Abstract: Implementations described herein relate to methods, systems, and computer-readable media to automatically detect prohibited content. For example, a method can include receiving data associated with a game hosted on a gaming platform, the data indicative of at least one developer, at least one user, and game content, automatically assigning a classification to the game with a machine learning model, the classification based on the data indicative of the at least one developer, at least one user, and game content, determining whether the classification of the game meets a safety threshold, and based on determining that the classification of the game does not meet the safety threshold, identifying the game as having prohibited content.

Abstract: The subject matter of this specification can be implemented in, among other things, a method that includes storing, in a collaboration platform, a first geographic location and a first time of a first authentication request for an account at the collaboration platform responsive to successful authentication of the first authentication request. The method includes receiving a second authentication request for the account at the collaboration platform. The method includes identifying a second geographic location and a second time of the second authentication request. The method includes providing access to the account responsive to a determination that a difference in time between the first time and the second time is large enough that a user of the account is able to travel a difference in distance between the first geographic location and the second geographic location within the difference in time.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to automatically detect prohibited content. For example, a method can include receiving data associated with a game hosted on a gaming platform, the data indicative of at least one developer, at least one user, and game content, automatically assigning a classification to the game with a machine learning model, the classification based on the data indicative of the at least one developer, at least one user, and game content, determining whether the classification of the game meets a safety threshold, and based on determining that the classification of the game does not meet the safety threshold, identifying the game as having prohibited content.

Abstract: Some implementations relate detection of malicious games. In some implementations, a computer-implemented method includes obtaining a list of games that includes a plurality of games, analyzing the plurality of games to identify at least one likely malicious game, and creating a ticket.

Abstract: A method and system is disclosed for training a machine learning model by generating first training input that includes a first number of reports at a first point in time. The reports are submitted by the users of the gaming platform and identify incidents where content of the gaming platform violates a policy of use associated with the gaming platform. The method and system generates second training input including a number of resources active at the first point in time. The method and system generates first target output identifies a number of resources sufficient to evaluate the target percentage of the first number of reports. The method and system provide the training data to train the machine learning model on (i) a set of training inputs comprising the first training input and the second training input, and (ii) a set of target outputs comprising the first target output.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to automatically detect prohibited content. For example, a method can include receiving data associated with a game hosted on a gaming platform, the data indicative of at least one developer, at least one user, and game content, automatically assigning a classification to the game with a machine learning model, the classification based on the data indicative of the at least one developer, at least one user, and game content, determining whether the classification of the game meets a safety threshold, and based on determining that the classification of the game does not meet the safety threshold, identifying the game as having prohibited content.

Abstract: Some implementations relate detection of malicious games. In some implementations, a computer-implemented method includes obtaining a list of games that includes a plurality of games, analyzing the plurality of games to identify at least one likely malicious game, and creating a ticket.

Abstract: Some implementations relate detection of malicious games. In some implementations, a computer-implemented method includes obtaining a list of games that includes a plurality of games, analyzing the plurality of games to identify at least one likely malicious game, and creating a ticket.

Abstract: The subject matter of this specification can be implemented in, among other things, a method that includes storing, in a collaboration platform, a first geographic location and a first time of a first authentication request for an account at the collaboration platform responsive to successful authentication of the first authentication request. The method includes receiving a second authentication request for the account at the collaboration platform. The method includes identifying a second geographic location and a second time of the second authentication request. The method includes providing access to the account responsive to a determination that a difference in time between the first time and the second time is large enough that a user of the account is able to travel a difference in distance between the first geographic location and the second geographic location within the difference in time.

Abstract: Some implementations relate detection of malicious games. In some implementations, a computer-implemented method includes obtaining a list of games that includes a plurality of games, analyzing the plurality of games to identify at least one likely malicious game, and creating a ticket.

Abstract: The subject matter of this specification can be implemented in, among other things, a method that includes storing, in a collaboration platform, a first geographic location and a first time of a first authentication request for an account at the collaboration platform responsive to successful authentication of the first authentication request. The method includes receiving a second authentication request for the account at the collaboration platform. The method includes identifying a second geographic location and a second time of the second authentication request. The method includes providing access to the account responsive to a determination that a difference in time between the first time and the second time is large enough that a user of the account is able to travel a difference in distance between the first geographic location and the second geographic location within the difference in time.

Abstract: The subject matter of this specification can be implemented in, among other things, a method that includes storing, in a collaboration platform, a first geographic location and a first time of a first authentication request for an account at the collaboration platform responsive to successful authentication of the first authentication request. The method includes receiving a second authentication request for the account at the collaboration platform. The method includes identifying a second geographic location and a second time of the second authentication request. The method includes providing access to the account responsive to a determination that a difference in time between the first time and the second time is large enough that a user of the account is able to travel a difference in distance between the first geographic location and the second geographic location within the difference in time.

Abstract: A method and system is disclosed for training a machine learning model by generating first training input that includes a first number of reports at a first point in time. The reports are submitted by the users of the gaming platform and identify incidents where content of the gaming platform violates a policy of use associated with the gaming platform. The method and system generates second training input including a number of resources active at the first point in time. The method and system generates first target output identifies a number of resources sufficient to evaluate the target percentage of the first number of reports. The method and system provide the training data to train the machine learning model on (i) a set of training inputs comprising the first training input and the second training input, and (ii) a set of target outputs comprising the first target output.

Abstract: A method and system is disclosed performs transactions of a virtual game item that transfer the virtual game item between user accounts of a gaming platform. The method and system generate entries in a ledger to record the transactions of the virtual game item. The entries are linked to a preceding entry using one or more hash values. The method and system receive a claim from a first user account of the user accounts to dispute a first transaction of the transactions. Responsive to the claim, the method and system perform an account restore operation based on the ledger that retrieves the virtual game item from another user account identified as a last entry in the ledger and restores the virtual game item to the first user account.