Abstract: Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.

Abstract: Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.

Abstract: Systems and methods for configuring and evaluating policies that direct processing of one or more data streams are described. A configuration interface is described for allowing users to specify object oriented policies. These object oriented policies may allow any data structures to be applied with respect to a payload of a received packet stream, including any portions of HTTP traffic. A configuration interface may also allow the user to control the order in which policies and policy groups are executed, in addition to specifying actions to be taken if one or more policies are undefined. Systems and methods for processing the policies may allow efficient processing of object-oriented policies by applying potentially complex data structures to unstructured data streams. A device may also interpret and process a number of flow control commands and policy group invocation statements to determine an order of execution among a number of policies and policy groups.

Abstract: A device may store information associated with a group of items in a database. The information associated with a particular item may include a group of versions of a particular attribute. A particular version of the particular attribute may include a value associated with the particular attribute and a timestamp. The device may receive a query that specifies a time; determine that the query is associated with the particular item; and determine, based on the specified time, which version of the particular attribute is associated with the query. The device may determine which version of the particular attribute is associated with the query by identifying, based on the timestamps associated with the versions of the particular attribute, a version of the particular attribute that is a newest version, of the versions of the particular attribute that are associated with timestamps that are before or concurrent with the specified time.

Abstract: A log file processing system includes a data storage device and a processing circuit configured to retrieve log file data from the data storage device and to create a bundle including a plurality of data chunks using the log file data. The processing circuit is configured to assign the bundle to a first processing pipeline of a set of multiple processing pipelines in response to a request from the first processing pipeline. The processing circuit is configured to store a global available timestamp for the bundle upon assigning the bundle to the first processing pipeline. The global timestamp is a time threshold before which the bundle is ineligible to be assigned to any of the multiple processing pipelines.

Abstract: A method of a device for filtering messages routing across a network includes extracting, by a filter configured on the device, a plurality of message components from messages received via a network. The plurality of message components is identified as having at least a field name in common, including a first field name. A learning engine configured on the device creates a list of data types for values of the first field name. The list includes one or more data types of a value of the first field name identified for each of the plurality of message components. The learning engine determines a most restrictive data type from the list of data types for the values of the first field name of the plurality of message components.

Abstract: Systems and methods for configuring and evaluating policies that direct processing of one or more data streams are described. A configuration interface is described for allowing users to specify object oriented policies. These object oriented policies may allow any data structures to be applied with respect to a payload of a received packet stream, including any portions of HTTP traffic. A configuration interface may also allow the user to control the order in which policies and policy groups are executed, in addition to specifying actions to be taken if one or more policies are undefined. Systems and methods for processing the policies may allow efficient processing of object-oriented policies by applying potentially complex data structures to unstructured data streams. A device may also interpret and process a number of flow control commands and policy group invocation statements to determine an order of execution among a number of policies and policy groups.

Abstract: Systems and methods for configuring and evaluating policies that direct processing of one or more data streams are described. A configuration interface is described for allowing users to specify object oriented policies. These object oriented policies may allow any data structures to be applied with respect to a payload of a received packet stream, including any portions of HTTP traffic. A configuration interface may also allow the user to control the order in which policies and policy groups are executed, in addition to specifying actions to be taken if one or more policies are undefined. Systems and methods for processing the policies may allow efficient processing of object-oriented policies by applying potentially complex data structures to unstructured data streams. A device may also interpret and process a number of flow control commands and policy group invocation statements to determine an order of execution among a number of policies and policy groups.

Abstract: A method of a device for filtering messages routing across a network includes extracting, by a filter configured on the device, a plurality of message components from messages received via a network. The plurality of message components is identified as having at least a field name in common, including a first field name. A learning engine configured on the device creates a list of data types for values of the first field name. The list includes one or more data types of a value of the first field name identified for each of the plurality of message components. The learning engine determines a most restrictive data type from the list of data types for the values of the first field name of the plurality of message components.

Abstract: A method of a device for filtering messages routing across a network includes extracting, by a filter configured on the device, a plurality of message components from messages received via a network. The plurality of message components is identified as having at least a field name in common, including a first field name. A learning engine configured on the device creates a list of data types for values of the first field name. The list includes one or more data types of a value of the first field name identified for each of the plurality of message components. The learning engine determines a most restrictive data type from the list of data types for the values of the first field name of the plurality of message components.

Abstract: A classification engine is capable of receiving a plurality of protocol data units (PDUs) and performing a tree-based classification on the PDUs. The classification engine includes: input means for receiving the PDUs; parsing means capable of parsing the PDUs to generate an abstracted protocol structure for at least one of the PDUs; classifier capable of performing the tree-based classification, said classifier being capable of enforcing policy using the abstracted protocol structure; and output means for transmitting the PDUs.

Abstract: A method of a device for filtering messages routing across a network includes extracting, by a filter configured on the device, a plurality of message components from messages received via a network. The plurality of message components is identified as having at least a field name in common, including a first field name. A learning engine configured on the device creates a list of data types for values of the first field name. The list includes one or more data types of a value of the first field name identified for each of the plurality of message components. The learning engine determines a most restrictive data type from the list of data types for the values of the first field name of the plurality of message components.

Abstract: A security gateway receives messages and extracts components thereof, typically in the form of field name-value pairs. The security gateway determines a data type of the values for individual field names to infer the most restrictive data type of the values for that field. The security gateway may then generates rules, which would block messages that do not have values that match the most restrictive data type. Since the most restrictive data type defines a data type of values for the field as narrowly as possible, the generated rules will make it more difficult for an intruder to guess a valid data type of a value. Since messages that have values that do not match the most restrictive data type are likely to represent malicious attacks, the more narrowly the data type of values is defined, the greater the number of illegitimate messages that will be blocked.

Abstract: Systems and methods for configuring and evaluating policies that direct processing of one or more data streams are described. A configuration interface is described for allowing users to specify object oriented policies. These object oriented policies may allow any data structures to be applied with respect to a payload of a received packet stream, including any portions of HTTP traffic. A configuration interface may also allow the user to control the order in which policies and policy groups are executed, in addition to specifying actions to be taken if one or more policies are undefined. Systems and methods for processing the policies may allow efficient processing of object-oriented policies by applying potentially complex data structures to unstructured data streams. A device may also interpret and process a number of flow control commands and policy group invocation statements to determine an order of execution among a number of policies and policy groups.

Abstract: A classification engine is capable of receiving a plurality of protocol data units (PDUs) and performing a tree-based classification on the PDUs. The classification engine includes: input means for receiving the PDUs; parsing means capable of parsing the PDUs to generate an abstracted protocol structure for at least one of the PDUs; classifier capable of performing the tree-based classification, said classifier being capable of enforcing policy using the abstracted protocol structure; and output means for transmitting the PDUs.