CN100485664C - Automatic state machine searching and matching method of multiple key words - Google Patents
Automatic state machine searching and matching method of multiple key words Download PDFInfo
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- CN100485664C CN100485664C CNB021113769A CN02111376A CN100485664C CN 100485664 C CN100485664 C CN 100485664C CN B021113769 A CNB021113769 A CN B021113769A CN 02111376 A CN02111376 A CN 02111376A CN 100485664 C CN100485664 C CN 100485664C
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Abstract
The automatic state machine searching and matching method includes the following steps: establishing total match state list; inputting information to be matched; automatic searching and matching with the automatic state machine by means of the total match state list; and outputting the searching and matching result. The present invention has fast searching speed independent on regulation number and no special requirement on the code of searched key word, can search text as multilingual combination, and can search several specific key words simultaneously or some specified key word. The present invention may be used in real-time network information monitoring system, large scale monitoring system with great search information amount and common information detecting system.
Description
Technical field
The present invention relates to used keyword search matching process in a kind of computer security filtration, relate in particular to a kind of multiple key of in network textual data bag, locating the particular problem key word and search matching process.
Background technology
The existing matching process of searching to single key word has a lot, and method at present commonly used is an automatic state machine searching and matching method, and the roughly thinking of this method is such: state machine M be one 5 tuple (Q, q, A, Σ, δ), wherein
Q is the finite aggregate of state
It is initial state that q belongs to Q
A belongs to the accepting state collection that Q is a uniqueness
Σ is limited input alphabet
δ is the transition function from state Q* Σ to Q of state machine M.
If state machine at state q, reads in input character a, then it becomes state δ (q, a) (carried out once propagate) from state q.When its current state belonged to A, then state machine M had received the string that is read in up to now.
There is a string coupling automat in each pattern P, must pretreatment stage goes out the automat of response according to schema construction after, could utilizes it to come the searching text string.Fig. 1 is the state transition graph about the state machine of pattern P=ababaca.Its initial state is 0, state set Q={0,1,2,3,4,5,6,7}, input alphabet Σ={ a, b, c}.Fig. 2 is the construction process of corresponding transfer function δ.
We are as can be seen for character set Σ={ a arbitrarily from Fig. 1 and Fig. 2, b, the text string input of c}, with current state and input character is input parameter, through state transition function δ, we can obtain a new state, in case the output result of state transition function δ is a state 7, that is to say to have arrived the accepting state that we set, we have just found search string.
Present automatic state machine searching and matching method is reasonable to be searched with having solved single key word and mates, and to searching each character of text only more once, can satisfy the requirement of system to algorithm on speed.But when needs are searched a plurality of key word (for example 2000 key words), then need a kind ofly the state table of a plurality of key words to be united the generating algorithm that forms a total state table, this need consider the problem that the similar state with the state table of a plurality of key words merges, but present automatic state machine searching and matching method can not solve the problem that multiple key is searched simultaneously.
In addition, the keyword search method of " prefix search tree " that the Si Dier .P. Nikkor of the U.S. proposed in nineteen ninety (Chinese patent application number 90107971.5) with partial key branching, what will comprise that the node of prefix key field constitutes searches the prefix index tree can find out a plurality of key words from text, but this method can't reach on speed each character more once linear speed of searching only.
Summary of the invention
The objective of the invention is to propose a kind ofly can search coupling simultaneously and on speed, reach to a plurality of key words to each character more once linear automatic state machine searching and matching method of searching speed only.
Technical scheme of the present invention is achieved in that a kind of automatic state machine searching and matching method of multiple key words, comprises the following steps:
1. set up the total state table of coupling;
2. import information to be matched;
3. the automatic state machine utilization is mated total state table and is searched coupling;
4. matching result is searched in output.
1. wherein said step comprises two stages: the phase one, subordinate phase was the state in synchronously total state table in order to generate the total state table of multiple key.
Phase one comprises the following steps:
1.-1. total state table of initialization automatic state machine, each key word state table and final state coupling description list;
2.-1. determine the relation between all key words to be found, for relation of inclusion being arranged and having some byte status of the key word of same prefix to determine or merge;
3.-1. the character that is not matched in the character state table to all key words mates again;
4.-1. carry out the generation of total state table according to the character state table.
Subordinate phase comprises the following steps:
1.-2. to each key word, set up an interim state table;
2.-2. all key words to be matched are found the prefix of all couplings in this key word, compare with existing prefix in the interim state table;
3.-2. upgrade state in the interim state table according to the maximum-prefix principle;
4.-2. according to the content in the interim state table total state table is upgraded.
The merging degree of a single state machine between key word depends on the similarity degree of status switch.Described similarity degree comprises three classes: relation of inclusion, similarity relation is with it doesn't matter.
Relation between described definite all key words to be found comprises:
1. judge whether certain key word and its following all key words have the prefix relation;
2. judge whether both keyword has relation of inclusion.
The key word that will have the prefix relation carries out following state and merges:
1.-3. if a next key word then deleted in identical key word, and discharge the character state table of the key word in back;
If 2.-3. both keyword has only part identical,, from the character state table of both keyword, find out the current state of key word under this character respectively then from first identical character.
1) if corresponding character state all is an idle condition in the both keyword, then get new state, and the corresponding state in the character state table of renewal both keyword is an identical intermediateness;
2),, then upgrade another current state with its value if one of them had been composed state if the current state in the character state table in the both keyword under certain character is not an idle condition;
3) if the two is not in idle condition, and both current states are unequal again, then judge it is to have had matching relationship.If the two all is a final state, be as the criterion with preceding state; If have only one to be final state, with this state synchronized corresponding state in another.
Both keyword there is the following processing of carrying out of relation of inclusion:
If to go here and there the state at pairing last character place be idle condition to 1. long key word comprising, then apply for a new final state;
If 2. long key word is gone here and there the state at pairing last character place for final state comprising, then apply for a new final state for it;
If 3. same prefix is arranged is again relation of inclusion to both keyword, then the final state of two key words is as the criterion with long key word;
4. if arrive last character coupling of long key word, then long key word is also added character state matches description list.
The described state that upgrades in the interim state table according to the maximum-prefix principle comprises the following steps:
If 1. matching length is the length of target keywords, then its state has all merged and has finished, and does not process;
If 2. a character is ending below the source key, source key then is described in target keywords, the two has relation of inclusion, continues to look for other coupling character if desired downwards, then proceeds to handle;
3. in interim state table, take out the maximum-prefix length of current coupling, if present prefix greater than original prefix, the state of correspondence wanted in character when then state transferred target keywords coupling termination to.
The present invention is according to the relation between a plurality of key words, generate the automatic state machine that can be used for searching simultaneously a plurality of key words of coupling, when the current state of automat is the final state of searching, certain in then a plurality of key words or a plurality of key word are arrived by Search and Orientation simultaneously.Seek rate of the present invention be to each character in the text only more once, can satisfy the real-time requirement of system to processing speed.Seek rate of the present invention and regular number are irrelevant, so more possess advantage under the many situations of regular quantity.
In sum, the present invention has following beneficial effect:
1, seek rate is fast.Only more once, to searching the demanding system of speed real-time, speed advantage of the present invention is apparent in view to each character in the text.
2, seek rate and regular number are irrelevant.Simultaneously what of the quantity of matched and searched key word are to not influence of seek rate, requirement that can the satisfying magnanimity rule.
3, the coding to search key does not have specific (special) requirements, can search the text that kinds of words is mixed.
4, can search a plurality of special key words simultaneously, also can only search some key words of appointment.
Description of drawings
Fig. 1 be in the prior art automatic state machine about the state exchange synoptic diagram of pattern string P=ababaca.
Fig. 2 be in the prior art automatic state machine about the construction process synoptic diagram of the state transition function δ of pattern string P=ababaca.
Fig. 3 is the general flow chart of the automatic state machine searching and matching method of multiple key words that proposes of the present invention.
Fig. 4 is a process flow diagram of setting up the phase one of the total state table of coupling in the method that proposes of the present invention.
Fig. 5 is a process flow diagram of setting up the subordinate phase of the total state table of coupling in the method that proposes of the present invention.
Embodiment
The present invention is described in further detail below in conjunction with accompanying drawing.
Fig. 1 and Fig. 2 had done explanation in background technology.
Fig. 3 is the general flow chart of the automatic state machine searching and matching method of multiple key words that proposes of the present invention.Filtration treatment to agreement text to be checked can be regarded as the problem of inquiring about a plurality of special key words in one section text simultaneously.Because the IDS system requires often all than higher real-time, the processing speed of search key and accuracy directly have influence on the quality of coupling strainability in text, and its performance is a key component of system performance.System requirements is the least possible to each character match number of times of searching text, and the length of search key is to searching not influence of performance.In addition, the quantity of the key word that system requirements is searched simultaneously should be as much as possible little to the influence of system, can the performance of system be declined to a great extent because of rolling up of search key quantity.As shown in Figure 3, this automatic state machine searching and matching method of multiple key words that the present invention proposes comprises the following steps: 1. to set up the total state table of coupling; 2. import information to be matched; 3. the automatic state machine utilization is mated total state table and is searched coupling; 4. matching result is searched in output.
1. step recited above comprises two stages: the phase one, subordinate phase was the state in synchronously total state table in order to generate the total state table of multiple key.Fig. 4 is a process flow diagram of setting up the phase one of the total state table of coupling in the method that proposes of the present invention.As shown in Figure 4, the phase one comprises the following steps: 1. total state table of initialization automatic state machine, each key word state table and final state coupling description list.The key word state table is the state table of each byte of each key word.Character state matches description list is the information that is illustrated in the key word that finds under certain final state.2. determine the relation between all key words to be found, for relation of inclusion being arranged and having some byte status of the key word of same prefix to determine or merge; 3. the character that is not matched in the character state table to all key words mates again; 4. carry out the generation of total state table according to the character state table.
The state table of this key word can be summarized in each key word, the current key word prefix of having mated of the state representation in the state table.For mating a plurality of key words simultaneously, then the state in each key word state table can and must merge.The merging degree of a single state machine depends on the similarity degree of status switch between key word, so the relation between key word and key word can be divided with the similarity degree between them.The position of same section in key word according to both keyword can be classified as the mutual relationship between key word following several classes:
| Finish begin | Head | In | Tail |
| Head | Relation of inclusion | It doesn't matter | It doesn't matter |
| In | Similarity relation | Relation of inclusion | It doesn't matter |
| Tail | Relation of inclusion | Similarity relation | It doesn't matter |
What need merging is the key word with similarity relation and relation of inclusion.
Key word with similarity relation is divided into two classes:
One class is the head of same section from both keyword, ends in the key word.As the relation between abcde and abcmnl, they have identical prefix key abc.
Another kind of is same section in the middle of one of them key word, and as abcdef and bcdgk, the prefix bcd of second key word is identical with part in first key word.
What also have is exactly (both keyword identical or a key word start anew to be completely contained in another key word) with special relation of inclusion.Comprised by acdfg as acd, abc is comprised by aabcd.
If begin mutually without any similarity relation from prefix between the both keyword, then do not have between state possibility of conversion mutually between them, their state set is common factor not, and the state of both keyword will independently be present in the multiple key state machine mutually so.
Relation between key word is if having the above-mentioned relation that connects each other, and both keyword will have the relation of mutual state exchange in state table so.The state of keyword fragment in state table that both keyword is identical must represent that the state that key word finds is fully represented with final state with unique state.If a certain key word belongs to the middle part of another key word, then the state of this key word all belongs to the state set of another key word.
The of the described phase one determines that the relation between all key words to be found comprises in 2.: 1. judge certain key word with its down all key words judged whether that prefix concerns; 2. judge whether both keyword has relation of inclusion.
The key word that will have the prefix relation carries out following state and merges:
1. if a next key word then deleted in identical key word, and discharge the character state table of the key word in back;
If 2. both keyword has only part identical,, from the character state table of both keyword, find out the current state of key word under this character respectively then from first identical character.
1) if corresponding character state all is an idle condition in the both keyword, then get new state, and the corresponding state in the character state table of renewal both keyword is an identical intermediateness;
2),, then upgrade another current state with its value if one of them had been composed state if the current state in the character state table in the both keyword under certain character is not an idle condition;
3) if the two is not in idle condition, and both current states are unequal again, then judge it is to have had matching relationship.If the two all is a final state, be as the criterion with preceding state; If have only one to be final state, with this state synchronized corresponding state in another.
Both keyword there is the following processing of carrying out of relation of inclusion:
If to go here and there the state at pairing last character place be idle condition to 1. long key word comprising, then apply for a new final state;
If 2. long key word is gone here and there the state at pairing last character place for final state comprising, then apply for a new final state for it;
If 3. same prefix is arranged is again relation of inclusion to both keyword, then the final state of two key words is as the criterion with long key word;
4. if arrive last character coupling of long key word, then long key word is also added character state matches description list.
In the 3. step of phase one, the character that is not matched in the character state table to all key words mates again.The character that is not matched in the character state table to all key words mates again.For the new intermediateness of application that is idle condition.If the current state idle condition under the key word last character is then applied for a new final state.
Phase one the 4. the step is the generation of carrying out total state table according to the character state table.Total state table is the bivariate table that variable is respectively state and input character, and data are the next redirect state of status change in the table.
According to the state table of all key words, all state synchronized in total state table, can tentatively be finished the foundation of total state table.The best redirect problem that preliminary total state table exists in the time of can't solving state exchange between key word, just all key words (comprising) implicit maximum under this state itself has been mated the problem of prefix under certain character state.By each key word being built an interim state table, in this key word, find the prefix of all couplings and the existing prefix in the temporary table to compare to all key words to be found, keep maximum-prefix, at last temporary table is updated in total state table and goes, finish the foundation of total state table.Fig. 5 is a process flow diagram of setting up the subordinate phase of the total state table of coupling in the method that proposes of the present invention.As shown in Figure 5,1. subordinate phase comprises the following steps: an interim state table set up in each key word; 2. all key words to be matched are found the prefix of all couplings in this key word, compare with existing prefix in the interim state table; 3. upgrade state in the interim state table according to the maximum-prefix principle; 4. according to the content in the interim state table total state table is upgraded.Method for synchronous is to all key words, and establishing initial current state is idle condition, and input character is first character of key word, and then the next redirect state of total state table is the next redirect state under the current character of this key word in the character state table.Then establishing current state is next redirect state, and current input character is second character of key word, again from this key word the character state table, get Next redirect state.The rest may be inferred, in total state table that the character state table of all key words is synchronous.
To each key word, set up an interim state table, be that variable is the two-dimensional array of key length and character probable value (255), the array value of depositing is to stop to this character at present, next jumps the possible maximum length of text reach prefix.All key words to be found compare with other, find out its all prefixes, relatively find its string system according to original table, and determine the content of its state machine at each byte, upgrade interim state table, refresh total state transition table.To source key relatively, find out the length of purpose key word coupling prefix therein therein.
The state that upgrades in the interim state table according to the maximum-prefix principle comprises the following steps:
If 1. matching length is the length of purpose key word, the state of this relation of inclusion is determined, determines in the relation of inclusion coupling in front, and its state has all merged to be finished, and can not process;
If 2. a character is ending below the source key, source key then is described in target keywords, the two has relation of inclusion, continues to look for other coupling character if desired downwards, then can proceed to handle;
3. in interim state table, take out the maximum-prefix length of current coupling, if present prefix greater than original prefix, the state of correspondence wanted in character when then state transferred purpose keyword matching termination to.
Range of application of the present invention is very extensive, can be applicable to HTTP, and FTP searches a plurality of key words simultaneously in text in the safety filterings such as mail.Promptly can be used for exigent real-time network information monitoring system of real-time and the very big extensive monitoring of retrieving information amount, also can be applicable to general information detecting system.
Claims (9)
1, a kind of automatic state machine searching and matching method of multiple key words is characterized in that comprising the following steps:
1. set up the total state table of coupling, comprise two stages: the phase one, subordinate phase was the state in synchronously total state table in order to generate the total state table of multiple key;
2. import information to be matched;
3. the automatic state machine utilization is mated total state table and is searched coupling;
4. matching result is searched in output.
2, a kind of automatic state machine searching and matching method of multiple key words according to claim 1 is characterized in that the described phase one comprises the following steps:
1.-1. total state table of initialization automatic state machine, each key word state table and final state mate description list;
2.-1. determine the relation between all key words to be found, for relation of inclusion being arranged and having the byte status of the key word of same prefix to determine or merge;
3.-1. the character that is not matched in the character state table to all key words mates again;
4.-1. carry out the generation of total state table according to the character state table.
3, a kind of automatic state machine searching and matching method of multiple key words according to claim 1 is characterized in that described subordinate phase comprises the following steps:
1.-2. to each key word, set up an interim state table;
2.-2. all key words to be matched are found the prefix of all couplings in this key word, compare with existing prefix in the interim state table;
3.-2. upgrade state in the interim state table according to the maximum-prefix principle;
4.-2. according to the content in the interim state table total state table is upgraded.
4, a kind of automatic state machine searching and matching method of multiple key words according to claim 2, it is characterized in that: the merging degree of a single state machine between described key word depends on the similarity degree of status switch, described similarity degree comprises three classes: relation of inclusion, similarity relation is with it doesn't matter.
5, a kind of automatic state machine searching and matching method of multiple key words according to claim 2, it is characterized in that described step 2.-1. comprise:
1. judge whether certain key word and its following all key words have the prefix relation;
2. judge whether both keyword has relation of inclusion.
6, a kind of automatic state machine searching and matching method of multiple key words according to claim 5 is characterized in that the key word that will have the prefix relation carries out following state and merges:
1.-3. if a next key word then deleted in identical key word, and discharge the character state table of the key word in back;
If 2.-3. both keyword has only part identical,, from the character state table of both keyword, find out the current state of key word under this character respectively then from first identical character.
7, a kind of automatic state machine searching and matching method of multiple key words according to claim 6, it is characterized in that described step 2.-3. specifically comprise the steps:
If 1. corresponding character state all is an idle condition in the both keyword, then get new state, and the corresponding state in the character state table of renewal both keyword is an identical intermediateness;
If 2. the current state in the character state table under certain character is not an idle condition in the both keyword,, then upgrade another current state with its value if one of them had been composed state;
3. if the two is not in idle condition, and both current states are unequal again, then judge it is to have had matching relationship.If the two all is a final state, be as the criterion with preceding state; If have only one to be final state, with this state synchronized corresponding state in another.
8, a kind of automatic state machine searching and matching method of multiple key words according to claim 5 is characterized in that both keyword is had the following processing of carrying out of relation of inclusion:
If to go here and there the state at pairing last character place be idle condition to 1. long key word comprising, then apply for a new final state;
If 2. long key word is gone here and there the state at pairing last character place for final state comprising, then apply for a new final state for it;
If 3. same prefix is arranged is again relation of inclusion to both keyword, then the final state of two key words is as the criterion with long key word;
4. if arrive last character coupling of long key word, then long key word is also added character state matches description list.
9, a kind of automatic state machine searching and matching method of multiple key words according to claim 3, it is characterized in that described step 3.-2. comprise the following steps:
If 1. matching length is the length of target keywords, then its state has all merged and has finished, and does not process;
If 2. a character is ending below the source key, source key then is described in target keywords, the two has relation of inclusion, continues to look for other coupling character if desired downwards, then proceeds to handle;
3. in interim state table, take out the maximum-prefix length of current coupling, if present prefix greater than original prefix, the state of correspondence wanted in character when then state transferred target keywords coupling termination to.
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| CNB021113769A CN100485664C (en) | 2002-04-10 | 2002-04-10 | Automatic state machine searching and matching method of multiple key words |
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| CNB021113769A CN100485664C (en) | 2002-04-10 | 2002-04-10 | Automatic state machine searching and matching method of multiple key words |
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| CN100485664C true CN100485664C (en) | 2009-05-06 |
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Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101246475B (en) * | 2007-02-14 | 2010-05-19 | 北京书生国际信息技术有限公司 | Retrieval methodology base on layout information |
| CN100452055C (en) * | 2007-04-13 | 2009-01-14 | 清华大学 | Large-scale and multi-key word matching method for text or network content analysis |
| CN101499065B (en) | 2008-02-01 | 2011-11-02 | 华为技术有限公司 | Table item compression method and device based on FA, table item matching method and device |
| CN101827095B (en) * | 2010-04-06 | 2012-10-24 | 北京网康科技有限公司 | Method and equipment for rapidly resolving protocol based on carriage returns and line feeds |
| CN101841546B (en) * | 2010-05-17 | 2013-01-16 | 华为技术有限公司 | Rule matching method, device and system |
| CN102521357A (en) * | 2011-12-13 | 2012-06-27 | 曙光信息产业(北京)有限公司 | System and method for achieving accurate matching of texts by automaton |
| CN103226551B (en) * | 2012-01-31 | 2016-05-25 | 中国科学技术大学 | The matching process of the non deterministic finite automaton based on TCAM and device |
| CN106874442B (en) * | 2017-02-08 | 2023-08-18 | 三和智控(北京)系统集成有限公司 | Method and device for realizing self-carrying characteristic information of data through naming of data name |
| CN107679219B (en) * | 2017-10-19 | 2021-05-11 | 广州视睿电子科技有限公司 | Matching method and device, interactive intelligent panel and storage medium |
| CN110365726B (en) * | 2018-04-09 | 2022-07-19 | 阿里巴巴集团控股有限公司 | Communication processing method, device, terminal and server |
| CN110781355A (en) * | 2018-07-31 | 2020-02-11 | 中兴通讯股份有限公司 | Storage information processing method and device, storage cabinet and storage medium |
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