Abstract:
An apparatus and techniques for constructing and utilizing a “dynamic dictionary” that is not a compiled dictionary, and therefore does not need to be recompiled in order to be updated. The dynamic dictionary includes respective data structures that represent (i) a management automaton that includes a plurality of management nodes, and (ii) a runtime automaton that is derived from the management automaton and includes a plurality of runtime nodes. The runtime automaton may be used to search input data, such as communication traffic over a network, for keywords of interest, while the management automaton manages the addition of keywords to the dynamic dictionary. Typically, at least two (e.g., exactly two) such dynamic dictionaries are used in combination with a static dictionary.
Abstract:
A rule engine configured with at least one hash table which summarizes the rules managed by the engine. The rule engine receives rules and automatically adjusts the hash table in order to relate to added rules and/or in order to remove cancelled rules. The adjustment may be performed while the rule engine is filtering packets, without stopping. The rules may be grouped into a plurality of rule types and for each rule type the rule engine performs one or more accesses to at least one hash table to determine whether any of the rules of that type match the packet. In some embodiments, the rule engine may automatically select the rule types responsive to a set of rules provided to the rule engine and adapt its operation to the specific rules it is currently handling, while not spending resources on checking rule types not currently used.
Abstract:
Methods and systems for keyword spotting, i.e., for identifying textual phrases of interest in input data. The input data may be communication packets exchanged in a communication network. A keyword spotting system holds a dictionary (or dictionaries) of textual phrases for searching input data. The input data and the patterns are assigned to multiple different pattern matching algorithms. For example, a share of the traffic is handled by one algorithm and smaller traffic shares may be handled by the others. The system monitors the algorithms performance as they process the data to search for a match. The ratio of traffic splitting among the algorithms is dynamically reassigned or adjusted to maximize the overall performance.