An internet of things competition information interaction security method and system

Abstract

The present application relates to the technical field of information interaction security, and particularly relates to a kind of IOT competitive information interaction security method and system, the method comprises the following steps: current competitive situation information and the type information of data packet are acquired, and according to current competitive situation information and the type information of data packet, the competitive influence weight of data packet is evaluated;Network transmission exception information of data packet is acquired, and according to network transmission exception information and the competitive influence weight of data packet, the influence level of network transmission exception to competition is identified;When the influence level belongs to the high influence level set, the expected operation result of the operation instruction corresponding to data packet under the condition of no network transmission exception is simulated, and the actual operation result of operation instruction is acquired;The actual influence degree of network transmission exception to operation instruction is determined by comparing expected operation result and actual operation result;According to actual influence degree, hierarchical response measures are taken to network transmission exception.The above can improve the fairness of competition.

Description

Technical Field

[0001] This invention relates to the technical field of information interaction security, and specifically to a method and system for secure information interaction in IoT-based competitive sports. Background Technology

[0002] In IoT-based competitive sports, the security of information exchange is crucial for ensuring fairness and stable system operation. Participating devices collect players' operational commands, physiological data, and key information from the game environment in real time, transmitting this data to a data processing center via a low-latency wireless network. Traditionally, encryption and authentication mechanisms are used to ensure data accuracy and real-time performance. However, as the stakes in competitions increase, malicious actors are beginning to use more covert methods to influence match results by interfering with the timing and integrity of data transmission, rather than directly tampering with the data content. This interference is often localized, instantaneous, and difficult to detect, and its behavior pattern is very similar to occasional network fluctuations or environmental disturbances, causing data to become invalid over time, thus substantially damaging the fairness of the competition. Summary of the Invention

[0003] The purpose of this invention is to address the aforementioned shortcomings by proposing a secure method and system for IoT-based competitive information interaction.

[0004] The present invention adopts the following technical solution: A method for secure information exchange in IoT-based competitive sports, comprising the following steps: Obtain current competitive context information and data packet type information, and evaluate the competitive impact weight of the data packet based on the current competitive context information and data packet type information; Obtain network transmission anomaly information of data packets, and identify the impact level of network transmission anomalies on the competition based on the network transmission anomaly information and the competition impact weight of data packets; When the impact level is set to the high impact level, simulate the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission abnormality, and obtain the actual operation result of the operation instruction; By comparing the expected and actual operational results, the actual impact of network transmission anomalies on operational instructions can be determined. Based on the actual degree of impact, tiered response measures will be taken for network transmission anomalies.

[0005] Through this technical solution, this application can effectively identify and quantify the impact of network transmission anomalies on IoT competitions, and take graded response measures according to the degree of impact, thereby ensuring the fairness of the competition and solving the problem that traditional methods are difficult to identify subtle malicious interference.

[0006] Furthermore, based on the above methods, the steps to determine the actual impact of network transmission anomalies on operational instructions by comparing the expected operational results with the actual operational results include: By comparing the expected and actual operational results, the initial impact of network transmission anomalies on operational instructions can be obtained. Obtain the player's operation sequence corresponding to the operation command; Based on the player's action sequence, identify the player's tactical intentions and the final strength value of those intentions; To determine whether there is a conflict between the player's tactical intentions and the game state on which the expected operational results are based; If a conflict exists and the final intensity value of the tactical intention reaches the preset intensity threshold, the initial impact level is adjusted based on the player's tactical intention and the final intensity value of the tactical intention to obtain the actual impact of the network transmission anomaly on the operation command. If there is no conflict or the final intensity value of the tactical intent does not reach the preset intensity threshold, the initial impact level will be taken as the actual impact of the network transmission anomaly on the operational instructions.

[0007] Furthermore, the steps for identifying a player's tactical intentions and their final intensity value based on the player's action sequence include: Obtain the player's action sequence and current competitive situation information; Extract characteristic operations related to the preset reference tactical intentions from the player's operation sequence, and obtain the occurrence of characteristic operations; Analyze the player's operation sequence to obtain the coherence of the operation sequence; Based on the current competitive context, adjust the weight of characteristic operations and the matching tolerance for core operational elements defined by the reference tactical intent; In the contestant's operation sequence, the occurrence of core operation elements is matched according to the matching tolerance, and the core operation elements are allowed to vary within a preset threshold range in terms of time sequence or time interval, so as to obtain the matching degree of the core operation elements. Based on the matching degree of core operational elements, the occurrence of characteristic operations, and the coherence of the player's operational sequence, calculate the final intensity value of one or more tactical intentions. Based on the current competitive situation information, the current competitive situation is obtained; When there are multiple candidate tactical intentions, priority is determined based on the candidate strength value of each candidate tactical intention and the degree of fit between the candidate tactical intention and the current competitive situation, and the candidate tactical intention with the highest priority is selected as the player's tactical intention.

[0008] Furthermore, the steps of adjusting the weights of characteristic operations and the matching tolerance for core operational elements defined by the reference tactical intent, based on the current competitive context information, include: Real-time analysis of the contestant's first operation command flow within a preset first time window to obtain the contestant's operation rhythm, operation coherence and operation accuracy; The deviation of the contestant's operational characteristics is calculated based on the contestant's operational rhythm, operational continuity, and operational precision. Based on the deviation of the player's operational characteristics and combined with the current competitive context information, the weight of the characteristic operations and the matching tolerance of the core operational elements defined for the reference tactical intent are adjusted.

[0009] Furthermore, the steps for evaluating the competitive impact weight of data packets include: Obtain the second operation command stream of the player corresponding to the data packet within the preset second time window, and identify the triggering operation of the actual key competitive event from the second operation command stream; Obtain instantaneous environmental change information related to the triggering operations of actual key competitive events in the game world corresponding to the data packet; The competitive impact weight of the data packet is evaluated based on the current competitive context information, data packet type information, actual key competitive events triggering operations, and instantaneous environmental change information.

[0010] Furthermore, the steps for identifying the triggering actions of actual key competitive events include: Analyze the types of operation instructions, the execution sequence of operation instructions, and the attribute changes of the operation objects in the second operation instruction stream; Based on the analysis results and the final correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template, the triggering operation of the actual key competitive event is identified from the second operation instruction stream.

[0011] Furthermore, the steps for obtaining the final correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template include: Based on the analysis results and the definition rules of the preset key competitive event template, the basic correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template is calculated. Obtain the current competitive context information corresponding to the operation instructions in the second operation instruction stream, and correct the basic correlation degree based on the current competitive context information to obtain the final correlation degree between the operation instructions in the second operation instruction stream and the preset key competitive event template.

[0012] Furthermore, the steps for refining the basic correlation include: Obtain the sequence of operation commands and the corresponding game state changes; Based on the sequence of operation instructions and changes in the game state, identify target instruction fragments in the sequence of operation instructions whose basic correlation is lower than a preset correlation threshold and which trigger changes in the game state. Based on the target instruction fragment, assess the impact of changes in game state on the competitive progress; The basic correlation is adjusted based on the degree of influence and the frequency of occurrence of the target instruction fragment. The current competitive context information includes the degree of influence and the frequency of occurrence of the target instruction fragment.

[0013] Furthermore, the steps for identifying target instruction fragments in the sequence of operation instructions that have a basic correlation degree lower than a preset correlation threshold and trigger a change in the game state include: Obtain the instantaneous change in game state after each operation instruction in the sequence of operation instructions is executed; Set a threshold for the significance of changes in game state; Group the operation instructions in the operation instruction sequence to form candidate operation combinations; Calculate the cumulative changes in the game state caused by candidate operation combinations within a preset third time window; Determine whether the cumulative change has reached the significance threshold; Determine whether the correlation between the candidate operation combination and the basic correlation is lower than a preset correlation threshold; If the cumulative change reaches the significance threshold and the basic correlation is lower than the preset correlation threshold, then the candidate operation combination is identified as the target instruction fragment in the operation instruction sequence whose basic correlation is lower than the preset correlation threshold and which triggers a change in the game state.

[0014] This application also discloses an IoT-based competitive information interaction security system, applied to the aforementioned IoT-based competitive information interaction security method, the system comprising: The evaluation module is used to obtain current competitive context information and data packet type information, and evaluate the competitive impact weight of the data packet based on the current competitive context information and data packet type information; The identification module is used to acquire network transmission anomaly information of data packets and identify the impact level of network transmission anomalies on the competition based on the network transmission anomaly information and the competition impact weight of data packets. The processing module, when the impact level is set to high impact level, simulates the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission abnormality, and obtains the actual operation result of the operation instruction. The determination module is used to compare the expected operation results with the actual operation results to determine the actual impact of network transmission anomalies on operation instructions. The response module takes tiered response measures to network transmission anomalies based on the actual degree of impact.

[0015] This application provides a system capable of implementing the above-mentioned method through this technical solution. Through modular design, the system can efficiently and accurately execute the IoT competitive information interaction security method, providing hardware and software support for competitive fairness.

[0016] This application can accurately quantify the damage to the fairness of competition caused by network anomalies and take targeted responses, thereby overcoming the risks of false alarms or missed alarms in the prior art and significantly improving the security, fairness and system stability of IoT competitive information interaction.

[0017] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for ensuring secure information exchange in IoT-based competitive sports according to the present invention. Figure 2 This is a schematic diagram of the structure of an IoT-based competitive information interaction security system according to the present invention. Detailed Implementation

[0019] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0020] This embodiment provides a secure method and system for IoT-based competitive information interaction, combined with... Figure 1 and Figure 2 As shown.

[0021] refer to Figure 1 A secure method for information exchange in IoT-based competitive sports, comprising the following steps: Obtain current competitive context information and data packet type information, and evaluate the competitive impact weight of the data packet based on the current competitive context information and data packet type information; Obtain network transmission anomaly information of data packets, and identify the impact level of network transmission anomalies on the competition based on the network transmission anomaly information and the competition impact weight of data packets; When the impact level is set to the high impact level, simulate the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission abnormality, and obtain the actual operation result of the operation instruction; By comparing the expected and actual operational results, the actual impact of network transmission anomalies on operational instructions can be determined. Based on the actual degree of impact, tiered response measures will be taken for network transmission anomalies.

[0022] This method aims to address the challenge of traditional security mechanisms in IoT esports, which struggle to effectively handle subtle network anomalies induced by malicious actors and designed to disrupt data transmission timing and integrity. By introducing an assessment of the competitive impact weight of data packets and identifying the level of impact of network transmission anomalies on competition, this application can more accurately pinpoint anomalies that pose a substantial threat to the fairness of the competition. Furthermore, by simulating the expected operational results under anomaly-free conditions and comparing them with the actual operational results, the actual impact of network transmission anomalies on player operations can be quantified, thus avoiding misjudgments that may result from relying solely on network indicators. Consequently, differentiated and tiered response measures can be implemented based on the actual degree of impact, ensuring the fairness and stability of the competitive environment.

[0023] Current competitive context information may include, but is not limited to, the game map, the current game phase (e.g., laning phase, team fight phase), player roles, and the economic status of both sides. Data packet type information may refer to operation command packets, status synchronization packets, chat packets, etc. In one implementation, a mapping table can be pre-defined, which directly assigns corresponding competitive impact weights based on different competitive contexts and data packet types. For example, in a team fight context, a data packet for a crucial skill release might be assigned a higher weight, while a non-critical movement command data packet might be assigned a lower weight. This mapping table can be manually configured by game developers or event organizers based on experience.

[0024] Network transmission anomalies can include packet loss rate, latency, jitter, and out-of-order delivery. One implementation can set fixed thresholds; for example, when the packet loss rate exceeds a certain percentage or the latency exceeds a certain number of milliseconds, the impact level of the data packet is directly determined as high, medium, or low, based on its competitive impact weight. For instance, if a high-weight data packet (such as a critical skill release command) has a latency exceeding 50 milliseconds, it is directly identified as having a high impact level.

[0025] Simulating the expected operation result can be achieved by setting up a local simulation environment synchronized with the game logic on the server. Upon receiving the operation command, this simulation environment executes it immediately under ideal network conditions and records the result. The actual operation result is obtained directly from the actual running game server or client. For example, when a shooting command is judged to be of high impact, the simulation environment immediately calculates the hit result of the shot under zero latency, while the actual result is the final hit result determined by the game server.

[0026] In one implementation, the difference between the expected and actual operation results can be directly compared. For example, if the expected operation result is that the character moves to point A, while the actual operation result is that the character stays at point B, the degree of impact can be quantified based on the distance between points A and B. Alternatively, if the expected operation result is that the skill hits the target, while the actual operation result is that the skill misses, it can be directly determined as a high impact. This comparison can be based on preset rules, such as comparing the numerical differences of key game state variables (such as health, position, and skill cooldown time).

[0027] Tiered response measures can vary depending on the actual level of impact. For example, when the actual impact is determined to be "high," measures such as automatic replay, suspension of the match, warning of players, or recording of evidence for post-match arbitration may be triggered; when the actual impact is "medium," only logging and notification to the backend monitoring system may be required; and when the actual impact is "low," no measures may be taken. The triggering conditions and specific execution methods of these response measures can be pre-configured.

[0028] The steps to determine the actual impact of network transmission anomalies on operational instructions by comparing the expected and actual operational results include: By comparing the expected and actual operational results, the initial impact of network transmission anomalies on operational instructions can be obtained. Obtain the player's operation sequence corresponding to the operation command; Based on the player's action sequence, identify the player's tactical intentions and the final strength value of those intentions; To determine whether there is a conflict between the player's tactical intentions and the game state on which the expected operational results are based; If a conflict exists and the final intensity value of the tactical intention reaches the preset intensity threshold, the initial impact level is adjusted based on the player's tactical intention and the final intensity value of the tactical intention to obtain the actual impact of the network transmission anomaly on the operation command. If there is no conflict or the final intensity value of the tactical intent does not reach the preset intensity threshold, the initial impact level will be taken as the actual impact of the network transmission anomaly on the operational instructions.

[0029] Specifically, "initial impact level" refers to the initial assessment value obtained by directly comparing the expected and actual operation results of the operation instructions under conditions of no network transmission anomalies. It reflects the direct deviation from the operation results. For example, it can be quantified as the numerical difference, state difference, or difference in the degree of functional realization between the expected and actual results.

[0030] "Player operation sequence" refers to a set of operation instructions executed by a player within a specific time period. It contains the continuity of the player's behavior and contextual information, and is an important basis for analyzing the player's tactical intentions.

[0031] "Identifying a player's tactical intentions and their ultimate intensity" refers to analyzing a player's action sequence to infer their expected strategic or tactical objectives in the current competitive situation, and quantifying the importance or determination to execute that tactical intention. For example, a tactical intention could be "focusing fire on a specific target," "making a defensive retreat," or "unleashing a combination of skills." The ultimate intensity value indicates the player's level of commitment to or reliance on that tactical intention; a higher intensity value indicates a greater impact of that intention on the player's performance.

[0032] "Assessing whether there is a conflict between the player's tactical intentions and the game state upon which the expected operational outcome is based" refers to evaluating whether the operational outcome caused by network transmission anomalies directly hinders the player from achieving their expected tactical goals, or whether it adversely changes the game state upon which the player depends to achieve their tactical intentions. For example, if a player intends to control an enemy unit with a certain skill, but due to a network anomaly, the skill misses and the enemy unit is not controlled, then there is a conflict between the tactical intentions and the actual game state.

[0033] "Adjusting the initial impact level" refers to adjusting the initial impact level assessment when network transmission anomalies not only cause deviations in operational results but also conflict with the player's core tactical intentions, and the final intensity value of these tactical intentions reaches a preset intensity threshold. This adjustment aims to more accurately reflect the deeper impact of network anomalies on the competition. This adjustment can manifest as increasing the impact level or adding weight to the quantitative value. If no such conflict exists, or the intensity of the tactical intentions does not reach a threshold sufficient to affect the overall assessment, the initial impact level is considered sufficient to represent the actual impact level.

[0034] In one specific implementation, suppose in a multiplayer online competitive game, a player is attempting to execute a complex skill combo with the tactical intent of quickly defeating an enemy target. During execution, due to a network transmission anomaly, the data packet for a key skill command is delayed, causing the skill to fail to be released at the expected time or to be released at an off-target.

[0035] First, the system compares the expected outcome of the skill command under conditions of no network transmission anomalies (e.g., the enemy target is defeated or suffers a large amount of damage) with the actual outcome (e.g., the skill misses or the damage is insufficient) to obtain an initial degree of impact.

[0036] Next, the system analyzes the player's sequence of actions to identify their tactical intention to "quickly defeat the enemy target" and calculates the final strength value of that intention. For example, by analyzing the density of actions and the complexity of skill combinations, the system determines that the strength is high.

[0037] The system then determines whether there is a conflict between the player's tactical intention (to defeat the enemy target) and the game state upon which the actual operation result due to the network anomaly is based (e.g., the enemy target is still alive and in good condition). In this example, a conflict exists because the key skill failed to function as expected, causing the tactical intention to fail.

[0038] Because of the conflict and the fact that the final intensity value of the tactical intention has reached the preset intensity threshold, the system will adjust the initial impact level based on the player's tactical intention and its final intensity value. For example, even if the initial impact level may only show as "skill missed", considering its serious obstruction to the player's high-intensity tactical intention of "quickly defeating the enemy target", the actual impact level will be adjusted to "serious tactical interruption", thereby triggering a higher level of response measures, such as providing stronger compensation or a more detailed anomaly report.

[0039] Conversely, if the intensity of the tactical intent identified in the player's action sequence is low, or if the action result is deviated but does not substantially conflict with the tactical intent (for example, the player simply releases a non-critical skill), then the initial impact level will be directly taken as the actual impact level without correction.

[0040] This application further proposes steps for identifying a player's tactical intentions and the final strength value of those intentions based on the player's action sequence, including: Obtain the player's action sequence and current competitive situation information; Extract characteristic operations related to the preset reference tactical intentions from the player's operation sequence, and obtain the occurrence of characteristic operations; Analyze the player's operation sequence to obtain the coherence of the operation sequence; Based on the current competitive context, adjust the weight of characteristic operations and the matching tolerance for core operational elements defined by the reference tactical intent; In the contestant's operation sequence, the occurrence of core operation elements is matched according to the matching tolerance, and the core operation elements are allowed to vary within a preset threshold range in terms of time sequence or time interval, so as to obtain the matching degree of the core operation elements. Based on the matching degree of core operational elements, the occurrence of characteristic operations, and the coherence of the player's operational sequence, calculate the final intensity value of one or more tactical intentions. Based on the current competitive situation information, the current competitive situation is obtained; When there are multiple candidate tactical intentions, priority is determined based on the candidate strength value of each candidate tactical intention and the degree of fit between the candidate tactical intention and the current competitive situation, and the candidate tactical intention with the highest priority is selected as the player's tactical intention.

[0041] Specifically, a player's action sequence refers to the set of all action commands input by the player within a specific time period, such as mouse clicks, keyboard presses, and skill activations. Current competitive situation information can be understood as a snapshot of the game world's state at a specific moment, including but not limited to character position, health, skill cooldowns, map visibility, and the distribution of friendly and enemy units.

[0042] Among these, the preset reference tactical intentions refer to a series of typical tactical patterns predefined for a specific game or competitive genre, such as "Gank," "Push," and "Counter-Attack." Characteristic operations refer to the key, signature operational instructions or sequences that constitute these tactical intentions. For example, in multiplayer online tactical competitive games, a hero's specific skill combo can be considered a characteristic operation. The occurrence of characteristic operations refers to information such as whether these characteristic operations appear in the player's operation sequence, their frequency of occurrence, and their relative position.

[0043] The coherence of a contestant's operational sequence refers to the time intervals between commands, the rhythm of the operation, and the smoothness of the execution. For example, continuous and tightly packed operations are generally considered to have high coherence, while interruptions or chaotic rhythms may indicate low coherence. Coherence can be quantified by analyzing differences in timestamps between commands and the frequency of command type transitions.

[0044] Furthermore, the weight of a feature operation refers to the degree of importance of different feature operations in identifying tactical intentions. Core operational elements refer to the most critical and indispensable operational instructions or sequences that constitute a tactical intention. Match tolerance refers to the range of deviations allowed in the temporal order or time interval when matching core operational elements. For example, in some tactics, the order of skill releases may be strictly fixed, while in others, the interval between skill releases may allow for some flexibility. Adjusting the weights and match tolerance based on the current competitive context aims to make the identification of tactical intentions more adaptable to the real-time game state. For example, in a disadvantageous situation, the weight of feature operations in defensive tactics may be increased, while the match tolerance for offensive tactics may be relaxed to accommodate the player's operational variations under pressure.

[0045] When matching the occurrence of core operational elements within a player's operational sequence based on a matching tolerance, dynamic programming, fuzzy matching, or sequence alignment algorithms can be employed. Allowing core operational elements to vary within a preset threshold range in terms of temporal order or time interval means that even if a player's actions deviate slightly due to network transmission anomalies or personal habits, as long as their core intent remains unchanged, they can still be accurately identified. Thus, the matching degree of the core operational elements can be obtained, which quantifies the degree to which the player's actions conform to the preset tactical intent.

[0046] Ultimately, based on the degree of matching of core operational elements, the occurrence of characteristic operations, and the coherence of the player's operational sequence, the final intensity value of one or more tactical intentions can be calculated. This intensity value comprehensively reflects the likelihood and determination of the player to execute a specific tactical intention. For example, the higher the degree of matching, the more complete the occurrence of characteristic operations, and the better the operational coherence, the higher the final intensity value of the tactical intention.

[0047] When multiple candidate tactical intentions exist, such as when a player's action sequence might simultaneously fit both "push" and "ambush" tactical patterns, priority must be determined based on the candidate strength value and the degree of fit between each candidate tactical intention and the current competitive situation. Fit refers to the degree to which the tactical intention matches the current game state; for example, under the enemy's high ground tower, a push tactic usually has a higher fit than an ambush tactic. By comprehensively considering both strength value and fit, the candidate tactical intention with the highest priority is selected as the player's tactical intention, thus avoiding misjudgment.

[0048] This application's solution overcomes the limitations of traditional methods in identifying tactical intentions in complex competitive situations by introducing refined analysis of player operation sequences, including feature operation extraction, evaluation of operation coherence, and flexible matching of core operation elements. Specifically, by acquiring player operation sequences and current competitive situation information, a comprehensive data foundation is provided for tactical intention identification. Extracting feature operations from player operation sequences and analyzing their occurrence can capture key patterns in player operations. Simultaneously, analyzing the coherence of player operation sequences helps determine the fluency of player operations and the clarity of intent.

[0049] Furthermore, by dynamically adjusting the weights of characteristic operations and the matching tolerance of core operational elements based on the current competitive context, the identification of tactical intentions can adapt to real-time changes in the game process and subtle differences in player operations. Even when network transmission anomalies cause operational distortions, the player's true intentions can still be identified through a flexible matching mechanism. Therefore, by calculating the final strength value of tactical intentions based on the matching degree of core operational elements, the occurrence of characteristic operations, and the coherence of the player's operational sequence, the clarity and enforceability of tactical intentions can be quantified. When multiple candidate tactical intentions exist, priority is determined by considering their relevance to the current competitive context, ensuring that the most realistic tactical intention is selected even in ambiguous situations. This multi-dimensional, context-aware identification mechanism significantly improves the accuracy and robustness of tactical intention identification, thus providing a more reliable basis for subsequently correcting the actual impact of network transmission anomalies on operational commands.

[0050] In some preferred embodiments, it is assumed that in a multiplayer online tactical game, a player is attempting to execute a "tower dive kill" tactical intent.

[0051] First, the system will obtain the player's action sequence within a short period of time, such as: movement command (towards the enemy turret), skill A release, skill B release, basic attack command (targeting an enemy hero), and flash skill release. Simultaneously, it will obtain current competitive situation information, including the enemy hero's health, the turret's health, the number of friendly minions, the cooldown status of friendly hero skills, and the position of enemy heroes.

[0052] Next, the system will extract characteristic operations related to the preset "tower dive kill" tactical intent from the player's operation sequence, such as "combo of skill A + skill B", "continuous attack on enemy heroes", and "movement towards the turret", and obtain the occurrence of these characteristic operations. At the same time, it will analyze the coherence of the player's operation sequence, such as whether the time interval between skill release and movement command is tight and whether the operation is smooth.

[0053] Furthermore, based on the current competitive context, the system dynamically adjusts the weight of characteristic operations and the matching tolerance of core operation elements. For example, if the enemy hero's health is extremely low, the weight of "kill" related operations (such as skill damage) will be increased; if the player is attacked under the tower, the matching tolerance for "flash" or "displacement" skills may be relaxed, allowing for a slight delay within a preset time window.

[0054] Within the player's action sequence, the system matches the occurrence of core action elements such as "Skill A + Skill B combo" and "continuous attacks on enemy heroes" based on the adjusted match tolerance. Even if Skill B is released 50 milliseconds later than expected due to network transmission anomalies, the combo will still be recognized as a valid match as long as it remains within the preset threshold. This determines the matching degree of the core action elements.

[0055] Ultimately, the system calculates the final strength value of the "tower dive kill" tactical intention based on the matching degree of core operational elements, the occurrence of characteristic operations, and the coherence of the player's operation sequence. For example, if all core operational elements match well and the operation coherence is high, the strength value of the tactical intention will be very high. If there is also a candidate tactical intention of "retreat" (e.g., the player moves backward immediately after attacking), the system will determine that "tower dive kill" has higher priority based on the current competitive situation information (e.g., enemy reinforcements are about to arrive) and the candidate strength values ​​and fit of the two tactical intentions, thus identifying it as the player's tactical intention. In this way, even if network transmission anomalies cause imperfect operation, the system can accurately identify the player's true tactical intention, providing an accurate basis for subsequent assessment of the impact of anomalies.

[0056] This application further proposes a method for adjusting the weights of characteristic operations and the matching tolerance for core operational elements defined by reference tactical intent based on current competitive context information. This method includes: Real-time analysis of the contestant's first operation command flow within a preset first time window to obtain the contestant's operation rhythm, operation coherence and operation accuracy; The deviation of the contestant's operational characteristics is calculated based on the contestant's operational rhythm, operational continuity, and operational precision. Based on the deviation of the player's operational characteristics and combined with the current competitive context information, the weight of the characteristic operations and the matching tolerance of the core operational elements defined for the reference tactical intent are adjusted.

[0057] Specifically, real-time analysis of the player's first operation command flow within a preset first time window aims to dynamically capture the player's operational behavior patterns over a specific time period. The "first time window" can be understood as a relatively short period used to monitor the player's operational performance in real time, such as the most recent few seconds or tens of seconds. By analyzing the "first operation command flow" within this time window, the player's "operation rhythm" (the frequency and speed at which the player executes operation commands), "operation coherence" (the tightness of the time intervals and logical sequence between operation commands), and "operation precision" (the accuracy and effectiveness of the player's operation commands, such as whether the target is hit or the skill is successfully cast) can be obtained. These indicators collectively reflect the player's current operational status and proficiency.

[0058] Furthermore, based on the competitor's operational rhythm, consistency, and precision, the "deviation degree of the competitor's operational characteristics" can be calculated. This deviation degree refers to the degree of difference between the competitor's current operational performance and the preset normal or expected operational pattern. For example, a historical operational data model or standard operational pattern of the competitor can be established in advance, and then the operational rhythm, consistency, and precision acquired in real time can be compared with this model or pattern to quantify the degree of deviation. The higher the deviation degree, the more abnormal the competitor's current operational performance is, which may be affected by factors such as abnormal network transmission, psychological pressure, or physical fatigue.

[0059] Therefore, based on the deviation of the player's operational characteristics and combined with the current competitive context information, the "weight of characteristic operations" and the "matching tolerance for core operational elements defined by the reference tactical intent" can be adjusted. The "weight of characteristic operations" refers to the importance of different operational instructions or sequences in judging tactical intent. For example, the release of certain key skills may have a higher weight. The "matching tolerance for core operational elements" refers to the allowable range of deviation in the timing, time interval, or specific execution details of operational instructions when matching a player's operational sequence with a preset tactical intent template. When the deviation is high, the weight of characteristic operations can be appropriately reduced or the matching tolerance increased to accommodate the player's operational performance under abnormal conditions and avoid misjudging their tactical intent due to operational distortion. Simultaneously, by combining "current competitive context information," such as the game situation, the resource status of both sides, and map location, these parameters can be adjusted more precisely to ensure the accuracy and adaptability of tactical intent recognition.

[0060] This application's solution dynamically adjusts key parameters in the tactical intent recognition model by monitoring the player's performance in real time and quantifying its deviation from the normal state. Specifically, when a player's operation deviates, the system can adaptively adjust the importance of feature operations and the leniency of matching operation sequences based on the degree of deviation and the current competitive situation. For example, when network transmission anomalies cause stuttering or delays in a player's operation, their operational rhythm, coherence, and accuracy may decrease. In this case, by increasing the matching tolerance, even if the execution sequence or interval of the operation instructions deviates to a certain extent from the standard template, the system can still identify the player's original tactical intent, avoiding misjudging operational distortions caused by network anomalies as changes in tactical intent.

[0061] In some preferred embodiments, suppose a tactical intent called "Quick Dash" exists in a multiplayer online competitive game. Its core operational elements include the rapid execution of movement, attack, and control skills within a short period. Under normal circumstances, players execute this maneuver with a fast pace, high consistency, and high precision. However, when network transmission anomalies occur (e.g., high latency or packet loss), players executing the "Quick Dash" tactic may experience delays in movement skill execution, failure to seamlessly connect attack skills, or deviations in the positioning of control skills, resulting in a slower operational pace, decreased consistency, and reduced precision.

[0062] At this point, the proposed solution analyzes the player's first operation command flow within a preset first time window in real time, obtaining the player's current operation rhythm, operation coherence, and operation precision. For example, the system detects that the average interval between skill releases by the player has increased by 200 milliseconds compared to normal, and the skill hit rate has decreased by 10%. Based on this data, the system calculates that the player's operation characteristics have a high deviation. Combining the current competitive situation information (e.g., the player is under enemy fire suppression and needs to quickly escape or counterattack), the system dynamically adjusts the weight of characteristic operations and the matching tolerance of core operation elements in the "rapid advance" tactical intent template according to this deviation. Specifically, the system may reduce the strict requirements on skill release intervals (i.e., increase the matching tolerance), allowing for larger time deviations, while slightly reducing the weight of certain non-core attack skills and focusing more on the identification of displacement and control skills. Through this dynamic adjustment, even if the player's operation is distorted due to network anomalies, the system can still accurately identify their "rapid advance" tactical intent, avoiding misjudging it as other tactics or no tactical intent, thereby ensuring a more accurate assessment of the impact of network transmission anomalies on the competition.

[0063] Specifically, in the above-mentioned IoT competitive information interaction security method, the step of evaluating the competitive impact weight of data packets can be further refined as follows.

[0064] The steps for evaluating the competitive impact weight of a data packet include: obtaining the second operation command stream of the player corresponding to the data packet within a preset second time window, identifying the triggering operation of the actual key competitive event from the second operation command stream; obtaining the instantaneous environmental change information in the game world corresponding to the data packet and associated with the triggering operation of the actual key competitive event; and evaluating the competitive impact weight of the data packet based on the current competitive situation information, the type information of the data packet, the triggering operation of the actual key competitive event, and the instantaneous environmental change information.

[0065] The preset second time window can be understood as a specific time range before and after data packet transmission. For example, it can be set to 500 milliseconds before and after data packet transmission. Its purpose is to capture player actions closely related to the data packet transmission. The second operation command flow refers to the set of operation commands executed by the player within this second time window, such as movement commands, attack commands, and skill release commands. The triggering operation of the actual key competitive event refers to the event that is directly or indirectly caused by the player's operation during the game and has a significant impact on the competitive process, such as killing an opponent, destroying a target, or completing a task. These operations are the key basis for identifying the importance of data packets.

[0066] Furthermore, instantaneous environmental change information refers to the immediate environmental or state changes in the game world that are directly related to the triggering action of a key competitive event. Examples include a decrease in character health, a reset of skill cooldown time, a transfer of control of a map area, and a change in the occupation status of resource points. This information reflects the immediate feedback and impact of the action command on the game environment.

[0067] In practical applications, current competitive context information may include, but is not limited to, game phase (such as laning phase, team fight phase), economic disparity between the two sides, character status (such as health, mana, buffs / debuffs), and map resource distribution. Data packet type information can refer to the specific category of the operation instructions carried by the data packet, such as movement instructions, attack instructions, skill release instructions, and item usage instructions.

[0068] This application's solution acquires the second operation instruction stream of the player corresponding to the data packet within a preset second time window, and identifies the triggering operations of actual key competitive events from it. This allows for a deep understanding of the context and importance of the operation instructions carried by the data packet within the player's operation sequence. It is precisely because of the identification of the triggering operations of actual key competitive events that the system can focus on those operations that have a decisive impact on the competitive outcome. Simultaneously, by acquiring instantaneous environmental change information associated with these triggering operations, the actual effect of the operation instructions and their immediate impact on the game state can be further verified. Therefore, by combining the current competitive context information and the data packet type information, the system can comprehensively evaluate the actual competitive impact weight of the data packet in a specific competitive context from multiple dimensions, thus avoiding the one-sidedness of judging its importance solely based on the data packet type or simple context.

[0069] Specifically, the steps for identifying the triggering actions of actual key competitive events include: Analyze the types of operation instructions, the execution sequence of operation instructions, and the attribute changes of the operation objects in the second operation instruction stream; based on the analysis results and the final correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template, identify the triggering operations of the actual key competitive events from the second operation instruction stream.

[0070] The analysis of the second operation command flow, including the types of operation commands, their execution sequence, and the attribute changes of the objects targeted by those commands, involves a detailed analysis of the operation command flow generated by the player within a preset second time window. Specifically, the types of operation commands can include, but are not limited to, movement commands, attack commands, skill release commands, and item usage commands, representing the specific action categories performed by the player. The execution sequence of operation commands refers to the order and time intervals in which these commands are executed, which is crucial for understanding the coherence and rhythm of the player's actions. The attribute changes of the objects targeted by those operation commands refer to the changes in the attributes of relevant entities in the game world (such as player characters, enemy units, environmental objects, etc.) such as health, position, status, and item quantity after the operation command is executed. Through comprehensive analysis of this information, a detailed profile of the player's operational behavior and its real-time feedback in the game world can be constructed.

[0071] Furthermore, based on the above analysis results and the final correlation between the operation commands in the second operation command flow and the preset key competitive event templates, the triggering operations of actual key competitive events can be identified from the second operation command flow. The preset key competitive event templates are a predefined set of operation sequences, changes in the attributes of the operation objects, and their temporal relationships. These templates represent events of significant competitive importance in the game, such as "successfully killing an enemy," "completing a key objective," and "releasing a decisive skill." The final correlation quantifies the degree of matching between the actually observed operation command flow and these preset templates. By comparing the analyzed player's operational behavior with these templates and combining their correlation, the system can accurately identify which specific operation commands or sequences of operation commands are the core actions that cause or trigger key competitive events.

[0072] This application's solution, through in-depth analysis of the type, execution sequence, and changes in the attributes of the operation instructions, and matching them with preset key competitive event templates, can accurately locate the triggering operation of the actual key competitive event from a massive flow of operation instructions. This method enables the system not only to identify the occurrence of the event but also to trace the specific operational root cause of the event, thus providing a more accurate and reliable input for subsequent evaluation of the competitive impact weight of data packets. By quantifying the final correlation between the operation instructions and the key competitive event templates, it can be ensured that the correlation between the identified triggering operation and the competitive event reaches a preset confidence level, avoiding misjudgments.

[0073] The above technical solution enables refined identification of key competitive events triggered in IoT competitive environments. Compared to traditional methods that rely solely on in-game event logs, this solution delves into the operational command level, capturing the specific operational details and their temporal relationships that lead to key events, thus significantly improving the accuracy and robustness of identification. This precise identification capability allows subsequent evaluation of the impact weight of data packets on competitive scenarios to more closely resemble actual competitive situations, thereby enhancing the effectiveness and reliability of the entire IoT competitive information interaction security method.

[0074] This application further proposes steps for obtaining the final correlation between operation instructions and preset key competitive event templates in the second operation instruction stream, including: Based on the analysis results and the definition rules of the preset key competitive event template, the basic correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template is calculated. Obtain the current competitive context information corresponding to the operation instructions in the second operation instruction stream, and correct the basic correlation degree based on the current competitive context information to obtain the final correlation degree between the operation instructions in the second operation instruction stream and the preset key competitive event template.

[0075] Specifically, the above analysis results refer to the results obtained after analyzing the types of operation instructions, the execution sequence of operation instructions, and the attribute changes of the operation objects in the second operation instruction stream. The definition rules of the preset key competitive event template can be understood as a set of pre-defined patterns or conditions used to describe specific key competitive events. For example, a "kill" event template might be defined as a series of attack operations, the target's health dropping to zero, and the appearance of a kill notification. Basic correlation refers to the initial matching degree between the operation instruction sequence and the preset key competitive event template without considering the real-time competitive context. Current competitive context information may include, but is not limited to, dynamic environmental data such as in-game time, map area, player position, character status (e.g., health, mana, skill cooldown), troop distribution of both sides, and resource point status. Correcting the basic correlation refers to adjusting the initially calculated basic correlation based on the current competitive context information to more accurately reflect the actual importance or relevance of the operation instructions in the current competitive environment. Therefore, the final correlation is a more context-aware correlation value after correction based on the current competitive context information.

[0076] This application's solution provides a preliminary matching metric by first calculating the basic correlation between operational instructions and key competitive event templates. Based on this, it further incorporates current competitive context information to refine the basic correlation. Due to the dynamic and complex nature of competitive contexts, relying solely on static template matching may not accurately capture the true intent and impact of operational instructions. By taking current competitive context information into account—for example, when an operational instruction sequence has a high match with a key competitive event template, but the current competitive context indicates that the conditions for the event's occurrence are not ripe or its impact is weakened—the basic correlation is appropriately reduced; conversely, if the current competitive context is extremely favorable for the event's occurrence or its impact is amplified, the basic correlation is increased. This correction mechanism allows the final correlation to more accurately reflect the actual meaning and importance of the operational instructions in a specific competitive context.

[0077] In some preferred embodiments, assuming a pre-defined "tower-stealing" key competitive event template exists in a multiplayer online competitive game, the definition rules include: a player continuously attacks an enemy turret near an undefended enemy hero. When the system analyzes the second operation command stream and finds that the player has performed a series of tower-attacking operations, it calculates a high basic correlation. At this point, the system acquires the current competitive context information. If the current competitive context information shows that the player's teammates are engaged in combat with the enemy's main force in another area, attracting the enemy's attention, and the enemy turret's health is already low, then this context information will further enhance the effectiveness and criticality of the "tower-stealing" behavior, thus positively correcting the basic correlation and obtaining a higher final correlation. Conversely, if the current competitive context information shows that the enemy hero is quickly retreating, or the turret's health is still high, then even if the operation command sequence matches the template, the current competitive context information will negatively correct the basic correlation, reducing the final correlation, because the "tower-stealing" behavior at this time may not be an actual key competitive event, or its success rate and impact may be low. In this way, the system can more intelligently determine the true intent of the operation command and its importance in the current competitive situation.

[0078] This application further proposes steps for correcting the basic correlation, including: acquiring the operation instruction sequence and the corresponding game state changes; identifying target instruction fragments in the operation instruction sequence whose basic correlation is lower than a preset correlation threshold and which trigger game state changes based on the operation instruction sequence and game state changes; assessing the degree of influence of game state changes on the competitive process based on the target instruction fragments; and correcting the basic correlation based on the degree of influence and the frequency of occurrence of the target instruction fragments, wherein the current competitive context information includes the degree of influence and the frequency of occurrence of the target instruction fragments.

[0079] Specifically, when correcting the basic correlation, the first step is to obtain the sequence of operation instructions and the corresponding changes in the game state after the execution of these instructions. The sequence of operation instructions can be understood as a series of instructions continuously input by the player over a period of time, while the changes in the game state refer to the instantaneous or cumulative changes in character attributes, environmental elements, scoring, etc., in the game world after these instructions are executed.

[0080] Furthermore, based on the acquired sequence of operation commands and changes in game state, the system is configured to identify target command fragments within the sequence of operation commands that have a basic correlation with a preset correlation threshold but trigger significant changes in game state. Here, a target command fragment refers to a segment in the entire sequence of operation commands that, although initially correlated with a preset key competitive event template, results in an actual, observable change in game state upon execution. The preset correlation threshold is used to initially filter out seemingly unimportant operations.

[0081] Therefore, once these target command fragments are identified, the impact of the resulting changes in the game state on the competitive process can be assessed. The degree of impact can be quantified as favorable or unfavorable changes in the game situation, the gain or loss of key resources, or the achievement or obstruction of tactical objectives. For example, a seemingly simple movement command, if it leads to the exposure of a key enemy unit or the successful retreat of an allied unit, may be assessed as having a high degree of impact.

[0082] Finally, the previously calculated baseline correlation was revised based on the assessed degree of impact and the frequency of occurrence of the target instruction fragment. The degree of impact and the frequency of occurrence of the target instruction fragment were incorporated into the current competitive context information to more comprehensively reflect the actual competitive value of the operational instructions. In this way, even operations with low initial correlation but significant actual impact can have their baseline correlation reasonably improved, thus more accurately reflecting their importance in the competition.

[0083] As a specific implementation, suppose in a real-time strategy game, player A issues a series of seemingly ordinary unit movement commands. These commands have a low correlation with preset key competitive event templates such as "surprise attack" or "rally," for example, below a preset correlation threshold. However, the system detects through monitoring that these seemingly ordinary movement commands lead to the successful capture of a key resource point on the game map, or the successful encirclement of a high-value enemy unit. In this case, the system will identify these movement command sequences as target command fragments.

[0084] Furthermore, the system assesses the impact of these target command fragments on the game's progress, specifically the game state changes such as "capturing key resource points" or "encircling high-value enemy units." For example, capturing key resource points might be assessed as "high impact" because it directly increases the player's resource income and weakens the enemy. Simultaneously, the system records the frequency of these target command fragments in historical gameplay.

[0085] Ultimately, based on the assessed high impact level and the frequency of such operations (even if the frequency is low, the high impact is sufficient for correction), the system will adjust the basic correlation of these movement commands, elevating them to a more reasonable level. In this way, even if these operations do not perfectly conform to the preset key competitive event template, their importance can still be accurately identified and reflected because they have a significant positive impact in actual gameplay. This ensures a comprehensive understanding of the player's operational intentions and competitive events, and provides a more accurate basis for subsequent assessments of the impact of network transmission anomalies.

[0086] Specifically, the steps for identifying target instruction fragments in the operation instruction sequence that have a basic correlation degree lower than a preset correlation threshold and trigger a change in the game state may include the following: Get the instantaneous changes in the game state after each operation instruction in the sequence of operation instructions is executed; Set a threshold for the significance of changes in game state; Group the operation instructions in the operation instruction sequence to form candidate operation combinations; Calculate the cumulative changes in the game state caused by candidate operation combinations within a preset third time window; Determine whether the cumulative change has reached the significance threshold; Determine whether the correlation between the candidate operation combination and the basic correlation is lower than a preset correlation threshold; If the cumulative change reaches the significance threshold and the basic correlation is lower than the preset correlation threshold, then the candidate operation combination is identified as the target instruction fragment in the operation instruction sequence whose basic correlation is lower than the preset correlation threshold and which triggers a change in the game state.

[0087] In this context, instantaneous changes in game state refer to the immediate changes in the game world that occur after a player executes a certain operation command in an IoT-based competitive environment. These changes include character position, skill cooldown, item quantity, and environmental interactions. These changes are the result of the operation command directly affecting the game logic.

[0088] The significance threshold is used to quantify the degree of change in game state, distinguishing between negligible changes and changes that have a real impact on the competitive process. This threshold can be preset and adjusted according to the game type, competitive rules, and sensitivity to the competitive impact. For example, for changes in character health, it might be set that a decrease in health exceeding a certain percentage is considered a significant change.

[0089] Specifically, a sequence of operation instructions can be divided into multiple consecutive or non-consecutive subsequences, each subsequence constituting a candidate operation combination. This grouping can be based on time windows, operation types, operation objects, or pre-defined logical relationships. For example, multiple operation instructions executed consecutively within a short period can be considered a combination to capture the impact of compound operations.

[0090] Cumulative change refers to the total change in game state within a specific third time window, resulting from the combined effect of all action commands within a candidate action combination. This cumulative change reflects the overall effect of a series of action commands, rather than the instantaneous impact of a single command. The third time window should be set to match the occurrence and development cycle of competitive events to ensure that meaningful cumulative effects can be captured.

[0091] This judgment aims to filter out candidate action combinations that genuinely have a sufficient impact on the game state. Only when the cumulative change reaches a preset significance threshold is the action combination considered potentially associated with a significant change in the game state.

[0092] This judgment is used to identify candidate action combinations that, while significantly impacting the game state, have a low degree of correlation with the pre-defined key competitive event template. This indicates that these action combinations may trigger significant changes in the game state in atypical or unexpected ways.

[0093] Therefore, by combining the actual degree of change in the game state and the correlation between the combination of operations and known key events, it is possible to accurately identify those seemingly unrelated operation segments that actually have a significant impact on the competitive process. These segments may represent deviations in operation results caused by network transmission anomalies, or atypical operation patterns of players under abnormal conditions.

[0094] This application's solution involves a detailed analysis of the sequence of operation instructions. First, it captures the instantaneous changes in the game state after each instruction is executed, laying the foundation for subsequent cumulative change calculations. Then, by setting a significance threshold, it effectively distinguishes between changes that have a real impact on the competitive process and those that are insignificant. By grouping operation instructions into candidate operation combinations and calculating their cumulative changes within a specific time window, the combined effect of a series of operations can be captured. Crucially, this solution not only focuses on the significant impact of operation combinations on the game state but also incorporates their basic correlation with a preset key competitive event template. When the cumulative change reaches the significance threshold, but the basic correlation is lower than the preset correlation threshold, this indicates that the operation combination may have triggered a significant change in the game state in an unexpected way, thus being identified as the target instruction fragment. This mechanism enables the system to identify deviations in operation results caused by abnormal network transmission or other atypical factors, even if these operations themselves have low correlation with known key events, but their actual impact on the game state cannot be ignored.

[0095] refer to Figure 2 This application further proposes an IoT-based competitive information interaction security system for implementing an IoT-based competitive information interaction security method. The system includes: The evaluation module is used to obtain current competitive context information and data packet type information, and evaluate the competitive impact weight of the data packet based on the current competitive context information and data packet type information; The identification module is used to acquire network transmission anomaly information of data packets and identify the impact level of network transmission anomalies on the competition based on the network transmission anomaly information and the competition impact weight of data packets. The processing module, when the impact level is set to high impact level, simulates the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission abnormality, and obtains the actual operation result of the operation instruction. The determination module is used to compare the expected operation results with the actual operation results to determine the actual impact of network transmission anomalies on operation instructions. The response module takes tiered response measures to network transmission anomalies based on the actual degree of impact.

[0096] The evaluation module is configured to acquire current competitive context information and data packet type information, and then evaluate the competitive impact weight of the data packet based on the acquired information. Specifically, the evaluation module is responsible for collecting real-time data related to the competitive environment, such as game stage, player status, and key event occurrences, and combining this data with the data packet's own attributes (such as data packet type, size, sender, etc.) to comprehensively determine the importance or degree of impact of the data packet on the competitive outcome in the current competitive context.

[0097] The identification module is configured to acquire network transmission anomaly information of data packets and, based on the acquired network transmission anomaly information and the competitive impact weight of the data packets, identify the impact level of the network transmission anomaly on the competition. Specifically, the identification module receives network transmission anomaly data from network monitoring or other sources, such as latency, packet loss, jitter, etc., and, combined with the competitive impact weight output by the evaluation module, quantifies the potential negative impact of the network transmission anomaly on the competition process, classifying it into different impact levels, such as low, medium, and high impact levels.

[0098] The processing module is configured to simulate the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission anomaly when the impact level is a set high impact level, and to obtain the actual operation result of the operation instruction. Specifically, when it is identified that a network transmission anomaly has a high impact on the competition, the processing module will start the simulation mechanism to predict the game result that the operation instruction should produce under ideal network conditions, and at the same time record the execution result of the operation instruction under the actual network anomaly condition.

[0099] The determination module is configured to compare the expected operation result with the actual operation result to determine the actual impact of network transmission anomalies on the operation command. Specifically, the determination module receives the expected operation result and the actual operation result provided by the processing module, and by comparing the differences between the two, accurately quantifies the actual deviation or damage caused by network transmission anomalies to the execution effect of a specific operation command.

[0100] The response module is configured to take tiered response measures to network transmission anomalies based on the actual degree of impact. Specifically, the response module triggers different preset levels of response strategies based on the actual degree of impact of the output from the determination module. For example, a minor impact may only involve logging, a moderate impact may involve attempting network optimization, and a high impact may trigger an in-game compensation mechanism or force a disconnection.

[0101] This application's IoT-based competitive information interaction security system, through its modular design, achieves comprehensive monitoring, assessment, and response to information interaction security issues in IoT competitive environments. Specifically, the assessment module first performs a forward-looking evaluation of the competitive impact weight of data packets, laying the foundation for subsequent anomaly identification. Subsequently, the identification module combines network transmission anomaly information with this weight to accurately determine the impact level of the anomaly on the competition. When a high-impact anomaly is detected, the processing module quantifies the actual impact of the network anomaly on operational instructions through simulation and real-world comparison. Finally, the determination module feeds back this impact level to the response module, which then takes targeted, tiered response measures for the network transmission anomaly according to a preset strategy. This collaborative mechanism ensures that network anomalies can be detected promptly, accurately assessed, and effectively addressed during competition, thereby minimizing their negative impact on competitive fairness and user experience.

[0102] In some preferred embodiments, suppose in a multiplayer online competitive game, player A is performing a crucial skill activation. When player A's action command data packet is transmitted via the Internet of Things (IoT), the IoT-based competitive information exchange security system activates.

[0103] First, the evaluation module acquires information about the current competitive situation (e.g., player A is in the core area of ​​a team fight, and skill usage may determine the outcome of the battle) and the type of the data packet (e.g., this is a high-priority skill usage command packet). Based on this information, the evaluation module assesses the competitive impact weight of the data packet as "extremely high".

[0104] Next, the identification module detects network transmission anomalies during the transmission of the data packet (e.g., a sudden increase in network latency to 200ms). Combining this with the "extremely high" competitive impact weight provided by the evaluation module, the identification module determines that the network transmission anomaly's impact on the competition is at a "high impact level."

[0105] Because the impact level is high, the processing module is activated. The processing module will simulate the expected operation result of player A's skill release command under the condition of no network transmission anomaly (e.g., the skill is successfully released, dealing damage to the enemy and applying a control effect), and at the same time obtain the actual operation result of the command under the actual network transmission anomaly (e.g., skill release is delayed, resulting in missing the target or weakening the effect).

[0106] The determination module then compares the expected and actual results of the operation. For example, if the expected result is a skill hit dealing 100 damage, but only 50 damage is actually dealt, the determination module will determine that the network transmission anomaly had a "moderate impact" on the operation command (e.g., 50% damage loss).

[0107] Finally, the response module takes tiered response measures to network transmission anomalies based on the "moderate impact" level determined by the determination module's output. For example, the system might trigger a compensation mechanism to provide player A with a temporary buff, or display a notification on the game interface indicating poor network conditions, and record the anomaly for later analysis. In this way, even when network anomalies occur, the fairness of the competition and the player experience can be maintained to the greatest extent possible.

[0108] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A method for secure information exchange in IoT-based competitive sports, characterized in that, The method includes the following steps: Obtain current competitive context information and data packet type information, and evaluate the competitive impact weight of the data packet based on the current competitive context information and data packet type information; Obtain network transmission anomaly information of data packets, and identify the impact level of network transmission anomalies on the competition based on the network transmission anomaly information and the competition impact weight of data packets; When the impact level is set to the high impact level, simulate the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission abnormality, and obtain the actual operation result of the operation instruction; By comparing the expected and actual operational results, the actual impact of network transmission anomalies on operational instructions can be determined. Based on the actual degree of impact, tiered response measures should be taken for network transmission anomalies; The step of comparing the expected operation results with the actual operation results to determine the actual impact of network transmission anomalies on operation instructions includes: By comparing the expected operation results with the actual operation results, the initial impact of network transmission anomalies on operation commands can be obtained; Obtain the player's operation sequence corresponding to the operation command; Based on the player's action sequence, identify the player's tactical intentions and the final strength value of those intentions; To determine whether there is a conflict between the player's tactical intentions and the game state on which the expected operational results are based; If a conflict exists and the final intensity value of the tactical intention reaches the preset intensity threshold, the initial impact level is adjusted based on the player's tactical intention and the final intensity value of the tactical intention to obtain the actual impact of the network transmission anomaly on the operation command. If there is no conflict or the final intensity value of the tactical intent does not reach the preset intensity threshold, the initial impact level will be taken as the actual impact of the network transmission anomaly on the operational instructions.

2. The IoT competitive information interaction security method as described in claim 1, characterized in that, The steps for identifying a player's tactical intentions and their final strength based on their sequence of actions include: Obtain the player's operation sequence and current competitive situation information; Extract characteristic operations related to the preset reference tactical intentions from the player's operation sequence, and obtain the occurrence of characteristic operations; Analyze the player's operation sequence to obtain the coherence of the operation sequence; Based on the current competitive context, adjust the weight of characteristic operations and the matching tolerance for core operational elements defined by the reference tactical intent; In the contestant's operation sequence, the occurrence of core operation elements is matched according to the matching tolerance, and the core operation elements are allowed to vary within a preset threshold range in terms of time sequence or time interval, so as to obtain the matching degree of the core operation elements. Based on the matching degree of core operational elements, the occurrence of characteristic operations, and the coherence of the player's operational sequence, calculate the final intensity value of one or more tactical intentions. Based on the current competitive situation information, the current competitive situation is obtained; When there are multiple candidate tactical intentions, priority is determined based on the candidate strength value of each candidate tactical intention and the degree of fit between the candidate tactical intention and the current competitive situation, and the candidate tactical intention with the highest priority is selected as the player's tactical intention.

3. The IoT competitive information interaction security method as described in claim 2, characterized in that, The steps for adjusting the weights of characteristic operations and the matching tolerance for core operational elements defined by the reference tactical intent, based on the current competitive context information, include: Real-time analysis of the contestant's first operation command flow within a preset first time window to obtain the contestant's operation rhythm, operation coherence and operation accuracy; The deviation of the contestant's operational characteristics is calculated based on the contestant's operational rhythm, operational continuity, and operational precision. Based on the deviation of the player's operational characteristics and combined with the current competitive context information, the weight of the characteristic operations and the matching tolerance of the core operational elements defined for the reference tactical intent are adjusted.

4. The IoT competitive information interaction security method as described in claim 1, characterized in that, The steps for evaluating the competitive impact weight of a data packet include: Obtain the second operation command stream of the player corresponding to the data packet within the preset second time window, and identify the triggering operation of the actual key competitive event from the second operation command stream; Obtain instantaneous environmental change information related to the triggering operations of actual key competitive events in the game world corresponding to the data packet; The competitive impact weight of the data packet is evaluated based on the current competitive context information, data packet type information, actual key competitive events triggering operations, and instantaneous environmental change information.

5. The IoT competitive information interaction security method as described in claim 4, characterized in that, The steps to identify the triggering actions of actual key competitive events include: Analyze the types of operation instructions, the execution sequence of operation instructions, and the attribute changes of the operation objects in the second operation instruction stream; Based on the analysis results and the final correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template, the triggering operation of the actual key competitive event is identified from the second operation instruction stream.

6. The IoT competitive information interaction security method as described in claim 5, characterized in that, The steps for obtaining the final correlation between operation instructions and preset key competitive event templates in the second operation instruction stream include: Based on the analysis results and the definition rules of the preset key competitive event template, the basic correlation between the operation instructions in the second operation instruction stream and the preset key competitive event template is calculated. Obtain the current competitive context information corresponding to the operation instructions in the second operation instruction stream, and correct the basic correlation degree based on the current competitive context information to obtain the final correlation degree between the operation instructions in the second operation instruction stream and the preset key competitive event template.

7. The IoT competitive information interaction security method as described in claim 6, characterized in that, The steps to correct the basic correlation include: Obtain the sequence of operation commands and the corresponding game state changes; Based on the sequence of operation instructions and changes in the game state, identify target instruction fragments in the sequence of operation instructions whose basic correlation is lower than a preset correlation threshold and which trigger changes in the game state. Based on the target instruction fragment, assess the impact of changes in game state on the competitive progress; The basic correlation is adjusted based on the degree of influence and the frequency of occurrence of the target instruction fragment. The current competitive context information includes the degree of influence and the frequency of occurrence of the target instruction fragment.

8. The IoT competitive information interaction security method as described in claim 7, characterized in that, The steps for identifying target instruction fragments in an operation instruction sequence whose basic correlation is lower than a preset correlation threshold and which trigger changes in the game state include: Obtain the instantaneous change in the game state after each operation instruction in the sequence of operation instructions is executed; Set a threshold for the significance of changes in game state; Group the operation instructions in the operation instruction sequence to form candidate operation combinations; Calculate the cumulative changes in the game state caused by candidate operation combinations within a preset third time window; Determine whether the cumulative change has reached the significance threshold; Determine whether the correlation between the candidate operation combination and the basic correlation is lower than a preset correlation threshold; If the cumulative change reaches the significance threshold and the basic correlation is lower than the preset correlation threshold, then the candidate operation combination is identified as the target instruction fragment in the operation instruction sequence whose basic correlation is lower than the preset correlation threshold and which triggers a change in the game state.

9. An IoT-based competitive information interaction security system, applied to the IoT-based competitive information interaction security method described in claim 1, characterized in that, The system includes: The evaluation module is used to obtain current competitive context information and data packet type information, and evaluate the competitive impact weight of the data packet based on the current competitive context information and data packet type information; The identification module is used to acquire network transmission anomaly information of data packets and identify the impact level of network transmission anomalies on the competition based on the network transmission anomaly information and the competition impact weight of data packets. The processing module, when the impact level is set to high impact level, simulates the expected operation result of the operation instruction corresponding to the data packet under the condition of no network transmission abnormality, and obtains the actual operation result of the operation instruction. The determination module is used to compare the expected operation results with the actual operation results to determine the actual impact of network transmission anomalies on operation instructions. The response module takes tiered response measures for network transmission anomalies based on the actual degree of impact. The determining module is also used for: By comparing the expected operation results with the actual operation results, the initial impact of network transmission anomalies on operation commands can be obtained; Obtain the player's operation sequence corresponding to the operation command; Based on the player's action sequence, identify the player's tactical intentions and the final strength value of those intentions; To determine whether there is a conflict between the player's tactical intentions and the game state on which the expected operational results are based; If a conflict exists and the final intensity value of the tactical intention reaches the preset intensity threshold, the initial impact level is adjusted based on the player's tactical intention and the final intensity value of the tactical intention to obtain the actual impact of the network transmission anomaly on the operation command. If there is no conflict or the final intensity value of the tactical intent does not reach the preset intensity threshold, the initial impact level will be taken as the actual impact of the network transmission anomaly on the operational instructions.

Images