Abstract:
Methods and systems for dependency tracking include identifying a hot process that generates bursts of events with interleaved dependencies. Events related to the hot process are aggregated according to a process-centric dependency approximation that ignores dependencies between the events related to the hot process. Causality in a reduced event stream that comprises the aggregated events is tracked.
Abstract:
Systems and a method are provided. A system includes a Temporal Behavior Query Language (TBQL) server having a processor and a memory operably coupled to the processor. The TBQL server configured to construct a TBQL query using a grammar inference technique based on syntactic sugar to expedite query construction. The TBQL server is further configured to execute the TBQL, query to generate TBQL query results.
Abstract:
A method and system for constructing behavior queries in temporal graphs using discriminative sub-trace mining. The method (100) includes generating system data logs to provide temporal graphs (102), wherein the temporal graphs include a first temporal graph corresponding to a target behavior and a second temporal graph corresponding to a set of background behaviors (102), generating temporal graph patterns for each of the first and second temporal graphs to determine whether a pattern exists between a first temporal graph pattern and a second temporal graph pattern, wherein the pattern between the temporal graph patterns is a non-repetitive graph pattern (104), pruning the pattern between the first and second temporal graph patterns to provide a discriminative temporal graph (106), and generating behavior queries based on the discriminative temporal graph (110).
Abstract:
Methods for querying a database and database systems include optimizing (304) a database query for parallel execution using spatial and temporal information relating to elements in the database, the optimized database query being split into sub-queries with sub-queries being divided spatially according to host and temporally according to time window. The sub-queries are executed (306) in parallel. The results of the database query are outputted (310) progressively.
Abstract:
A method and system for constructing behavior queries in temporal graphs using discriminative sub-trace mining. The method includes generating system data logs to provide temporal graphs, wherein the temporal graphs include a first temporal graph corresponding to a target behavior and a second temporal graph corresponding to a set of background behaviors, generating temporal graph patterns for each of the first and second temporal graphs to determine whether a pattern exists between a first temporal graph pattern and a second temporal graph pattern, wherein the pattern between the temporal graph patterns is a non-repetitive graph pattern, pruning the pattern between the first and second temporal graph patterns to provide a discriminative temporal graph, and generating behavior queries based on the discriminative temporal graph.