31 results about "Cheating" patented technology

The embodiment of the invention provides a cheating detection and model training method and device for a shooting game and a storage medium. After a server obtains video data of a shooting game, aiming paths of virtual shooting operation of a user in the shooting game are detected based on the video data, the aiming paths are classified according to the neural network model, and a cheating detection result of the virtual shooting operation is obtained. According to the implementation mode, deployment on the server side is easy, an anti-cheating program does not need to be deployed on a game terminal, and therefore the cheating detection strategy is not likely to be bypassed by a cheating user in a targeted mode. Meanwhile, depending on the strong learning and computing capabilities of the neural network model, whether the virtual shooting operation is a cheating behavior or not can be accurately recognized based on the aiming paths, and the accuracy and reliability of the cheating detection method are greatly improved.

The invention discloses a safety monitoring cheating prevention calculation method and system based on weighing data and relates to the field of weighing behavior monitoring. The method comprises thefollowing steps of A, returning to zero of data; B, continuous increase, stabilization and micro floating of data in short time; C, judgment whether or not floating exceeds a range; D, the micro floating process; E, judgement whether or not data up and down floats 20-100 kg; F, continuous stabilization of data; G, increase, decrease, continuous stabilization and returning to zero of data. According to the safety monitoring cheating prevention calculation method and system, each frame of weighing data is recorded in detail, the data flow is effectively processed, recorded and stored into a database, identification is uniquely identified through a number plate, whether or not a data floating rule is in a normal range in the whole weighing process is determined, various cheating behaviors canbe quickly found, the enterprise management intensity is improved, the management cost is reduced, and the enterprise management risk is reduced.

The invention discloses a cheating behavior detection and early warning method and system, and the method comprises the steps: obtaining a monitoring start instruction, and extracting the picture information in monitoring video information according to the monitoring start instruction; combining the picture information with a preset convolutional neural network to obtain a plurality of priori boxes as pre-selected boxes; and matching the pre-selected boxes in combination with a preset cheating behavior atlas and a loss function, and sending early warning information when matching succeeds. Byautomatically monitoring the abnormal behaviors of the examinees in the examination room in real time, once it is monitored that the abnormal behaviors of the examinees belong to cheating behaviors, early warning information is sent out immediately in real time, accurate recognition of the cheating behaviors of the examinees is achieved, a large amount of manpower is saved, and meanwhile the workefficiency of monitoring the cheating behaviors of the examinees is greatly improved. The cheating behavior detection and early warning method and system can be widely applied to the technical field of image processing.

The invention relates to a method and device for detecting cheating behaviors, electronic equipment and a storage medium. In one method, first behavior data and second behavior data of a first accountand a second account are acquired, respectively, the first behavior data and the second behavior data representing behavior data for providing services to a first set and a second set of service objects by the first account and the second account, respectively. The behavior similarity is determined between the first account and the second account based on the first behavior data and the second behavior data. Cheating behaviors of the first account and the second account are detected based on the behavior similarity and a cheating detection model formed through training. The cheating detectionmodel describe an association relationship between the behavior similarity of the plurality of accounts for providing services to respective service object sets and the cheating behaviors of the plurality of accounts. Furthermore, the invention provides a corresponding device, electronic equipment and a storage medium. In this way, whether cheating behaviors exist in all accounts or not can be detected based on the behavior data of all the accounts.

The present application relates to a cheating determination method, device, storage medium and computer equipment, the method comprising: acquiring a video frame formed during the game; extracting the pixel value of the target color from the video frame to obtain the A frame image composed of pixel values; according to the frame image, it is determined that the video frame contains a virtual object displayed due to a perspective obstacle; when it is detected that the sight for positioning the virtual object is turned on, the displayed Among the virtual objects, it is determined that there is at least one virtual object in the field of view area corresponding to the aimer; when it is detected that the projection operation is performed, it is determined that there is cheating during the game. The scheme provided by this application can improve the efficiency of judging cheating behavior.

The present invention provides a method, device, electronic device, and storage medium for training a cheat recognition model. The method includes: determining the training samples of the cheat recognition model based on the behavior information of the target user, and determining the characteristics of the cheat portrait in the cheat recognition environment. ; According to the behavior information of the target user, determine the corresponding behavior sequence information; determine the model parameters that are compatible with the plug-in identification model, so that the behavior of the target user can be monitored in real time through the plug-in identification model, and According to the risk prediction results, the matching event execution strategy is executed, which makes the generalization ability and data processing ability of the cheat recognition model stronger, adapts to different cheat recognition environments, and reduces the robustness of the cheat recognition model. At the same time, there is no need to obtain a large number of labeled samples to train a model dedicated to identifying cheating behaviors, so the cost of identifying cheating behaviors can be effectively reduced.

The invention discloses an intelligent billiards referee anti-cheating method and system, comprising: acquiring the batter's batting parameters, and calculating the batting energy value according to the batting parameters; after the batter finishes hitting the ball, acquiring Continuous frame images of the table and billiards on the table; analyzing the continuous frame images to obtain the movement trajectory of each billiard ball; obtaining the corresponding energy loss value of each billiard ball according to the movement trajectory of each billiard ball; calculating the energy consumption of all billiard balls value, judging whether the sum of the energy loss values ​​is greater than the energy value of hitting the ball, and if it is determined that the sum of the energy loss values ​​is greater than the energy value of hitting the ball, it indicates that there is cheating. According to the relationship between the energy value of hitting the ball and the energy loss value of the billiard ball after hitting the ball, it is accurately judged whether the player is cheating.

The invention discloses a method, an apparatus and a system for preventing cheat during step count. The method comprises the following steps: acquiring amount of steps collected by accumulation of a step counting sensor in an intelligent wearable device; counting collected step number at every preset time interval, calculating difference values between adjacent two counted step numbers, and obtaining a step increment in each preset time interval; determining whether step counting is suspected to be cheated according to the step increment in each preset time interval, if step counting is suspected to be cheated, acquiring heart rate data collected by a heart rate sensor in the intelligent wearable device, and confirming whether the step counting is really cheated according to heart rate data. The method fills the blank for preventing users cheating in the aspect of step count in the prior art, provides a real sports rank; prevents deviation appeared in evaluation of user health state due to step count data errors; and prevents improper incomes obtained by cheating in step count matches which causes losing match meanings.

A cheating detection method, device and terminal including: determining the data to be detected, and select the observation index to be observed as well as a variety of dimensions, each dimension has to be observed at least one value; According to the plurality of dimensions to be observed, the values of each dimension to be observed are combined to form a plurality of observation dimension combinations; According to the data to be tested, the index value of the observed index is calculated for each observation dimension combination; The candidate anomaly combination in the observation dimension combination is determined according to the index value; Based on the historical data, the candidate anomaly combination is analyzed to determine the abnormal combination in the candidate anomaly combination.The abnormal combination is used to determine the flow of cheating. The technical scheme of the invention can detect the flow of cheating.

The invention relates to the field of network education technology, and particularly to an intelligent cheating preventing method and a device thereof, wherein the method comprises the steps of acquiring position distribution of intelligent devices by a server, and further determining n intelligent devices with a cheating risk around a random intelligent device A; distributing examination questions to each intelligent device by a server according to different sequences so that each intelligent device successively displays the problems according to a distributed sequence; and dynamically adjusting the displaying sequence of the questions on each intelligent device by the server based on the question answering progress of each examinee, so that the current displaying questions on a random intelligent device in the n intelligent devices and the intelligent device A are different. According to the method and the device, not only can the examination questions be distributed to the intelligent devices according to different sequences in advance, but also the question sequence is dynamically adjusted according to the question answering progress in an examination process so that displayingof the same question on the screens of adjacent examinees at the same time is prevented, thereby reducing cheating behaviors.

The invention discloses a fNIRS data processing method based on deceptive behaviors in different situations. The fNIRS signals of subjects' spontaneous and controlled deceptive behaviors are collected for band-pass filtering, and the HbO data in the filtered fNIRS signals are segmented according to trials. Calculate the Welch power spectrum after averaging, then calculate the power of each channel and normalize the power, then perform statistical detection on the standardized power, and use the detection results to identify the difference in neural activity between deception and honesty under different conditions. The present invention proposes a method for detecting differences in brain activity between deceitful and honest brain regions using the normalized power of fNIRS signals. The normalized power generated by this model is used to quantify the energy of brain activity, which can be used as a scale for fNIRS to detect deceptive behavior neural activity. The proposed method for processing fNIRS data provides us with a new tool for identifying spoofed brain activity changes using fNIRS.

The application relates to a running anti-cheating processing method, a readable storage medium and a terminal processor, and belongs to the technical field of running anti-cheating. The present application provides a running anti-cheating processing method, the method is applied to a terminal processor, the terminal processor has a preset short receiving distance, and is used to set it near the end point of the preset running route, the method includes: receiving a message sent by a wearable device The identity information of the intermediate processors collected by the wearable device and arranged in the order of collection, wherein at least one intermediate processor is set along the preset running route, and each intermediate processor is used to launch within the preset short launch distance The identity information that forms a unique correspondence with it; according to the received identity information of the intermediate processor arranged in the order of collection, it is judged whether the athlete wearing the wearable device has cheated by taking shortcuts while running. Through the application, the reliability of monitoring cheating behaviors by taking shortcuts during a running competition can be improved.

The invention discloses a reading cheating behavior identification method, computing equipment and computer storage medium. Wherein, the method includes: for any sampling unit, acquiring the attribute information of multiple page turning behaviors contained in the sampling unit; according to the attribute information of the multiple page turning behaviors contained in the sampling unit, calculating the corresponding page turning behavior of the sampling unit Behavior difference degree; if the difference degree of page-turning behavior corresponding to the sampling unit is less than a preset threshold, it is determined that the reading behavior corresponding to the sampling unit is a cheating behavior. This scheme can accurately identify reading cheating based on page-turning behavior, thus providing a basis for the prevention and control of reading cheating. Moreover, the implementation process of this scheme is simple and easy, the identification efficiency is high, and it is suitable for large-scale application and implementation.

The invention discloses a mobile attendance anti-cheating big data detection method based on a Bayesian model, which is used to solve the defect of attendance cheating in the prior art. It includes the following steps: building a cheating proxy model; applying the cheating proxy model; wherein, building a cheating proxy model includes four steps: establishing a sample library, model training, model application, and model optimization. The present invention builds a big data platform based on hadoop+spark, uses the Bayesian model for data modeling and training, and constructs attendance anti-cheating samples and models, thereby performing real-time detection of user attendance check-in data; the present invention can more accurately identify cheating Personnel and agent punch card data provide effective basis for daily attendance attendance and management, and better prevent and eliminate cheating.

The invention discloses an online examination system anti-cheating method based on pupil tracking, and belongs to the field of image processing. The invention provides a pupil tracking invigilation method, which aims at solving the problem that online invigilation is not in place by an existing examination anti-cheating method in an online system, and comprises the following steps of: 1, acquiring pupil positions; 2, calibrating a screen range; 3, constructing a vector relation between a screen range and a binocular focus position range; and 4, tracking pupils and judging whether cheating behaviors exist or not. According to the method, whether cheating behaviors exist or not is judged by tracking the pupils and utilizing the image frame difference information, waste of human resources is reduced, and meanwhile the method is more accurate.

The present application provides a game behavior recognition method, device, device, and medium, the method comprising: after receiving a game match request for a game match, obtaining game match records of all participants in the game match data, the game game data includes the basic data of all the participants and the operation sequences corresponding to the multi-round game operations of all the participants; based on the game game data, use the behavior recognition model to identify the game Whether the game behavior corresponding to the game request is an abnormal game behavior. The features extracted by this application contain more details than the existing technology, can replace the existing design of artificial statistical features, have high recognition efficiency for abnormal game behaviors, and solve the problem of illegal trading of small accounts, illegal trading of game coins, etc. in the game business. A variety of malicious behavior issues such as double reed actor cheating.

The embodiment of the invention discloses an examination anti-cheating method and device, computer equipment and a storage medium. The method comprises the steps that when an ActiveX control monitorsthat a current terminal enters an examination stage, an examination monitoring function is started; extracting a corresponding number of test questions from the test question set of each test questionmodule based on a preset automatic test paper composition method to generate and output test paper containing the test questions of each test question module, the preset automatic test paper composition method performing test question extraction based on a knapsack principle; and automatically stopping the examination when the ActiveX control detects that the current terminal has illegal operation in the examination stage. The problem that an existing online examination system neglects to prevent cheating behaviors in the examination process is solved, and the safety and fairness of online examination are improved.

The invention provides a method and device for identifying machine assisted cheating. The method includes the following steps that: a time interval sequence is generated according to the operation time of an assessed device or account; the time interval sequence is discretized, so that a discrete time interval sequence can be formed; the entropy rate of the discrete time interval sequence is calculated; and when the entropy rate is smaller than a preset threshold value, it is identified that the assessed device or account adopts machine assisted cheating in operation. According to the method and device of the invention, the entropy rate of the discrete time interval sequence is calculated, so that rhythmic operation and arrhythmic operation can be accurately distinguished, and therefore, the machine assisted cheating can be accurately identified.