The invention relates to a method and a system for space-efficient multi-pattern matching. Firstly, a novel data structure HashTrie for storing pattern string is proposed, in which an original pattern string matrix is stored in the form of one-dimensional table by using a bit vector table, thus avoiding the problem of state transition matrix of conventional method memory automations; resolving the special bit vector table by using the method of recursive Hash function so as to save memory space; in the process of calculating the Hash function, converting the Hash function into a simple and efficient bit operation by using bit operation; the adoption the Rank technology in HashTrie construction and key word searching increases space and time efficiency of search. The method and system herein markedly reduce memory overhead and pretreatment time, can meet the need of timelessness as required by a real-time intrusion detection system as for when rules come into effect, and is more suitable for handling multi-pattern real-time matching which features in comparatively large scale of pattern string collection and comparatively short length of pattern string.

Method and system for space-efficient multi-pattern matching

The invention discloses an AMQ (approximate membership query) method based on a high-dimensional data filter. A new LSH (locality-sensitive hashing) function shown in the specification is defined to represent multi-dimensional data and to-be-inquired multi-dimensional data in a target data set respectively, the filter is not required to be reconstructed, the AMQ of more filter distance parameters can be supported, the space cost is substantially reduced, multiple function groups are used, each function group comprises multiple functions, a 'and-or' combined method is used when whether q is an approximate membership of the target data set omega or not is determined finally, and the false negative rate of the filter can be decreased; meanwhile, an entity calibrator is constructed for calibration, so that the false positive rate of the filter with different filter distance parameters is greatly decreased, and usually, space resources are greatly saved under the condition that the accuracy is slightly reduced with the entity filter number reducing method.

AMQ (approximate membership query) method based on high-dimensional data filter

The invention provides a grouping method and device of feature string sets. The method comprises the steps of obtaining length information of each feature string in multiple feature strings in the feature string sets; counting the number of the feature strings of each length information, generating a feature string number array according to the number, and generating a length array based on the length information; determining a grouping number according to the length array, and determining initial groups according to the grouping number and the feature string number array; choosing a group with the smallest feature string length in the initial groups as a first target group; making a second target group included in the multiple initial groups, and extending each feature string character in the first target group to obtain multiple corresponding extended character strings; making the second target group and surplus groups in the multiple initial groups as a third target group to match the feature string sets based on the third target group. According to the grouping method and device of the feature string sets, the feature set strings can be grouped automatically, and the information loss of initial feature strings is reduced.

Grouping method and device of feature string sets

The invention provides a hash-based string matching method and a method thereof for selecting a pattern string sub-window. The hash value of each pattern string is calculated by selecting the optimal sub-window of the corresponding pattern string so as to establish a hash table accordingly. Therefore, under the condition that a great many of pattern strings have the same prefixes, suffixes or sub-strings, the pattern strings are ensured to be hashed uniformly in the hash table as much as possible, so that the uniformity of the hash table is improved and the high-efficiency operation of the hash-based string matching method is guaranteed.

Hash-based string matching method and method thereof for selecting pattern string sub-window

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Hash-based string matching method and method thereof for selecting pattern string sub-window