably, the constraints include:

[0018] Determine the lower limit of encryption security and calculate the key entropy value, which is determined by the key length and the size of the key space;

[0019] Set security constraints to ensure that the key entropy value is not lower than the preset encryption security requirement, which is defined according to the specific application scenario;

[0020] Set delay limits, count the delay indicators of the communication network, and calculate the total delay by combining blockchain consensus delay, encryption calculation delay, and communication network delay;

[0021] Set delay constraints to ensure that the total delay does not exceed the maximum allowable delay of the system real-time performance;

[0022] Analyze the computing power, bandwidth resources, and storage resources of the device, and count resource usage;

[0023] Set resource budget constraints to ensure that the total resource consumption of the device does not exceed the preset resource budget, including computing resources, communication bandwidth resources, and storage resources;

[0024] Security constraints, delay constraints, and resource budget constraints are uniformly modeled as constraints of the optimization problem and used as input parameters of the optimization objective function to participate in the final strategy solution.

[0025] Preferably, the mathematical optimization model is solved by an iterative optimization algorithm, including:

[0026] Initialize optimization variables and set initial values ​​of key length, blockchain consensus delay, encryption delay, and communication delay;

[0027] According to the optimization objective function, calculate the partial derivative of each optimization variable and determine the optimization direction;

[0028] By iteratively updating the optimization variables, the optimal solution is gradually approached;

[0029] When the optimization result meets the preset accuracy conditions, the optimized solution is output.

[0030] Preferably, the multi-agent game model includes:

[0031] Consider wireless communication nodes and blockchain nodes as game entities, establish the objective function of each entity, and optimize its latency, resource consumption, and encryption security;

[0032] Fix the strategy of a certain game subject and optimize the strategies of other game subjects until a global equilibrium is achieved;

[0033] When the strategies of all game players reach equilibrium, the Nash equilibrium solution is output.

[0034] Preferably, the dynamic strategy adjustment includes:

[0035] Real-time monitoring of the communication environment’s latency, bandwidth, and device resource usage;

[0036] Dynamically adjust the weight parameters in the optimization objective function according to the monitoring results and recalculate the optimization solution;

[0037] When the communication environment changes, the key length, blockchain consensus parameters and communication delay optimization strategy are updated in real time.

[0038] Preferably, the encryption security is represented by a key entropy value, which is associated with the key length and the size of the key space and is used to measure the anti-cracking ability of the encryption system:

[0039] Calculate blockchain synchronization delay: By selecting and configuring the blockchain consensus algorithm, determine the block time, number of nodes, and synchronization efficiency, and then calculate the blockchain synchronization delay;

[0040] Calculate encryption calculation delay: Determine encryption calculation delay based on the calculation complexity of the selected encryption algorithm and the dynamically adjusted key length, combined with the computing performance of the device;

[0041] Calculate communication network delay: Calculate the network transmission delay generated during the communication process based on the communication bandwidth, transmission data volume and network status;

[0042] Determine resource consumption: Calculate total resource consumption by counting the computing consumption of the device, communication bandwidth usage, and blockchain storage consumption;

[0043] Represents the total delay: Add the blockchain synchronization delay, encryption calculation delay and communication network delay to get the total delay of the communication system.

[0044] Preferably, the construction of the optimization objective function is used to optimize encryption delay, blockchain synchronization delay and resource consumption in wireless communication, while improving encryption security, specifically including:

[0045] Determine blockchain synchronization delay through blockchain consensus algorithm;

[0046] The encryption calculation delay is determined by the calculation complexity of the encryption algorithm and the key length;

[0047] Determine communication network latency based on communication bandwidth and data volume;

[0048] The total delay is the sum of blockchain synchronization delay, encryption calculation delay and communication network delay.

[0049] Preferably, the iterative optimization algorithm adopts a gradient descent method for solving, which specifically includes:

[0050] Initialize optimization variables and step size parameters;

[0051] Calculate the gradient value according to the optimization objective function;

[0052] Adjust the variable value in the optimization direction until the modulus of the gradient value meets the convergence condition.

[0053] Preferably, the initialization system parameters include:

[0054] Determine the initial value of the key length, and select a key length that meets the lower limit of encryption security based on the security requirements, key space size, and encryption algorithm characteristics in the application scenario;

[0055] Set security requirements, combine the sensitivity level of communication data and potential attack threats, and define the minimum key entropy value as a security constraint;

[0056] Determine the delay limit. Combined with the real-time requirements in the application scenario, set the maximum allowable value of the total delay by collecting historical data on blockchain synchronization delay, encryption calculation delay, and communication network delay;

[0057] Set resource budgets, combining the computing power, communication bandwidth, and storage capacity of the device to define the maximum available values ​​of computing resources, bandwidth resources, and storage resources;

[0058] Initialize the weight parameters and assign delay weight, security weight, and resource consumption weight according to the system's priority requirements for delay, security, and resource consumption optimization to ensure that the optimization goals match the requirements of the application scenario.

[0059] The present invention provides a wireless communication encryption method combined with blockchain technology. It has the following beneficial effects:

[0060] 1. The present invention uses a multi-agent game model to optimize the interaction strategy between wireless communication nodes and blockchain nodes, achieving the technical effect of global optimal equilibrium. Compared with the technical solution of independent optimization strategy of a single node in the prior art, it solves the problems of strategy conflict between nodes and uneven global resource allocation, thereby improving the coordination and overall performance of the system.

[0061] 2. The present invention achieves the technical effect of flexible adaptation in complex environments by dynamically adjusting encryption and blockchain parameters and recalculating the optimal strategy based on real-time monitoring of communication environment changes. Compared with the technical solutions of fixed encryption configuration or static blockchain parameters in the prior art, it solves the problem of performance degradation caused by network fluctuations or resource constraints, and significantly improves the stability and real-time performance of the system.

[0062] 3. The present invention constructs a mathematical optimization model with latency, security and resource consumption as the core, and uses iterative solution technology to obtain the optimal configuration, achieving the technical effect of multi-objective balanced optimization. Compared with the optimization method in the prior art that only focuses on a single performance indicator, it solves the problem of lack of overall consideration in multi-objective optimization scenarios, enabling the system to achieve a dynamic balance between performance and resource utilization in different scenarios.

[0063] 4. The present invention uses key entropy to quantify security and adjusts key length and encryption algorithm in combination with actual scenarios, achieving a technical effect of effectively balancing security and computing resources. Compared with the technical solution in the prior art that simply increases key length and wastes resources, it solves the contradiction between high security requirements and limited resource conditions, and provides a more reasonable encryption solution for resource-constrained wireless devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is one of the flow charts of the method of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] Please see attached Figure 1 , an embodiment of the present invention provides a wireless communication encryption method combined with blockchain technology, comprising the following steps:

[0067] S1. Initialize system parameters, including key length, security requirements, delay constraints, and resource budget;

[0068] Wireless communication encryption methods require that the key parameters of the system be initialized reasonably at the beginning. The purpose of initializing system parameters is to provide initial conditions for subsequent optimization calculations and ensure that the system can perform effective strategy solving under the premise of meeting specific security, real-time and resource budget requirements. These initialization parameters include but are not limited to key length, security requirements, delay constraints and resource budgets.

[0069] In general, the initialization of system parameters needs to be combined with the needs of actual application scenarios. For example, in high-security applications, longer key lengths need to be set; in applications with high real-time requirements, delay indicators need to be more strictly limited; for resource-constrained devices, more attention needs to be paid to the allocation and utilization of resource budgets. As an option, the initialization of these parameters can be reasonably set through historical data analysis, actual environment monitoring, and system computing power evaluation.

[0070] Specifically, the present invention describes in detail the initialization method of each parameter as follows.

[0071] In this embodiment, the key length K is a key parameter that affects the encryption security and computational complexity of the system. Generally, the initial value of the key length needs to meet the encryption security requirements while considering the computational resource constraints of the system.

[0072] In some embodiments, the initial value of the key length may be set according to the following formula:

[0073]

[0074] Among them, H(K) is the key entropy, K is the key length (unit: bit), is the size of the key space.

[0075] As an alternative, assume that a minimum security requirement S is required. min , then the initial key length must satisfy:

[0076]

[0077] Specifically, if the key space Size and minimum security requirement S min =128 bits, then the minimum value of the initial key length K is:

[0078]

[0079] In another possible implementation, for high-security scenarios, a higher key length may be selected, such as 256 bits or 512 bits. These key lengths can effectively improve the system's anti-cracking capability, but will also increase the consumption of computing resources.

[0080] In this embodiment, security requires a minimum value S of the key entropy. min In general, security requirements are determined by the data sensitivity and potential security threats in the application scenario. For example, in ordinary data transmission, the minimum security requirement can be set to 128 bits; while in communication scenarios involving sensitive information, it can be set to 256 bits or higher.

[0081] In some embodiments, the setting of security requirements can be determined by historical attack case analysis, communication data importance assessment, etc. As an option, when the target scenario needs to resist quantum computing attacks, a quantum-resistant encryption algorithm can be used, and the recommended minimum security requirement is usually above 256 bits.

[0082] Specifically, security requirements directly affect the choice of key length. If higher security is required in the application scenario, the key length K can be appropriately increased or the key space can be expanded.

[0083] In this embodiment, the delay limit is mainly for the total delay, which includes blockchain synchronization delay, encryption calculation delay and communication network delay. In general, the total delay needs to meet the system's real-time requirements.

[0084] Alternatively, the total delay can be calculated using the following formula:

[0085] T total =T bc +T enc +Tcomm

[0086] in:

[0087] T total is the total delay (in seconds);

[0088] T bc The blockchain synchronization delay depends on the efficiency of the consensus algorithm, the number of nodes, and the block time;

[0089] T enc The encryption calculation delay is related to the key length K and the computing performance of the device;

[0090] T comm It is the communication network delay, which is determined by bandwidth, data volume and network status.

[0091] In some embodiments, the delay limit T max The initial value of can be obtained through statistical analysis of historical communication data. For example, in real-time video communication scenarios, the delay limit is usually required to be less than 50 milliseconds, while in ordinary data transmission, it can be relaxed to 200 milliseconds.

[0092] Specifically, in one possible implementation, the blockchain synchronization delay and communication network delay can be optimized in combination with the scenario. For example, by adjusting the block time of the blockchain, the blockchain synchronization delay can be reduced; by compressing the data volume, the communication network delay can be reduced.

[0093] In this embodiment, the resource budget includes computing resources, communication bandwidth resources and storage resources. Generally, the initialization of the resource budget needs to be reasonably allocated in combination with device performance and network conditions.

[0094] In some embodiments, the resource budget P is calculated comp The initial value of can be obtained by analyzing the computing power of the device. For example, for ordinary IoT devices, the computing resource budget can be set to 5 watts, while for high-performance communication devices, it can be increased to more than 10 watts.

[0095] As an option, the communication bandwidth budget P bw It can be determined by data transmission requirements and network bandwidth conditions. For example, in high-bandwidth scenarios, the communication bandwidth budget can be appropriately increased to meet real-time data transmission requirements.

[0096] Specifically, the initialization formula of the resource budget can be expressed as:

[0097] P total =P comp +P bw +P bc

[0098] in:

[0099] P total budget for total resources;

[0100] P comp budgeting for computing resources;

[0101] P bw budget for communication bandwidth;

[0102] P bc Budgeting for blockchain storage.

[0103] In one possible implementation, the proportion of each resource budget can be dynamically adjusted based on the scenario requirements. For example, in a scenario with low storage requirements, the blockchain storage budget can be appropriately reduced to allocate more resources to computing and communication bandwidth.

[0104] S2. Construct an optimization objective function to optimize encryption delay, blockchain synchronization delay and resource consumption in wireless communication, while improving encryption security;

[0105] Optimizing the objective function is the core link to achieve wireless communication encryption and blockchain synchronization performance optimization. By optimizing the objective function, a dynamic balance can be achieved between satisfying delay, security and resource consumption, and the overall performance of the system can be improved. In general, the construction of the optimization objective function needs to fully consider the multi-dimensional requirements of the system, including the real-time nature of the delay, the strength of security, and the controllability of resource consumption. As an option, the present invention adjusts the priority of the optimization target by weight distribution in combination with the needs of specific application scenarios, so as to meet the actual needs in different scenarios.

[0106] Specifically, the core of the optimization objective function is to comprehensively quantify latency, security, and resource consumption. The present invention constructs a mathematical expression to uniformly represent encryption latency, blockchain synchronization latency, communication network latency, and the consumption of computing resources, bandwidth resources, and storage resources. At the same time, through the introduction of security objectives, the optimization of key entropy values ​​is used as the core indicator of the system's encryption strength. In the specific implementation of the optimization objective function, the present invention fully combines the technical advantages of optimization algorithms such as gradient descent and dynamic weight adjustment, making this method highly versatile in multi-scenario applications.

[0107] In this embodiment, the optimization objective function is expressed in the following form:

[0108] J(x)=α1C d (x)+α2C r (x)-α3C s (x)

[0109] in:

[0110] J(x) is the overall objective function, which represents the weighted comprehensive value of delay, resource consumption and security;

[0111] C d (x) is the delay cost, including blockchain synchronization delay, encryption calculation delay and communication network delay;

[0112] C r (x) is the resource consumption cost, including the total consumption of computing resources, bandwidth resources, and storage resources;

[0113] C s (x) is the security benefit, represented by the key entropy value;

[0114] α1, α2, and α3 are weight coefficients, which respectively represent the importance of latency, security, and resource consumption in the optimization objective.

[0115] In general, the delay cost C d (x) is an important component of the optimization objective and is used to quantify the time cost of the encryption process. In the present invention, the delay cost can be expressed as:

[0116] C d (x) = T bc +T enc +T comm

[0117] in:

[0118] T bc Indicates the blockchain synchronization delay, which is determined by the efficiency of the blockchain consensus algorithm, the number of nodes, and the block time;

[0119] T enc represents the encryption calculation delay, which depends on the key length K and the computational complexity of the encryption algorithm;

[0120] T comm Indicates the communication network delay, which is affected by the data volume, communication bandwidth and network status.

[0121] In one possible implementation, in order to reduce the blockchain synchronization delay, the consensus algorithm of the blockchain can be optimized, such as selecting the PBFT (Practical Byzantine Fault Tolerance) algorithm, and dynamically adjusting the number of nodes participating in the consensus and the block time. In addition, by compressing the data packet or adjusting the complexity of the encryption algorithm, the encryption calculation delay can also be effectively reduced.

[0122] In this embodiment, the resource consumption cost C r (x) is another important optimization objective, which mainly quantifies the system's resource consumption in terms of computing, communication, and storage. The resource consumption cost can be expressed as:

[0123] C r (x) = P comp +P bw +P bc

[0124] in:

[0125] P comp Indicates the computing resource consumption, which is determined by the computing power of the device and the complexity of the encryption algorithm;

[0126] P bw Indicates the consumption of communication bandwidth resources, which is related to the data transmission volume and bandwidth utilization;

[0127] P bc Indicates the blockchain storage resource consumption, which is affected by the blockchain data synchronization frequency and storage capacity limitations.

[0128] In some embodiments, the optimization of computing resource consumption can be achieved by reducing the key length or adopting a lightweight encryption algorithm, such as selecting a resource-friendly elliptic curve encryption (ECC) algorithm. As an option, in order to reduce storage resource consumption, the overall storage requirements can be reduced by sharding the blockchain data or adopting a deduplication algorithm.

[0129] In this embodiment, the security benefit C s (x) is an important part of the optimization objective function and is used to measure the anti-attack capability of the encryption system. The security benefit is expressed by the key entropy value H(K):

[0130]

[0131] in:

[0132] K represents the key length (unit: bit);

[0133] Indicates the size of the key space;

[0134] H(K) represents the key entropy value, which is used to reflect the randomness and anti-cracking ability of the key.

[0135] Generally, in order to improve the security of the system, the key length K can be increased or the key space can be expanded. In one possible implementation, in order to maintain high security under limited resource conditions, the key generation strategy can be dynamically adjusted, such as increasing the bit width of the random number or adopting a quantum secure key generation algorithm.

[0136] In some embodiments, the weight coefficients α1, α2, and α3 in the optimization objective function can be dynamically adjusted according to the actual scenario requirements. For example, in scenarios with high real-time requirements, the value of the delay weight α1 can be appropriately increased while reducing the resource consumption weight α2; in high-security scenarios, the value of the security weight α3 can be increased, thereby giving priority to optimizing the security of the system.

[0137] As an option, dynamic adjustment of the weight coefficients can be implemented in combination with real-time monitoring data. For example, when network bandwidth is limited, the priority of the communication delay target can be appropriately reduced to allocate more resources to storage and computing tasks.

[0138] S3. Construct constraints, which include encryption security lower limit, delay limit and resource budget;

[0139] Constructing constraints is one of the core links of the optimization process. By setting the constraints of encryption security lower limit, delay limit and resource budget, it can be ensured that the system can achieve multi-objective optimization while meeting specific performance requirements. In general, the setting of constraints needs to be analyzed in combination with the needs of actual application scenarios, and these conditions are accurately expressed through mathematical modeling. As an option, these constraints can be dynamically adjusted according to different scenario requirements to adapt to environments with limited resources or high security requirements. In the specific implementation of the constraints, the present invention quantifies the constraints and closely combines them with the optimization objective function by constructing a formulated description, providing an input basis for subsequent optimization algorithms.

[0140] In this embodiment, the mathematical expression of the constraint conditions includes the following aspects:

[0141] The lower limit of encryption security is:

[0142] H(K)≥S min

[0143] Latency Limit Constraints:

[0144] T total =T bc +T enc +T comm ≤T max

[0145] Resource budget constraints:

[0146] P total =P comp +P bw +P bc ≤P max

[0147] In the above expression, the meaning of each parameter is as follows:

[0148] H(K): key entropy value, indicating the security of the encryption system;

[0149] S min : Minimum security requirements, determined by the security needs of the application scenario;

[0150] T total : Total delay, including blockchain synchronization delay T bc , encryption calculation delay T enc and communication network delay T comm ;

[0151] T max : Maximum allowed delay, determined by the real-time requirements of the system;

[0152] P total : Total resource consumption, including computing resources P comp , communication bandwidth resources P bw and storage resources P bc ;

[0153] P max : The upper limit of resource budget is determined by device performance and system resource allocation strategy.

[0154] In this embodiment, the encryption security lower limit constraint is defined by the minimum requirement of the key entropy value. In general, the key entropy value H(K) is a function of the key length K and the key space size. The calculation formula is as follows:

[0155]

[0156] Specifically, if the minimum security requirement is S min , the key length needs to meet the following conditions:

[0157]

[0158] As an option, when the key space size For 2 32 , minimum security requirement S min When the key length is 128 bits, the minimum value of the key length K is:

[0159]

[0160] In one possible implementation, for quantum attack-resistant application scenarios, a larger key space can be selected, such as Thereby further improving the system's anti-cracking capabilities.

[0161] In this embodiment, the delay limit constraint is set by the total delay T totalIn general, the total delay is composed of three parts: blockchain synchronization delay, encryption calculation delay and communication network delay. The calculation formula is as follows:

[0162] T total =T bc +T enc +T comm

[0163] Specifically, the blockchain synchronization delay T bc Depends on the efficiency of the consensus algorithm, the number of nodes, and the block time. For example, in the PBFT consensus algorithm, T can be reduced by reducing the number of consensus nodes or extending the block time. bc .

[0164] Encryption calculation delay T enc It is related to the key length K and the complexity of the encryption algorithm. In one possible implementation, by selecting an encryption algorithm with lower computational complexity, T can be reduced while ensuring security. enc .

[0165] Communication network delay T comm Affected by data volume, bandwidth, and network status. For example, when the data volume is large, T can be reduced by compressing or transmitting the data in pieces. comm As an option, for scenarios with high real-time requirements, the total delay limit T max It is set to 50 milliseconds, and for normal data transmission scenarios, it can be relaxed to 200 milliseconds.

[0166] In this embodiment, the resource budget constraint is implemented by limiting the total consumption of computing resources, communication bandwidth resources, and storage resources. total It can be expressed as:

[0167] P total =P comp +P bw +P bc

[0168] in:

[0169] P comp It represents the consumption of computing resources, which is affected by the key length K and the computational complexity of the encryption algorithm;

[0170] P bw Indicates the consumption of communication bandwidth resources, which is related to the data transmission volume and bandwidth utilization;

[0171] P bc Represents the blockchain storage resource consumption, which is affected by the blockchain data synchronization frequency and storage capacity limitations.

[0172] Specifically, in resource-constrained devices, such as IoT nodes, the total resource budget T max The computing consumption is set to be less than 5 watts, the storage capacity is less than 100MB, and the transmission resources are set to a certain bandwidth. In one possible implementation, resource utilization can be further optimized by dynamically adjusting the allocation ratio of computing tasks. For example, in a scenario where storage resources are limited, the synchronization frequency of blockchain data can be reduced, storage consumption can be reduced, and more resources can be allocated to computing and communication tasks.

[0173] S4. Use mathematical optimization models to solve the optimization objective function and obtain the optimal encryption and blockchain configuration strategy;

[0174] Solving the optimization objective function through a mathematical optimization model is a key step in achieving encryption and blockchain performance optimization. The mathematical optimization model combines the objective functions of latency, security, and resource consumption with the corresponding constraints, and obtains the optimal encryption and blockchain configuration strategy through an iterative solution method. In general, this process requires a combination of gradient calculation and iterative optimization algorithms to ensure that the optimized solution can minimize the total system cost while satisfying all constraints. As an option, the mathematical optimization model can dynamically adjust weights and parameters based on scenario requirements to adapt to different wireless communication environments and security requirements.

[0175] Specifically, the mathematical optimization model of the present invention transforms the system optimization problem into a nonlinear optimization problem of multi-dimensional variables by constructing an objective function and constraints. Then, an optimization algorithm such as the gradient descent method is used to solve the problem and finally output the optimized solution. The specific process is described in detail below.

[0176] In this embodiment, the goal of the mathematical optimization model is to minimize the total cost function J(x) of the system, which is expressed in mathematical form as follows:

[0177] J(x)=α1C d (x)+α2C r (x)-α3C s (x)

[0178] in:

[0179] J(x) is the total cost function;

[0180] α1, α2, and α3 are the weight coefficients of delay cost, security benefit, and resource consumption, respectively;

[0181] C d (x) is the delay cost, including blockchain synchronization delay, encryption calculation delay and communication network delay;

[0182] C r(x) is the resource consumption cost, including the consumption of computing, communication and storage resources;

[0183] C s (x) is the security gain, represented by the key entropy value.

[0184] In some embodiments, the weight parameters α1, α2, and α3 of the objective function can be dynamically adjusted according to actual needs. For example, in a real-time communication scenario that is sensitive to delay, the value of α1 can be increased to prioritize the optimization of the delay target.

[0185] In this embodiment, the optimization problem is subject to multiple constraints. Generally, these constraints include encryption security lower limit, delay limit and resource budget, which are described as follows:

[0186] The lower limit of encryption security is:

[0187] H(K)≥S min

[0188] Where H(K) is the key entropy value, S min Minimum security requirements;

[0189] Latency Limit Constraints:

[0190] T total =T bc +T enc +T comm ≤T max

[0191] Where T total is the total delay, T max is the maximum allowed delay;

[0192] Resource budget constraints:

[0193] P total =P comp +P bw +P bc ≤P max

[0194] Where P total is the total resource consumption, P max The resource budget cap.

[0195] In a possible implementation, in order to solve the above optimization problem, the present invention uses a gradient descent method for optimization. The specific optimization process is as follows:

[0196] In this embodiment, the gradient descent method determines the optimization direction by calculating the gradient of the objective function. The gradient of the objective function with respect to each optimization variable is It is expressed as:

[0197]

[0198] in:

[0199] The gradient of the key length K is related to the change in the key entropy value;

[0200] The gradient of the delay variable is related to the optimization relationship between blockchain synchronization, cryptographic computing, and communication networks.

[0201] In some embodiments, the iterative formula of the gradient descent method can be expressed as:

[0202]

[0203] in:

[0204] x (k) is the variable value of the Kth iteration;

[0205] η is the learning rate, which is used to control the step size of gradient update;

[0206] is the gradient of the objective function at the Kth iteration.

[0207] In general, the choice of learning rate η has an important impact on the convergence and stability of the optimization process. As an option, the learning rate can be set to a dynamically adjusted value to adapt to the gradient changes during the optimization process.

[0208] In another possible implementation, in order to improve the solution efficiency, a constrained optimization algorithm (such as the Lagrange multiplier method) can be used to jointly solve the objective function and the constraint conditions. Specifically, by introducing the Lagrange multiplier, the constraint conditions are integrated into the objective function, and the Lagrange function is constructed as follows:

[0209]

[0210] in:

[0211] λ1, λ2, and λ3 are Lagrange multipliers used to measure the degree of violation of constraints.

[0212] By taking partial derivatives of the Lagrangian function with respect to the variable x and the multiplier λ respectively and solving them simultaneously, the optimal solution of the objective function can be obtained.

[0213] In this embodiment, when the optimization process meets the convergence condition, the optimized solution is output. Specifically, the convergence condition can be set by the modulus value of the gradient, for example:

[0214]

[0215] Where ∈ is the preset convergence threshold. When the convergence condition is met, the output optimization results include the key length k, the blockchain synchronization parameter P bc and the delay optimization strategy T comm And other key configurations.

[0216] S5. Establish a multi-agent game model, optimize the interaction strategies of wireless communication nodes and blockchain nodes, and obtain the global optimal equilibrium strategy;

[0217] There is a complex interactive relationship between wireless communication nodes and blockchain nodes. Especially when optimizing encryption performance and blockchain synchronization performance, the strategy choices between these nodes will affect each other. In order to analyze and optimize the global behavior of the multi-node system, the present invention establishes a multi-agent game model to describe the competition and cooperation relationship between the nodes, and solves the global optimal equilibrium strategy on this basis. In general, the multi-agent game model is suitable for scenarios where nodes have independent goals but are subject to global constraints of the system, such as the balanced optimization of delay, security and resources in wireless communication systems. As an option, the game model in the present invention uses Nash equilibrium as the solution target to ensure that all nodes cannot obtain better results by adjusting their strategies individually under the current strategy.

[0218] Specifically, the establishment of a multi-agent game model includes three main links: agent definition, utility function construction, and equilibrium solution. These links are described in detail below.

[0219] In this embodiment, the subjects of the multi-agent game model include wireless communication nodes and blockchain nodes. Generally speaking, wireless communication nodes are responsible for data transmission and encryption operations, and their optimization goal is to minimize communication delays and resource consumption while ensuring encryption security; blockchain nodes are responsible for consensus and synchronization operations, and their optimization goal is to minimize blockchain synchronization delays and storage resource consumption while ensuring data integrity and consistency.

[0220] In some embodiments, the policy set for each principal may be represented as:

[0221] x i =(K i ,T bc,i ,T enc,i ,T comm,i )

[0222] in:

[0223] K i : The key length of node i, which affects the encryption strength and calculation delay;

[0224] T bc,i : The blockchain synchronization delay of node i is determined by the consensus mechanism and node configuration;

[0225] T enc,i : The encryption calculation delay of node i is related to the key length and encryption algorithm;

[0226] T comm,i : The communication network delay of node i is determined by the bandwidth and data volume.

[0227] In this embodiment, the utility function U i (x i ,x -i ) is used to describe the optimization goal of each node i, where x -i represents the strategy set of other nodes except node i. In general, the utility function can be expressed as:

[0228] U i (x i ,x -i )=-α1C d (x i )-α2C r (x i )+α3C s (x i )

[0229] in:

[0230] C d (x i ): the delay cost of node i, which consists of its communication delay, encryption delay and blockchain delay;

[0231] C r (x i ): resource consumption cost of node i, including computing resources, bandwidth resources and storage resources;

[0232] C s (x i ): The security benefit of node i, which is determined by the key entropy value H(K i )express;

[0233] α1, α2, α3: weight parameters representing delay cost, security benefit, and resource consumption, respectively.

[0234] Specifically, the delay cost can be further broken down into:

[0235] C d (x i )=T bc,i +T enc,i +T comm,i

[0236] The resource consumption cost can be expressed as:

[0237] Cr (x i )=P comp,i +P bw,i +P bc,i

[0238] in:

[0239] T comm,i : Computational resource consumption of node i;

[0240] P bw,i : Communication bandwidth consumption of node i;

[0241] P bc,i : Blockchain storage resource consumption of node i.

[0242] The security benefit is calculated by the key entropy value:

[0243]

[0244] in Indicates the size of the key space of node i.

[0245] In this embodiment, the equilibrium solution of the game model aims at Nash equilibrium. Generally speaking, Nash equilibrium means that when all other node strategies are fixed, no node can obtain a higher utility value by adjusting its strategy alone. Mathematically, the equilibrium condition can be expressed as:

[0246]

[0247] in:

[0248] represents the optimal strategy of node i in equilibrium state;

[0249] Represents the optimal strategy of other nodes in equilibrium state;

[0250] S i Represents the set of feasible strategies for node i.

[0251] In a possible implementation, in order to solve the Nash equilibrium, the present invention uses the best response method to iteratively solve. The specific process is as follows:

[0252] In this embodiment, the optimal response method fixes the strategies x- i , optimize the strategy x of node i i . This process can be expressed as:

[0253]

[0254] in:

[0255] represents the optimal strategy of node i in the k+1th iteration;

[0256] represents the strategies of other nodes in the kth iteration.

[0257] In general, the iteration process stops when all node strategies converge, that is, the following conditions are met:

[0258]

[0259] Where ∈ is the convergence threshold.

[0260] In some embodiments, in order to speed up the equilibrium solution process, a distributed computing method can be combined. Specifically, each node independently calculates its optimal response strategy and synchronizes and updates the strategy set x through communication between nodes. As an option, in scenarios where communication resources are limited, the synchronization frequency can be reduced or a distributed approximation algorithm can be used to further reduce the computing and communication overhead.

[0261] S6. Implement dynamic policy adjustment to adjust encryption and blockchain parameters based on real-time changes in the communication environment;

[0262] Dynamic policy adjustment is an important function used to adapt to real-time changes in the communication environment. Wireless communication systems and blockchain networks are often affected by dynamic conditions such as network delays, bandwidth fluctuations, and insufficient computing resources. By dynamically adjusting encryption and blockchain parameters, system performance can be optimized in different scenarios. In general, dynamic policy adjustment is accomplished by real-time monitoring of key indicators of the communication environment and recalculating the optimal policy in combination with the optimization model. As an option, the dynamic adjustment method of the present invention combines dynamic updating of weight parameters, real-time reconstruction of policies, and adaptive adjustment of parameters to ensure the stability and efficiency of the system in complex environments.

[0263] Specifically, dynamic strategy adjustment includes three main links: communication environment monitoring, real-time optimization calculation and dynamic parameter update. These links are described in detail below.

[0264] Latency monitoring:

[0265] By counting the real-time delay in the network, including communication delay, blockchain synchronization delay and encryption calculation delay, the current total delay T is obtained. total . These delays can be expressed as:

[0266] T total =T bc +T enc +T comm

[0267] in:

[0268] T bc : Blockchain synchronization delay;

[0269] T enc : Encryption calculation delay;

[0270] T comm : Communication network delay.

[0271] Resource monitoring:

[0272] Including computing resource consumption P comp , Communication bandwidth resource consumption P bw and storage resource consumption P bc . These resource consumption can be expressed as:

[0273] P total =P comp +P bw +P bc

[0274] Specifically, computing resource consumption is monitored through the device’s CPU or GPU load; bandwidth resource consumption is measured through data traffic and network utilization; and storage resource consumption is calculated through the node’s storage capacity and blockchain data volume.

[0275] The security of the system is quantified by monitoring the key length K and the key entropy value H(K). The formula is:

[0276]

[0277] in Indicates the size of the key space. Generally, when the communication environment is threatened by potential attacks, the key length can be increased to enhance security.

[0278] In this embodiment, real-time optimization calculation is the core link of dynamic adjustment. Generally, when the communication environment changes significantly, it is necessary to recalculate the optimization objective function and adjust the system strategy. The optimization objective function can be expressed as:

[0279] J(x)=α1C d (x)+α2C r (x)-α3C s (x)

[0280] in:

[0281] C d (x): delay costs;

[0282] C r (x): resource consumption cost;

[0283] Cs (x): security benefit;

[0284] α1, α2, α3: weight parameters.

[0285] In some embodiments, when the delay exceeds a set threshold T max When the resource consumption exceeds the budget P, the weight α1 of the delay target can be reduced first and the optimization solution can be recalculated. max When synchronizing blockchain data, the frequency of blockchain data synchronization can be reduced or the complexity of the encryption algorithm can be adjusted to reduce resource usage.

[0286] In this embodiment, the dynamic update of parameters is driven by real-time monitoring results. Generally, the main parameters that are dynamically adjusted include the key length K, the blockchain synchronization frequency, and the data compression rate.

[0287] In a possible implementation, when insufficient communication bandwidth is detected, T can be reduced by reducing the amount of data transmitted or increasing the data compression rate. comm For example, using more efficient compression algorithms can reduce the network load during data transmission, thereby reducing communication delays.

[0288] As an option, when computing resources are insufficient, the key length K can be reduced or an encryption algorithm with lower computational complexity can be selected. For example, switching the encryption algorithm from AES to ECC can reduce the consumption of computing resources while ensuring security.

[0289] Specifically, when storage resources are limited, the synchronization frequency of the blockchain can be reduced by sync Or choose a shard storage solution to reduce P bc . This process can be expressed as:

[0290] P bc,new =P bc (1-r)

[0291] Where r represents the reduction ratio of the synchronization frequency.

[0292] In some embodiments, in order to further improve the efficiency of dynamic adjustment, a distributed monitoring and adjustment method can be used. Specifically, each node independently monitors its own communication environment and completes parameter updates through collaboration with other nodes. For example, when changes in network delay mainly affect certain nodes, the strategies of these nodes can be adjusted first without making large-scale modifications to global parameters.

[0293] In another possible implementation, in order to prevent frequent dynamic adjustments from affecting system stability, a trigger threshold for dynamic adjustment may be set, for example, dynamic adjustment is triggered only when the delay variation exceeds 10% or resource consumption exceeds 20% of the budget.

[0294] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wireless communication encryption method combined with blockchain technology, characterized in that: The following steps are involved: Initialize system parameters, including key length, security requirements, delay constraints, and resource budget; Construct an optimization objective function to optimize encryption latency, blockchain synchronization latency, and resource consumption in wireless communications while improving encryption security; Constructing constraints, wherein the constraints include a cryptographic security lower bound, a latency limit, and a resource budget; Use mathematical optimization models to solve the optimization objective function and obtain the optimal encryption and blockchain configuration strategy; Establish a multi-agent game model, optimize the interaction strategies of wireless communication nodes and blockchain nodes, and obtain the global optimal equilibrium strategy; Implement dynamic policy adjustments to adjust encryption and blockchain parameters based on real-time changes in the communication environment.

2. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The optimization objective function includes: Latency target, which is used to minimize the total latency in the encryption process, including blockchain consensus latency, encryption computation latency, and communication network latency; Resource consumption goals, used to minimize the use of computing resources, communication bandwidth resources, and storage resources; The security goal is to maximize the key entropy of communication encryption, thereby improving encryption security.

3. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The constraints include: Determine the lower limit of encryption security and calculate the key entropy value, which is determined by the key length and the size of the key space; Set security constraints to ensure that the key entropy value is not lower than the preset encryption security requirement, which is defined according to the specific application scenario; Set delay limits, count the delay indicators of the communication network, and calculate the total delay by combining blockchain consensus delay, encryption calculation delay, and communication network delay; Set delay constraints to ensure that the total delay does not exceed the maximum allowable delay of the system real-time performance; Analyze the computing power, bandwidth resources, and storage resources of the device, and count resource usage; Set resource budget constraints to ensure that the total resource consumption of the device does not exceed the preset resource budget, including computing resources, communication bandwidth resources, and storage resources; Security constraints, delay constraints, and resource budget constraints are uniformly modeled as constraints of the optimization problem and used as input parameters of the optimization objective function to participate in the final strategy solution.

4. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The mathematical optimization model is solved by an iterative optimization algorithm, including: Initialize optimization variables and set initial values ​​of key length, blockchain consensus delay, encryption delay, and communication delay; According to the optimization objective function, calculate the partial derivative of each optimization variable and determine the optimization direction; By iteratively updating the optimization variables, the optimal solution is gradually approached; When the optimization result meets the preset accuracy conditions, the optimized solution is output.

5. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The multi-agent game model includes: Consider wireless communication nodes and blockchain nodes as game entities, establish the objective function of each entity, and optimize its latency, resource consumption, and encryption security; Fix the strategy of a certain game subject and optimize the strategies of other game subjects until a global equilibrium is achieved; When the strategies of all game players reach equilibrium, the Nash equilibrium solution is output.

6. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The dynamic strategy adjustment includes: Real-time monitoring of the communication environment’s latency, bandwidth, and device resource usage; Dynamically adjust the weight parameters in the optimization objective function according to the monitoring results and recalculate the optimization solution; When the communication environment changes, the key length, blockchain consensus parameters and communication delay optimization strategy are updated in real time.

7. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The encryption security is represented by the key entropy value, which is associated with the key length and the size of the key space and is used to measure the encryption system's ability to resist cracking: Calculate blockchain synchronization delay: By selecting and configuring the blockchain consensus algorithm, determine the block time, number of nodes, and synchronization efficiency, and then calculate the blockchain synchronization delay; Calculate encryption calculation delay: Determine encryption calculation delay based on the calculation complexity of the selected encryption algorithm and the dynamically adjusted key length, combined with the computing performance of the device; Calculate communication network delay: Calculate the network transmission delay generated during the communication process based on the communication bandwidth, transmission data volume and network status; Determine resource consumption: Calculate total resource consumption by counting the computing consumption of the device, communication bandwidth usage, and blockchain storage consumption; Represents the total delay: Add the blockchain synchronization delay, encryption calculation delay and communication network delay to get the total delay of the communication system.

8. According to claim 1, a wireless communication encryption method combined with blockchain technology is characterized in that: The construction of the optimization objective function is used to optimize the encryption delay, blockchain synchronization delay and resource consumption in wireless communication, while improving encryption security, specifically including: Determine blockchain synchronization delay through blockchain consensus algorithm; The encryption calculation delay is determined by the calculation complexity of the encryption algorithm and the key length; Determine communication network latency based on communication bandwidth and data volume; The total delay is the sum of blockchain synchronization delay, encryption calculation delay and communication network delay.

9. According to claim 4, a wireless communication encryption method combined with blockchain technology is characterized in that: The iterative optimization algorithm adopts the gradient descent method to solve, which specifically includes: Initialize optimization variables and step size parameters; Calculate the gradient value according to the optimization objective function; Adjust the variable value in the optimization direction until the modulus of the gradient value meets the convergence condition.

10. A wireless communication encryption method combined with blockchain technology according to claim 1, characterized in that: The initialization system parameters include: Determine the initial value of the key length, and select a key length that meets the lower limit of encryption security based on the security requirements, key space size, and encryption algorithm characteristics in the application scenario; Set security requirements, combine the sensitivity level of communication data and potential attack threats, and define the minimum key entropy value as a security constraint; Determine the delay limit. Combined with the real-time requirements in the application scenario, set the maximum allowable value of the total delay by collecting historical data on blockchain synchronization delay, encryption calculation delay, and communication network delay; Set resource budgets, combining the computing power, communication bandwidth, and storage capacity of the device to define the maximum available values ​​of computing resources, bandwidth resources, and storage resources; Initialize the weight parameters and assign delay weight, security weight, and resource consumption weight according to the system's priority requirements for delay, security, and resource consumption optimization to ensure that the optimization goals match the requirements of the application scenario.

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