Computing force dynamic adjustment-based game system and method on excitation compatible chain

Abstract

The invention provides an incentive compatible chain game system and method based on computing power dynamic adjustment. The system comprises a mine pool management module which is used for being responsible for management and scheduling work in a mine pool, receiving and processing an incentive fund request from an attacker and responding to the incentive fund request according to a preset strategy; the network communication module is responsible for communication between nodes and block propagation in the block chain network; the strategy execution module is used for monitoring network conditions, adjusting computing power distribution, initiating bifurcation attacks and combining bifurcation chains; the data analysis and monitoring module is used for analyzing and monitoring data of the block chain network in real time, the data analysis and monitoring module comprises block propagation speed, network delay and mine pool computing power distribution, and decision support is provided for the strategy execution module through data analysis. According to the invention, by introducing the incentive mechanism of incentive gold and optimizing the calculation power distribution strategy, the maximization of the gaming income on the chain, the improvement of the network security and the incentive compatibility among miners are realized.

Description

Technical Field

[0001] The present invention relates to the field of blockchain technology, and in particular to an incentive-compatible on-chain game (BM-PAW) system and method based on dynamic adjustment of computing power. Background Art

[0002] In today's digital age, blockchain technology is developing rapidly. Its security and stability have shown great application potential in many fields and have become one of the focuses of global science and technology. Among them, Bitcoin, as the first successful and representative public chain application of blockchain technology, has opened up a new path for the development of the digital economy and opened an unprecedented new era with its outstanding characteristics such as decentralization, immutability and high transparency.

[0003] However, as Bitcoin's global recognition continues to increase, its value has also shown a trend of continuous rise. This significant change has attracted many investors and participants to participate in the field of Bitcoin chain games, but it has also caused a series of problems that cannot be ignored. Especially in terms of network security, due to the huge economic value of Bitcoin, some lawless elements have begun to rack their brains to develop various advanced chain game attack strategies in order to obtain more benefits. These attack strategies are endless and increasingly complex and hidden, posing an extremely severe challenge to the security of the Bitcoin network.

[0004] Traditional on-chain game strategies, such as selfish on-chain games and block withholding on-chain games, may be able to play a certain role in the relatively simple network environment in the early days. However, with the continuous evolution of network technology, today's network environment has become complex and changeable, the user scale continues to expand, the network traffic is becoming increasingly large, and various new technical applications are constantly emerging. Under such a new situation, the limitations exposed by traditional on-chain game strategies are becoming more and more obvious, and they can no longer effectively respond to the many new requirements put forward by the current complex and changeable network environment.

[0005] Through searching patent documents, it is found that the invention patent with publication number CN107819756A discloses a new method and system for improving the benefits of on-chain gaming. Based on the PoW consensus algorithm and the dilemma model, the patent analyzes the two situations of the same and different miners' computing power, and obtains the miners' on-chain gaming benefit matrix; constructs the non-ZD strategy, single ZD strategy, and double ZD strategy models, and calculates the system on-chain gaming benefits when the computing power is the same and different according to the benefit matrix and the Markov transfer matrix. However, it does not involve the incentive mechanism and the fork and merge mechanism, and cannot dynamically adjust the computing power and achieve incentive compatibility.

[0006] To sum up, in view of the many shortcomings of the above-mentioned existing technologies, in order to ensure the normal development of on-chain game activities in the Bitcoin network and even the entire blockchain field, ensure the security and stability of the network, and improve the rationality and sustainability of on-chain game benefits, it has become a key task to study an incentive-compatible on-chain game (BM-PAW) system and method based on dynamic adjustment of computing power. Summary of the invention

[0007] In view of the defects in the prior art, the purpose of the present invention is to provide an incentive-compatible on-chain game (BM-PAW) system and method based on dynamic adjustment of computing power.

[0008] According to the present invention, an incentive-compatible on-chain game (BM-PAW) system based on dynamic adjustment of computing power is provided, comprising:

[0009] Mining pool management module: including miner registration unit, computing power allocation unit and block verification unit. The mining pool management module is responsible for the management and scheduling of the mining pool, receiving and processing incentive requests from attackers, and responding to incentive requests according to preset strategies;

[0010] Network communication module: responsible for the communication between nodes and the propagation of blocks in the blockchain network;

[0011] Strategy execution module: responsible for monitoring network status, adjusting computing power allocation, launching fork attacks, and merging forked chains;

[0012] Data analysis and monitoring module: used to analyze and monitor the data in the blockchain network in real time. The data analysis and monitoring module includes block propagation speed, network latency and mining pool computing power distribution, and provides decision support for the strategy execution module through data analysis;

[0013] Among them, the mining pool management module, network communication module, strategy execution module and data analysis and monitoring module work together to realize the overall function of the incentive-compatible on-chain game system based on dynamic adjustment of computing power.

[0014] The present invention also provides an incentive-compatible on-chain game (BM-PAW) method based on dynamic adjustment of computing power, based on the above-mentioned BM-PAW system, comprising the following steps:

[0015] Step S1, set initial parameters and select target mining pool;

[0016] Step S2: Based on the initial parameters, a mechanism for paying and receiving incentive funds is constructed. If the two parties establish a cooperative relationship, the target mining pool adjusts the on-chain game strategy.

[0017] Step S3, based on the initial parameters and on-chain game strategy, carry out computing power adjustment and on-chain game to create block forks;

[0018] Step S4, obtaining the profit distribution ratio through fork monitoring and merging operations;

[0019] Step S5: Based on the profit distribution ratio, profit distribution and strategy adjustment are performed.

[0020] Preferably, step S1 includes the following sub-steps:

[0021] Step S1.1, the attacker sets the initial parameters, including the initial amount of incentive funds, the step size of computing power adjustment, the fork length threshold, and the computing power allocation ratio;

[0022] In step S1.2, the attacker selects a target mining pool as the target of attack based on the mining pool computing power distribution information, network delay data and the initial amount of incentive funds.

[0023] Preferably, in step S1.1, the initial amount of the incentive is dynamically adjusted according to the computing power scale of the target mining pool, the network status and the expected profit of the attacker.

[0024] Preferably, in step S1.2, there are two ways for the attacker to determine the target mining pool: one is to determine the target mining pool by offline incentives; the other is to determine the target mining pool by issuing a smart contract for incentives.

[0025] Preferably, step S2 includes the following sub-steps:

[0026] Step 2.1: Based on the initial amount of the incentive, the attacker sends an incentive payment request to the target mining pool through the mining pool management module of the BM-PAW system, and attaches the initial amount of the incentive and payment conditions;

[0027] Step S2.2: After receiving the incentive payment request, the target mining pool verifies and confirms whether to accept the incentive payment request. If accepted, the two parties establish a cooperative relationship. The target mining pool sends a confirmation message to the attacker through the mining pool management module and adjusts the preset on-chain game strategy according to the attacker's requirements. If not accepted, return to step S2.1.

[0028] Preferably, in step S2.2, the verification content includes: whether the target address of the incentive payment request matches the address of the target mining pool.

[0029] Preferably, step S3 includes the following sub-steps:

[0030] Step S3.1: The attacker obtains the optimal computing power allocation plan through the strategy execution module according to the current network status, its own risk resistance and initial parameters;

[0031] In step S3.2, the attacker and the target mining pool conduct on-chain games according to the on-chain game strategies respectively. The attacker controls the infiltration on-chain game computing power allocated by himself and works together with the computing power of the target mining pool based on the optimal computing power allocation plan to create a block fork.

[0032] Preferably, step S4 includes the following sub-steps:

[0033] Step S4.1, through the data analysis and monitoring module, the block fork in the blockchain network is monitored in real time. Once a fork is detected, the length and status information of the forked chain are recorded;

[0034] Step S4.2: When the length of the forked chain reaches the preset threshold, the attacker evaluates the feasibility of merging the forked chain through the policy execution module. If the evaluation result shows that the merger operation is expected to bring higher benefits, the merger decision is passed;

[0035] Step S4.3, after the merger decision is passed, the attacker merges the forked chain back to the main chain by controlling the game computing power on its own penetration chain and the computing power of the target mining pool. After the merger is successful, the attacker and the target mining pool determine the profit distribution ratio based on the proportion of their respective contributed computing power.

[0036] Preferably, step S5 includes the following sub-steps:

[0037] Step S5.1, after each fork attack, the additional revenue is distributed to the attacker and the target mining pool according to the revenue distribution ratio;

[0038] Step S5.2, based on the results of each attack and changes in network conditions, the attacker evaluates the effectiveness of the current strategy through the data analysis and monitoring module, and adjusts the initial parameters in a timely manner for subsequent attacks.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] 1. The present invention provides an innovative incentive-compatible on-chain game method (BM-PAW) based on dynamic adjustment of computing power. By introducing incentive money as an incentive mechanism, the target mining pool is induced to conduct on-chain games according to the attacker's intention, thereby improving the success rate of fork competition and increasing the benefits of the attacker and the target mining pool.

[0041] 2. The BM-PAW method of the present invention also maximizes the benefits of on-chain gaming and improves network security by optimizing computing power allocation and dynamically adjusting strategy parameters.

[0042] 3. The present invention is based on the calculation power adjustment and retention on-chain game (BM-PAW) algorithm design with incentive money, and aims to maximize the on-chain game revenue, improve network security, and achieve incentive compatibility among miners by introducing incentive money incentive mechanism and optimizing calculation power allocation strategy, solve the problems of low revenue, unstable success rate of fork competition, and poor security in existing on-chain game strategies, and provide new ideas and methods for on-chain game attack and defense strategies in the field of blockchain technology. Therefore, the present invention has broad application prospects and market value. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0044] Figure 1 This is a system architecture diagram of an incentive-compatible on-chain game (BM-PAW) based on dynamic adjustment of computing power in an embodiment of the present invention;

[0045] Figure 2 This is a flow chart of an incentive-compatible on-chain game (BM-PAW) method based on dynamic adjustment of computing power in an embodiment of the present invention;

[0046] Figure 3 is the relative additional reward of the attacker in scenario 1 in the embodiment of the present invention;

[0047] Figure 4 is the relative additional reward of the attacker in scenario 2 in the embodiment of the present invention;

[0048] Figure 5 is the relative additional reward of the attacker in scenario 3 in the embodiment of the present invention;

[0049] Figure 6 is the relative additional reward of the attacker in scenario 4 in the embodiment of the present invention;

[0050] Figure 7 The relative additional reward of the target mining pool in scenario 1 in the embodiment of the present invention;

[0051] Figure 8 The relative additional reward of the target mining pool in scenario 2 in the embodiment of the present invention;

[0052] Fig. 9 The relative additional reward of the target mining pool in scenario 3 in the embodiment of the present invention;

[0053] Fig.10 This is the relative additional reward of the target mining pool in scenario 4 in the embodiment of the present invention. DETAILED DESCRIPTION

[0054] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0055] The present invention adopts the following technical solutions:

[0056] 1. The basic framework of BM-PAW:

[0057] Incentive mechanism: In the BM-PAW method, the attacker induces the target mining pool to participate in the attack by paying incentives to it. The amount of the incentive is dynamically adjusted according to factors such as the computing power scale of the target mining pool, network conditions, and the attacker's expected benefits. By setting the incentive reasonably, it is ensured that both the BM-PAW attacker mining pool and the target mining pool obtain higher benefits when participating in the attack than when not participating, thereby achieving incentive compatibility. Among them, the reasonable incentive setting needs to meet the following requirements: the minimum incentive amount set needs to ensure that the reward of the target mining pool in BM-PAW is greater than its reward under PAW, and the maximum incentive amount of the attacker in BM-PAW must ensure that the attacker's reward is greater than the reward under PAW, that is, as well as

[0058] Computing power adjustment strategy: The attacker dynamically adjusts the computing power of the game on the penetration chain based on factors such as the computing power scale and network status of the target mining pool. By constructing and solving the optimization equation, the optimal computing power allocation plan under given conditions is obtained to improve the success rate and profit level of the fork competition.

[0059] Fork and merge mechanism: BM-PAW attackers strategically control their own and the target mining pool's on-chain gaming behavior to create block forks. When certain conditions are met (such as the fork length reaches a predetermined threshold), the attacker will try to merge the forked chain back to the main chain to obtain higher on-chain gaming benefits.

[0060] 2. BM-PAW method flow:

[0061] Similar to the PAW attack, the BM-PAW attacker first divides its own on-chain gaming computing power into innocent on-chain gaming computing power and infiltrated on-chain gaming computing power in a victim pool scenario. When the attacker's infiltrated on-chain gaming computing power finds a valid full proof of work (FPoW), the attacker adjusts the allocation ratio of its on-chain gaming computing power.

[0062] The difference between a BM-PAW attack and a PAW attack is that a BM-PAW attacker will bribe the target mining pool to increase the probability that the branch where its FPoW is located will be selected as the main chain in the fork competition. More specifically, when a valid block (FPoW) is found, there are five possible situations:

[0063] Case 1: If the valid block is discovered by the attacker’s innocent mining pool, in this case, the attacker will immediately propagate it and receive the block reward (coinage reward).

[0064] Case 2: If the valid block is discovered by other miners who do not belong to the attacker, the target mining pool, and the victim mining pool, the attacker will accept it and continue to mine the next block. In this case, the attacker cannot get any reward.

[0065] Case 3: If the valid block is discovered by the attacker’s infiltrated mining pool in the victim’s pool, the attacker will accept it and continue to mine the next block. In this case, the attacker will receive the corresponding share reward.

[0066] Case 4: If the valid block is discovered by the target mining pool, the situation is similar to Case 2. The attacker will accept it and continue to mine the next block. In this case, the attacker will not receive any reward.

[0067] Case 5: If the valid block is discovered by the attacker's infiltration pool, the attacker will withhold the block and readjust his on-chain gaming power. At the same time, when he discovers the next FPoW, the following four sub-cases will occur:

[0068] Case 5-1: If the next FPoW is discovered by the attacker's innocent mining pool, the attacker will discard the withheld FPoW and propagate the new FPoW. In this case, the attacker gets a block reward.

[0069] Case 5-2: If the next FPoW is discovered by other miners who do not belong to the attacker, the target mining pool, and the victim mining pool. The attacker will immediately submit the withheld FPoW to the victim pool administrator. When the administrator propagates the FPoW, a fork occurs. At the same time, the attacker lures the target mining pool to play on-chain on the attacker's FPoW. If the target mining pool chooses to accept the incentive and mine on the attacker's FPoW, then he will receive the incentive paid by the attacker. Otherwise, he will adopt an honest on-chain game strategy like other miners. Even if the attacker adopts a very small ε1 as the incentive, the target mining pool will choose to accept the incentive. In this case, the attacker obtains a fork reward. Please note that the fork reward obtained is different when the target mining pool chooses to accept or reject the incentive.

[0070] Case 5-3: If the next FPoW is discovered by the attacker's infiltration pool in the victim pool, the attacker will accept it and discard the withheld FPoW. In this case, the attacker gets the corresponding share reward in the victim pool.

[0071] Case 5-4: If the next FPoW is discovered by the target mining pool. The attacker will immediately submit the withheld FPoW to the victim pool administrator. At the same time, the attacker lures the target mining pool to discard his FPoW. If the target mining pool chooses to accept the incentive and mine on the attacker's FPoW, then he will receive the incentive paid by the attacker. Otherwise, he will propagate his FPoW and a fork will occur. The target mining pool will only accept the incentive if the amount of incentive paid by the attacker is greater than the loss suffered by the target by accepting the incentive. In this case, the attacker receives a share reward (when the target mining pool accepts the incentive) or a fork reward (when the target mining pool rejects the incentive).

[0072] Note that the BM-PAW attack adds a type of participant, the target mining pool, on the basis of the PAW attack, which will cause the strategy cases to become more complicated. Specifically, Case 4 is added in the stage before adjusting the on-chain game computing power. Once the target mining pool finds a valid block, the attacker will accept it and continue to mine the next block. In addition, Case 5-2 is modified, and Case 5-4 is added in the stage after the on-chain game computing power is redistributed. The attacker will try to lure the target mining pool to play on-chain games on the attacker's FPoW during the fork competition phase. When there is a fork between the attacker's FPoW and the FPoW of other miners (Case 5-2), the target will accept the incentive even if the attacker adopts a very small ε1 as the incentive. However, the target mining pool will only accept the incentive when ε2 is large enough (Case 5-4).

[0073] 3. Optimization strategies for computing power and incentives

[0074] How to adjust the attacker's on-chain gaming computing power to maximize his reward?

[0075] Based on the attacker’s system rewards in BM-PAW, by finding the optimal ratio of the attacker’s on-chain gaming power ( and ) to maximize its expected reward

[0076]

[0077] st0≤r1≤1,0≤r2≤1.

[0078] Use Lagrange multipliers to solve the above equation. Specifically, rewrite it as follows:

[0079]

[0080] stg1(r1,r2)=-r1≤0;

[0081] g2(r1,r2)=r1-1≤0;

[0082] g3(r1,r2)=-r2≤0;

[0083] g4(r1,r2)=r2-1≤0;

[0084] As expected, when r1∈[0,1], the objective function is a convex function about r1 (the Hessian matrix is ​​positive definite). Therefore, by solving the KKT condition, we can find the optimal and

[0085] How to price incentives?

[0086] Assume that there is a secret agreement ε1 (Case 5-2) and ε2 (Case 5-4), which represent the negotiation results of the attacker and the target mining pool on the incentive fund. Focus on analyzing the constraints of ε1 and ε2 to make the BM-PAW attack effective and profitable. is the total reward of the target mining pool in BM-PAW (i.e. the target mining pool that receives the incentive), is the total reward of the target mining pool in PAW (i.e., the target mining pool that refuses the incentive). When the attacker cannot provide a sufficiently attractive incentive to the target mining pool, the BM-PAW attack will be downgraded to a PAW attack. At the same time, after paying the incentive to the target mining pool, the BM-PAW attacker can get a higher reward. Based on this, the reward of the target mining pool in the PAW attack is obtained. In addition, the minimum incentive amount needs to ensure that the reward of the target mining pool in BM-PAW is greater than PAW, and the maximum incentive amount of the attacker in BM-PAW must ensure that the attacker's reward is greater than PAW, that is, as well as

[0087] Embodiment 1:

[0088] Figure 1 This is a system architecture diagram of an incentive-compatible on-chain game (BM-PAW) based on dynamic adjustment of computing power in an embodiment of the present invention.

[0089] like Figure 1 As shown, this embodiment provides an incentive-compatible on-chain game (BM-PAW) system based on dynamic adjustment of computing power, including:

[0090] Mining pool management module: including miner registration unit, computing power allocation unit and block verification unit. The mining pool management module is responsible for the management and scheduling of the mining pool, receiving and processing incentive requests from attackers, and responding to incentive requests according to preset strategies.

[0091] Network communication module: responsible for the communication between nodes and the propagation of blocks in the blockchain network.

[0092] Policy execution module: responsible for monitoring network status, adjusting computing power allocation, launching fork attacks, and merging forked chains.

[0093] Data analysis and monitoring module: used for real-time analysis and monitoring of data in the blockchain network. The data analysis and monitoring module includes block propagation speed, network latency, and mining pool computing power distribution, and provides decision support for the strategy execution module through data analysis.

[0094] Among them, the mining pool management module, network communication module, strategy execution module and data analysis and monitoring module work together to realize the overall function of the incentive-compatible on-chain game (BM-PAW) system based on dynamic adjustment of computing power.

[0095] Embodiment 2:

[0096] Figure 2 This is a flow chart of an incentive-compatible on-chain game (BM-PAW) method based on dynamic adjustment of computing power in an embodiment of the present invention.

[0097] like Figure 2 As shown, this embodiment provides an incentive-compatible on-chain game (BM-PAW) method based on dynamic adjustment of computing power, based on the BM-PAW system in the above embodiment 1, including the following steps:

[0098] Step S1, set initial parameters and select the target mining pool.

[0099] Specifically, step S1 includes the following sub-steps:

[0100] Step S1.1, the attacker sets the initial parameters, which include the initial amount of incentive funds, the step size of computing power adjustment, the fork length threshold and the computing power allocation ratio.

[0101] In this embodiment, the initial amount of the incentive is dynamically adjusted according to the computing power scale of the target mining pool, the network status and the expected income of the attacker. The initial amount of the incentive meets the following requirements: the minimum incentive amount needs to ensure that the reward of the target mining pool in BM-PAW is greater than its reward under PAW, and the maximum incentive amount of the attacker in BM-PAW must ensure that the attacker's reward is greater than its reward under PAW, that is, as well as This ensures that both the BM-PAW attacker mining pool and the target mining pool gain more profit when participating in the attack than when not participating, thus achieving incentive compatibility.

[0102] In step S1.2, the attacker selects a target mining pool as the target of attack based on the mining pool computing power distribution information, network delay data and the initial amount of incentive funds.

[0103] In this embodiment, there are two ways for the attacker to determine the target mining pool: one is to determine the target mining pool through offline incentives; the other is to determine the target mining pool by issuing a smart contract for incentives.

[0104] Specifically, when the attacker adopts the offline incentive method, he will conduct offline negotiations and communication with the target mining pool, including the specific attack behavior that the target mining pool needs to perform, and determine the specific incentive amount to be given to the target mining pool. When the attacker publishes a smart contract for incentives, the attacker first publishes the incentive smart contract, and the target mining pool willing to accept the incentive will choose to call the incentive smart contract and perform the corresponding attack behavior according to the requirements specified in the incentive smart contract.

[0105] Step S2: Based on the initial parameters, a mechanism for paying and receiving incentives is constructed. If the two parties establish a cooperative relationship, the target mining pool adjusts the on-chain game strategy.

[0106] Specifically, step S2 includes the following sub-steps:

[0107] Step 2.1: Based on the initial amount of the incentive, the attacker sends an incentive payment request to the target mining pool through the mining pool management module of the BM-PAW system, and attaches the initial amount of the incentive and payment conditions.

[0108] Step S2.2: After receiving the incentive payment request, the target mining pool verifies and confirms whether to accept the incentive payment request. If accepted, the two parties establish a cooperative relationship. The target mining pool sends a confirmation message to the attacker through the mining pool management module and adjusts the preset on-chain game strategy according to the attacker's requirements. If not accepted, return to step S2.1.

[0109] In this embodiment, the verification content includes: whether the target address of the incentive payment request matches the address of the target mining pool.

[0110] Step S3, based on the initial parameters and on-chain game strategy, carry out computing power adjustment and on-chain game to create block forks.

[0111] Specifically, step S3 includes the following sub-steps:

[0112] In step S3.1, the attacker obtains the optimal computing power allocation plan through calculation by the strategy execution module based on the current network status, its own risk resistance and initial parameters.

[0113] Specifically, based on the computing power allocation ratio, the strategy execution module performs calculations and allocates the gaming computing power on the infiltration chain to the target mining pool according to the step size of the computing power adjustment. At the same time, the attacker determines the portion of computing power reserved for supporting forked chain mining based on the fork length threshold, and obtains the optimal computing power allocation plan to improve the success rate and profit level of fork competition.

[0114] In step S3.2, the attacker and the target mining pool conduct on-chain games according to the on-chain game strategies respectively. The attacker controls the infiltration on-chain game computing power allocated by himself and works together with the computing power of the target mining pool based on the optimal computing power allocation plan to create a block fork.

[0115] In this embodiment, the strategy execution module executes the on-chain game task according to the on-chain game strategy. The network communication module ensures that the forked blocks are propagated to the target mining pool and other related nodes in a timely and accurate manner.

[0116] Step S4, obtaining the profit distribution ratio through fork monitoring and merging operations.

[0117] Specifically, step S4 includes the following sub-steps:

[0118] Step S4.1, through the data analysis and monitoring module, the block fork in the blockchain network is monitored in real time. Once a fork is detected, the length and status information of the forked chain are recorded.

[0119] Step S4.2, when the length of the forked chain reaches the preset threshold, the attacker evaluates the feasibility of merging the forked chain through the policy execution module. If the evaluation result shows that the merger operation is expected to bring higher benefits, the merger decision is passed.

[0120] Step S4.3, after the merger decision is passed, the attacker merges the forked chain back to the main chain by controlling the game computing power on its own penetration chain and the computing power of the target mining pool. After the merger is successful, the attacker and the target mining pool determine the profit distribution ratio based on the proportion of their respective contributed computing power.

[0121] Step S5: Based on the profit distribution ratio, profit distribution and strategy adjustment are performed.

[0122] Specifically, step S5 includes the following sub-steps:

[0123] Step S5.1: After each fork attack, the BM-PAW system distributes the additional revenue to the attacker and the target mining pool according to the revenue distribution ratio.

[0124] Furthermore, the distribution ratio may be adjusted based on the initial amount of the incentive.

[0125] Step S5.2: Based on the results of each attack and changes in network conditions, the attacker evaluates the effectiveness of the current strategy through the data analysis and monitoring module, and adjusts the initial parameters, including the amount of incentives and the computing power allocation ratio, for subsequent attacks.

[0126] Example 3: On-chain game attack practice based on BM-PAW method

[0127] Scene Setting:

[0128] Assume that there is a blockchain network called "AlphaNet" with multiple mining pools, each with different scales of computing power. The attacker "MinerX" decides to launch a BM-PAW attack on one of the mining pools with moderate computing power, "BetaPool", to obtain additional on-chain gaming benefits.

[0129] Step 1: Initialization and parameter setting

[0130] MinerX sets the initial incentive ratio to ε1=0.1 and ε2=0.1, the computing power adjustment step to 5%, and the fork length threshold to 1 block.

[0131] MinerX sends an incentive payment request to BetaPool through the mining pool management module of the BM-PAW system, and attaches the payment conditions and expected profit distribution plan.

[0132] Step 2: Payment and receipt of incentive funds

[0133] After receiving the payment request, BetaPool evaluated MinerX’s reputation and expected returns, decided to accept the incentive, and established a partnership.

[0134] The two parties ensure the transparency of the payment and distribution of incentive funds through smart contracts, and clearly stipulate the rights and obligations of both parties during the attack.

[0135] Step 3: Hashrate Adjustment and On-chain Gaming

[0136] MinerX calculates the optimal computing power allocation plan based on the current network status and BetaPool's computing power scale through the strategy execution module, and allocates part of the computing power to BetaPool.

[0137] MinerX and BetaPool conduct on-chain games according to preset on-chain game strategies respectively. MinerX controls its infiltrated on-chain game computing power to work together with BetaPool's computing power to create block forks.

[0138] Step 4: Fork monitoring and merging

[0139] During the on-chain game, the data analysis and monitoring module of the BM-PAW system detected in real time the emergence of a forked chain jointly maintained by MinerX and BetaPool in the blockchain network.

[0140] When the length of the forked chain reaches 1 block, MinerX evaluates the feasibility of the merger through the strategy execution module and decides to initiate the merger operation.

[0141] After the merge operation is successfully executed, the forked chain is merged back to the main chain, and MinerX and BetaPool distribute the additional profits according to the proportion of their respective contributed computing power.

[0142] Step 5: Profit distribution and strategy adjustment

[0143] After the merger is successful, the BM-PAW system will distribute the additional profits to MinerX and BetaPool according to the preset profit distribution rules.

[0144] Based on the results of this attack and changes in network conditions, MinerX evaluates the effectiveness of the current strategy through the data analysis and monitoring module, and adjusts parameters such as the incentive ratio and computing power allocation ratio to optimize the effects of subsequent attacks.

[0145] Experimental Results

[0146] The expected relative extra reward (RER) is used to evaluate the BM-PAW attack, which can be expressed as Where τ represents the role of the participant (i.e. attacker (α), target (t), etc.), S represents different on-chain game strategies (i.e. BM-PAW, PAW, etc.), Indicates the reward of participant τ. In order to verify the effectiveness of the BM-PAW algorithm, a Monte Carlo simulator was implemented and a simulation experiment was conducted. The experimental results show that by reasonably setting the incentive amount, compared with the PAW attack, the BM-PAW attack can bring higher benefits to both the attacker and the target mining pool, thereby achieving incentive compatibility.

[0147] 8.1 Experimental parameters:

[0148] Attacker’s computing power α = 0.2

[0149] Victim mining pool hashrate β = {0.1, 0.2, 0.3}

[0150] Target mining pool computing power η = {0.1, 0.2}

[0151] Other miners’ computing power δ=1-α-β-η

[0152] The proportion of other miners who choose the branch where the attacker's FPoW is located as the main chainγ=0.5

[0153] In case 5-2, when the target mining pool chooses to accept the incentive, the proportion of the incentive that the attacker is willing to pay for each block is ε1 = 0.1

[0154] In case 5-4, when the target mining pool chooses to accept the incentive, the proportion of the incentive that the attacker is willing to pay for each block is ε2 = 0.1

[0155] Simulator runs 10 times 9

[0156] 8.2 Experimental results analysis:

[0157] First, consider a specific case: the attacker's on-chain gaming power α = 0.2, and the victim's mining pool's on-chain gaming power β = 0.2.

[0158] The on-chain gaming power of the target mining pool is η = 0.2, and the proportion of other miners who choose the branch where the attacker's FPoW is located as the main chain is γ = 0.5. like Figure 3 As shown in Figure 2. The left side of the solid line indicates that BM-PAW attackers can obtain more benefits than PAW. In addition, as the ratio between the incentive ratios ε1 and ε2 decreases, the relative additional benefits of BM-PAW attackers will gradually increase.

[0159] Consider β = 0.2, the minimum ratio of ε1 and ε2, with changes in α and η like Figure 4 As shown in the figure. The area below the solid line indicates that BM-PAW is the dominant on-chain gaming strategy compared to PAW. When the on-chain gaming computing power of the victim mining pool decreases, the attacker's relative additional benefits will increase because the attacker can obtain a higher share reward from the target mining pool. At the same time, when the on-chain gaming computing power controlled by the target mining pool is relatively small, regardless of the scale of the attacker's own on-chain gaming computing power, he has a strong motivation to launch a BM-PAW attack. This is because, when the target mining pool has weak computing power, the attacker can more easily influence the decision of the target mining pool through bribery and other means, thereby increasing the chance of his FPoW winning the fork competition. Compared with traditional attack methods, BM-PAW attacks are more profitable in this case because the attacker can obtain a higher probability of success at a lower cost. Therefore, when the computing power of the target mining pool is limited, launching a BM-PAW attack becomes an optimal choice for the attacker.

[0160] Considering α=0.2,η={0.1,0.2,0.3},β={0.1,0.2,0.3}, the smallest ε1 and ε2 ratio, different γ like Figure 5 As shown in Figure 2. The attacker’s RER is related to his network power. When the on-chain gaming power of the victim pool infiltrated by the attacker is low, he can obtain higher profits regardless of his network power because the attacker can obtain more share rewards from the target mining pool. Therefore, mining pools with lower on-chain gaming power are more vulnerable to attacks.

[0161] Figure 6 It shows the change of α when β=0.2,η=0.2, the minimum ε1 and ε2 ratio, γ={0:0.1:1} The results show that the attacker's network capabilities can affect both BM-PAW and PAW.

[0162] Figure 7 The plot shows the change of ε1 and ε2 when α=0.2, β=0.2, η=0.2, γ=0.5. The area to the right of the solid line indicates that the target mining pool that accepts the incentive can get more rewards than rejecting the incentive. The relative additional benefits of the target mining pool increase with the increase of ε1 and ε2, because the reward of the target mining pool is positively correlated with the incentive that the attacker is willing to pay. Therefore, when the attacker provides appropriate incentives, accepting the incentive is always the best strategy for the target mining pool.

[0163] also, Figure 8 The results show that the maximum ratio of ε1 to ε2 is different for different α values ​​when β = 0.2, η = 0.2, γ = 0.5. When the attacker pays the maximum incentive amount, the target mining pool can always get the highest reward. Therefore, no matter how much on-chain gaming computing power the target mining pool has, accepting the incentive is always the best strategy.

[0164] Consider α=0.2,η={0.1,0.2},β={0.1,0.2,0.3}, the maximum ε1 and ε2 ratio, Fig. 9 Shows the different γ The graphical results show that the target mining pool has an incentive to accept the incentive in all cases. Similarly, when the on-chain gaming power of the victim pool decreases, the relative additional revenue of the target mining pool will also increase, because the target can obtain more incentives from the attacker's share reward.

[0165] Fig.10 The plot shows the maximum ε1 and ε2 ratio when β = 0.2, η = 0.2, and γ = {0:0.1:1}, as α changes. The experimental results show that the attacker's network capabilities affect both BM-PAW and PAW, so stronger network capabilities do not always bring higher relative additional benefits to the target mining pool.

[0166] Through the demonstration of Example 3, it can be seen that the BM-PAW algorithm and its system have the following technical effects and advantages in practical applications:

[0167] Improve on-chain gaming benefits: By introducing incentive mechanisms and optimizing computing power allocation strategies, the BM-PAW algorithm can significantly improve on-chain gaming benefits.

[0168] Enhanced network security: By dynamically adjusting policy parameters and monitoring network conditions in real time, the BM-PAW algorithm can promptly detect and respond to potential security threats, thereby improving the overall security of the blockchain network.

[0169] Achieve incentive compatibility: By reasonably setting the incentive amount and policy parameters, the BM-PAW algorithm can achieve incentive compatibility between the attacker and the target mining pool, ensuring that both parties can obtain higher returns in the process of participating in the attack. Improve the success rate of fork competition: By optimizing the computing power allocation and fork and merge mechanisms, the BM-PAW algorithm can significantly improve the success rate of block fork competition, thereby increasing the opportunities for attackers and target mining pools to obtain additional benefits through fork attacks.

[0170] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0171] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An incentive-compatible on-chain gaming system based on dynamic adjustment of computing power, characterized in that: include: Mining pool management module: including a miner registration unit, a computing power allocation unit and a block verification unit. The mining pool management module is responsible for the management and scheduling of the mining pool, receiving and processing incentive payment requests from attackers, and responding to the incentive payment requests according to preset strategies; Network communication module: responsible for the communication between nodes and the propagation of blocks in the blockchain network; Strategy execution module: responsible for monitoring network status, adjusting computing power allocation, launching fork attacks, and merging forked chains; Data analysis and monitoring module: used to analyze and monitor the data in the blockchain network in real time. The data analysis and monitoring module includes block propagation speed, network latency and mining pool computing power distribution, and provides decision support for the strategy execution module through analysis of the data; Among them, the mining pool management module, the network communication module, the strategy execution module and the data analysis and monitoring module work together to realize the overall function of the incentive-compatible on-chain game system based on dynamic adjustment of computing power.

2. An incentive-compatible on-chain game method based on dynamic adjustment of computing power, based on the incentive-compatible on-chain game system based on dynamic adjustment of computing power according to claim 1, characterized in that: The steps include: Step S1, set initial parameters and select target mining pool; Step S2, based on the initial parameters, construct a mechanism for payment and receipt of incentive funds. If the two parties establish a cooperative relationship, the target mining pool adjusts the on-chain game strategy; Step S3, based on the initial parameters and the on-chain game strategy, carry out computing power adjustment and on-chain game to create a block fork; Step S4, obtaining the profit distribution ratio through fork monitoring and merging operations; Step S5: Based on the profit distribution ratio, profit distribution and strategy adjustment are performed.

3. According to claim 2, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: The step S1 includes the following sub-steps: Step S1.1, the attacker sets the initial parameters, including the initial amount of incentive funds, the step size of computing power adjustment, the fork length threshold, and the computing power allocation ratio; In step S1.2, the attacker selects a target mining pool as the target of attack based on the mining pool computing power distribution information, network delay data and the initial amount of the incentive fee.

4. According to claim 3, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: In step S1.1, the initial amount of the incentive is dynamically adjusted according to the computing power scale of the target mining pool, the network status and the expected profit of the attacker.

5. According to claim 3, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: In step S1.2, there are two ways for the attacker to determine the target mining pool: one is to determine the target mining pool through offline incentives; the other is to determine the target mining pool by issuing a smart contract for incentives.

6. According to claim 2, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: The step S2 includes the following sub-steps: Step 2.1, based on the initial amount of the incentive, the attacker sends an incentive payment request to the target mining pool through the mining pool management module of the BM-PAW system, and attaches the initial amount of the incentive and payment conditions; Step S2.2: After receiving the incentive payment request, the target mining pool verifies and confirms whether to accept the incentive payment request. If accepted, the two parties establish a cooperative relationship. The target mining pool sends a confirmation message to the attacker through the mining pool management module and adjusts the preset on-chain game strategy according to the attacker's requirements. If not accepted, return to step S2.

1.

7. According to claim 5, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: In step S2.2, the verification content includes: whether the target address of the incentive payment request matches the address of the target mining pool.

8. According to claim 2, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: The step S3 includes the following sub-steps: Step S3.1, the attacker obtains the optimal computing power allocation plan through calculation by the strategy execution module according to the current network status, the attacker's own risk resistance and the initial parameters; In step S3.2, the attacker and the target mining pool conduct on-chain games according to the on-chain game strategies respectively. The attacker controls the infiltration on-chain game computing power allocated by itself to work in coordination with the computing power of the target mining pool based on the optimal computing power allocation plan to create a block fork.

9. According to claim 2, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: The step S4 includes the following sub-steps: Step S4.1, through the data analysis and monitoring module, the block fork in the blockchain network is monitored in real time. Once a fork is detected, the length and status information of the forked chain are recorded; Step S4.2: When the length of the forked chain reaches the preset threshold, the attacker evaluates the feasibility of merging the forked chain through the policy execution module. If the evaluation result shows that the merger operation is expected to bring higher benefits, the merger decision is passed; Step S4.3, after the merger decision is passed, the attacker merges the forked chain back to the main chain by controlling the game computing power on its own penetration chain and the computing power of the target mining pool. After the merger is successful, the attacker and the target mining pool determine the profit distribution ratio based on the proportion of their respective contributed computing power.

10. According to claim 2, an incentive-compatible on-chain game method based on dynamic adjustment of computing power is characterized in that: The step S5 comprises the following sub-steps: Step S5.1, after each fork attack ends, the additional revenue is distributed to the attacker and the target mining pool according to the revenue distribution ratio; Step S5.2, based on the results of each attack and changes in network conditions, the attacker evaluates the effectiveness of the current strategy through the data analysis and monitoring module, and adjusts the initial parameters in a timely manner for subsequent attacks.

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