Abstract: A packet classification system, apparatus, and corresponding apparatus are provided for enabling packet classification. A processor of a security appliance coupled to a network uses a classifier table having a plurality of rules, the plurality of rules having at least one field, to build a decision tree structure for packet classification. Duplication in the decision tree may be identified, producing a wider, shallower decision tree that may result in shorter search times with reduced memory requirements for storing the decision tree. A number of operations needed to identify duplication in the decision tree may be reduced, thereby increasing speed and efficiency of a compiler building the decision tree.

Abstract: In a processor of a security appliance, an input of a sequence of characters is walked through a finite automata graph generated for at least one given pattern. At a marked node of the finite automata graph, if a specific type of the at least one given pattern is matched at the marked node, the input sequence of characters is processed through a reverse non-deterministic finite automata (rNFA) graph generated for the specific type of the at least one given pattern by walking the input sequence of characters backwards through the rNFA beginning from an offset of the input sequence of characters associated with the marked node. Generating the rNFA for a given pattern includes inserting processing nodes for processing an input sequence of patterns to determine a match for the given pattern. In addition, the rNFA is generated from the given type of pattern.

Abstract: A packet classification system, methods, and corresponding apparatus are provided for enabling packet classification. A processor of a security appliance coupled to a network uses a classifier table having a plurality of rules, the plurality of rules having at least one field, to build a decision tree structure including a plurality of nodes, the plurality of nodes including a subset of the plurality of rules. The methods may produce wider, shallower trees that result in shorter search times and reduced memory requirements for storing the trees.

Abstract: In one embodiment, a method includes encoding a key matching rule having at least one dimension by storing in a memory (i) a header of the key matching rule that has at least one header field, and (ii) at least one rule value field of the key matching rule corresponding to one of the dimensions.

Abstract: A system, apparatus, and method are provided for adding, deleting, and modifying rules in one update from the perspective of an active search process for packet classification. While a search processor searches for one or more rules that match keys generated from received packets, there is a need to add, delete, or modify rules. By adding, deleting, and modifying rules in one update from the perspective of an active search process for packet classification, performance and functionality of the active search process may be maintained, thereby preventing packet loss and preserving throughput.

Abstract: A method and apparatus relate to recognizing anchored patterns from an input stream. Patterns from a plurality of given patterns are marked as anchored patterns. An anchored state tree for the anchored patterns of the plurality of given patterns is built, including nodes representing a state of the anchored state tree. For each node of the anchored state tree, a failure value equivalent to a node representing a state in an unanchored state tree representing unanchored patterns of the plurality of given patterns is determined.

Abstract: A method and corresponding apparatus relate to converting a nondeterministic finite automata (NFA) graph for a given set of patterns to a deterministic finite automata (DFA) graph having a number of states. Each of the DFA states is mapped to one or more states of the NFA graph. A hash value of the one or more states of the NFA graph mapped to each DFA state is computed. A DFA states table correlates each of the number of DFA states to the hash value of the one or more states of the NFA graph for the given pattern.

Abstract: A method and corresponding apparatus are provided implementing a stage one of run time processing using Deterministic Finite Automata (DFA) and implementing a stage two of run time processing using Non-Deterministic Finite Automata (NFA) to find the existence of a pattern in a payload, such as the payload portion of an Internet Protocol (IP) datagram, or an input stream.

Abstract: Methods and apparatuses are disclosed for caching portions of a Deterministic Finite Automata (DFA) graph during a compilation stage prior to a run-time stage that identifies attack traffic based on the graph. Cacheable components are identified based on a traffic profile, a dictionary of keywords, and/or a geometrical configuration of the graph. Techniques are disclosed for performing various types of caching alone or in combination with other types. Caching based on a dictionary or profile exploit a tendency of graph traversals performed during non-attack scenarios to remain near root nodes that correspond to the start of patterns designating blacklist traffic. By caching nodes that are near root nodes and that are visited frequently during peacetime (non-attack) scenarios, significant cache hits may be achieved during run-time execution. Caching graph components while compiling patterns using presently disclosed techniques avoids the need for expensive hardware to learn what and when to cache.