Abstract: A processor may receive a smart contract. The processor may generate an entity policy. The entity policy may provide one or more world-state rules associated with a particular entity. The processor may update, responsive to receiving the smart contract, a world-state database of the particular entity. The one or more world-state rules may affect the world-state database of the particular entity differently than the world-state database of a second entity.

Abstract: A system and method for detecting and blocking bots are presented. The method includes receiving unlabeled data regarding a visitor of a web source, grouping the received unlabeled data with similar characteristics into a group of data, detecting, based on the group of data, at least one anomaly, and determining, based on the at least one detected anomaly, several visitors to be blacklisted.

Abstract: A system of method of detecting bots are presented. The method includes receiving access patterns of a visitor accessing a protected web property, encoding each of the access patterns into a fixed length feature vector, determining an offline-trained model based on past data, generating an anomaly score based on the fixed length feature vector and an offline-trained model, and determining the visitor to be a bot, when the generated anomaly score associated with the visitor reaches a predetermined threshold.

Abstract: A system and method for detecting bots. The method includes receiving a request to access a server, the request is being received from a client device, and responsive to the request, causing the client device to download a script code file to the client device. The script code file, when executed, collects a profile, and the profile includes a plurality of parameters. The method also includes receiving the created profile, generating a score based on the plurality of parameters to identify a bot, and initiating a mitigation action based on the identified bot.

Abstract: A processor may receive a smart contract. The processor may generate an entity policy. The entity policy may provide one or more world-state rules associated with a particular entity. The processor may update, responsive to receiving the smart contract, a world-state database of the particular entity. The one or more world-state rules may affect the world-state database of the particular entity differently than the world-state database of a second entity.

Abstract: An example operation includes one or more of identifying, by an archiving server node, a unique archival policy for each of a plurality of blockchain nodes, executing, by the archiving server node, a consensus mechanism to determine at least one block from a plurality of blocks of the plurality of the blockchain nodes to be archived, and running the unique archival policy to archive the at least one block from the plurality of the blocks.

Abstract: A system and method for detecting bots. The method includes receiving a request to access a server, the request is being received from a client device, and responsive to the request, causing the client device to download a script code file to the client device. The script code file, when executed, collects a profile, and the profile includes a plurality of parameters. The method also includes receiving the created profile, generating a score based on the plurality of parameters to identify a bot, and initiating a mitigation action based on the identified bot.

Abstract: A system and method for detecting and blocking bots are presented. The method includes receiving unlabeled data regarding a visitor of a web source, grouping the received unlabeled data with similar characteristics into a group of data, detecting, based on the group of data, at least one anomaly, and determining, based on the at least one detected anomaly, several visitors to be blacklisted.

Abstract: A system of method of detecting bots are presented. The method includes receiving access patterns of a visitor accessing a protected web property, encoding each of the access patterns into a fixed length feature vector, determining an offline-trained model based on past data, generating an anomaly score based on the fixed length feature vector and an offline-trained model, and determining the visitor to be a bot, when the generated anomaly score associated with the visitor reaches a predetermined threshold.