CN106548069A - A kind of Feature Extraction System and method based on sort algorithm - Google Patents
A kind of Feature Extraction System and method based on sort algorithm Download PDFInfo
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- CN106548069A CN106548069A CN201610563595.0A CN201610563595A CN106548069A CN 106548069 A CN106548069 A CN 106548069A CN 201610563595 A CN201610563595 A CN 201610563595A CN 106548069 A CN106548069 A CN 106548069A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/55—Detecting local intrusion or implementing counter-measures
- G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
- G06F21/561—Virus type analysis
Abstract
The invention discloses a kind of Feature Extraction System and method based on sort algorithm, including：Database Unit, is configured to store the certain amount of feature for including one or more behavioural informations, and the feature-set is characterized 1；Feature flows into unit, is arranged to one or more black samples are carried out feature extraction and produce individual features, and is stored in Database Unit, and the individual features setting is characterized 2；Extraction unit, is arranged to one or more samples to be detected are carried out feature extraction and produce respective sample feature；Detector unit, is configured to produce testing result based on the compare mode of checking of any one characteristic element f and the sample characteristics in the feature 1 and feature 2 for receiving；And sequencing unit, being configured the ranking function result based on testing result carries out including the sequence of order to one or more features.The present invention overcomes tradition not screen to carried feature in automatically extracting feature mode, causes the uneven problem of put forward characteristic mass.
Description
Technical field
The present invention relates to computer security technique field, relates more specifically to a kind of feature extraction system based on sort algorithm
System and method.
Background technology
As the fast development of computer technology is widely available with the Internet, network safety event emerges in an endless stream, and arrives greatly
National attack, it is little to general Websites by extension horse, it is all closely bound up with computer virus, from the angle of Protection of Network Security
From the point of view of degree, the feature for extracting virus becomes the top priority of identification virus, the so-called feature i.e. mark of the virus, the spy for being carried
Levy the discrimination height to the viroid and the wrong report of the non-viroid will not be caused to be high-quality feature.
Existing virus characteristic extracting method mainly has two kinds, the artificial mode extracted and automatically extracts mode, conventional
Artificial feature mode of extracting is, analyzes same family's Virus Sample first by static and dynamic mode, then analyze its character string,
Network behavior etc. proposes to identify the viroid or the feature with family viral, and manual type has some limitations, first
First feature efficiency is not high, depending on next technical merit also because of analysis project teacher of the quality to carried feature；Conventional carries automatically
The mode for taking feature is to extract feature, automatization feature using identical algorithm to each Virus Sample or network packet
In order to avoid wrong report is typically complete hash, such versatility is poor, and substantial amounts are less efficient.And not to carried spy
Levy and screened, i.e., the grade of all features is identical, this causes carried characteristic mass uneven, and then affect to use feature
Antivirus engine recall rate and rate of false alarm, it is impossible to meet need of the environment in the confined space using the high-quality feature of needs
Ask.
The content of the invention
In order to solve above-mentioned technical problem, there is provided a kind of Feature Extraction System based on sort algorithm of the invention
And method.
According to the first aspect of the invention, there is provided a kind of Feature Extraction System based on sort algorithm.The system includes：
Database Unit, is configured to store the certain amount of feature including one or more behavioural informations, wherein the feature sets
It is set to feature 1；Feature flows into unit, is configured for one or more black samples are carried out feature extraction and produce corresponding spy
Levy, and the individual features are stored in into Database Unit, wherein individual features setting is characterized 2；Extraction unit, is configured
Into for feature extraction being carried out to one or more samples to be detected produce respective sample feature；Detector unit, is configured to
Inspection is produced based on the compare mode of checking of any one characteristic element f and the sample characteristics in the feature 1 and feature 2 for receiving
Survey result；And sequencing unit, it is configured to wrap one or more features based on the ranking function result of testing result
Include the sequence of order.
In certain embodiments, the ranking function also including below equation come score function S (f) for calculating：
S(f)=S+n-m；
Wherein, its initial score of the arbitrary characteristics element f is set to S, and n is represented in the sample characteristics by the arbitrary characteristics
The black number of samples that element f is verified, m are verified as black sample by the arbitrary characteristics element f in representing the sample characteristics
White number of samples.
In certain embodiments, the sequencing unit can carry out descending or ascending sort using the ranking function.
In certain embodiments, also include：
Unit is deleted, is configured to delete one or more features and form the certain amount of feature based on the sequence.
In certain embodiments, also include：
Unit is deleted, and is configured to one or more of features be deleted based on the m values, wherein m>3, then delete corresponding
The characteristic element f.
In certain embodiments, the deletion unit is configured to be deleted and ranked behind or forward based on the sequence
The feature of predetermined number forms the certain amount of feature.
According to the second aspect of the invention, there is provided a kind of feature extracting method based on sort algorithm, including：Based on the data
The certain amount of feature including one or more behavioural informations stored in library unit, wherein the feature-set is characterized 1；
Feature extraction is carried out to one or more black samples based on feature inflow unit and individual features are produced, and will be described corresponding
Feature is stored in Database Unit, wherein individual features setting is characterized 2；One or more are treated based on the extraction unit
Detection sample carries out feature extraction and produces respective sample feature；Based in feature 1 and feature 2 that the detector unit is received
The compare mode of checking of any one characteristic element f and sample characteristics produces testing result；And it is single based on the sequence
Unit carries out including the sequence of order to one or more features for the ranking function result of testing result.
In certain embodiments, the ranking function also including below equation come score function S (f) for calculating：
S(f)=S+n-m
Wherein, its initial score of the arbitrary characteristics element f is set to S, and n is represented in the sample characteristics by the arbitrary characteristics
The black number of samples that element f is verified, m are verified as black sample by the arbitrary characteristics element f in representing the sample characteristics
White number of samples.
In certain embodiments, the sequencing unit can carry out descending or ascending sort using the ranking function.
In certain embodiments, also include：
Delete one or more features and form the certain amount of feature for the sequence based on unit is deleted.
In certain embodiments, also include：
One or more of features, wherein m are deleted for the m values based on unit is deleted>3, then delete corresponding described
Characteristic element f.
In certain embodiments, the deletion unit is deleted and is ranked behind or forward predetermined number based on the sequence
Feature form the certain amount of feature.
By using the system and method for the present invention, it is possible to use the feature extracted carrying out comparison and detection to sample characteristics,
Carry out ranking to eliminate with reference to sort algorithm to testing result, for the feature improved in feature database, improve feature extraction
High-quality feature can be also extracted while efficiency, meet user the confined space environment use high-quality characteristics need
Will.
Description of the drawings
In order to be illustrated more clearly that technical scheme, letter will be made to accompanying drawing to be used needed for embodiment below
Singly introduce, it should be apparent that, drawings in the following description are only some embodiments described in the present invention, for this area
For those of ordinary skill, on the premise of not paying creative work, can be with according to these other accompanying drawings of accompanying drawings acquisition.
Fig. 1 shows the block diagram of the Feature Extraction System based on sort algorithm according to embodiments of the present invention.
The flow chart that Fig. 2 shows the feature extracting method based on sort algorithm according to embodiments of the present invention.
Specific embodiment
With reference to the accompanying drawings to a preferred embodiment of the present invention will be described in detail, eliminated for this in the course of the description
It is unnecessary details and function for invention, to prevent the understanding of the present invention from causing to obscure.Show although showing in accompanying drawing
Example property embodiment, it being understood, however, that may be realized in various forms the present invention and should not be limited by embodiments set forth here
System.On the contrary, there is provided these embodiments are able to be best understood from the disclosure, and can be complete by the scope of the present invention
Convey to those skilled in the art.
Hereinafter, by all types of computer viruses（Including nonspecific infection sexually transmitted disease (STD) poison, the grand diseases of Word and Excel
Poison, leading viruses, script virus, wooden horse, backdoor programs, Key Logger, password eavesdropper etc.）Feature be referred to as
" feature ", to facilitate description.It will be understood by those skilled in the art that " feature " hereinafter can be any type of computeritis
Malicious feature.
Fig. 1 shows the block diagram of the Feature Extraction System based on sort algorithm according to embodiments of the present invention.Such as Fig. 1 institutes
Show, system can include：Database Unit 110, feature flows into unit 120, extraction unit 130, detector unit 140, sequence list
Unit 150.
Database Unit 110, is configured to store the certain amount of feature including one or more behavioural informations, wherein
Feature-set is characterized 1.
Wherein, certain amount of feature can have user to set, to safeguard a limited characteristic set.It is mentioned herein
Feature can be the feature for being initially identified as computer virus, the feature extraction in the stage shape when system is set up
Into.
Feature flows into unit 120, is configured for carrying out feature extraction to one or more black samples and producing corresponding
Feature, and individual features are stored in into Database Unit, wherein individual features setting is characterized 2.
Wherein, feature flows into unit 120 and the black sample characteristics for automatically extracting can be continued to flow into into characteristic set, continues
Flow into sample and ensure continuing to increase, update, breeding for feature.
Extraction unit 130, is configured for carrying out feature extraction to one or more samples to be detected and producing corresponding
Sample characteristics.
Wherein, the substantial amounts of black and white sample for continuing to flow into is received, and these samples is carried out with feature extraction, produce corresponding sample
Eigen.
A large amount of black and white samples to continuing to flow in extraction unit 130 carry out feature extraction, and if will produce dry sample
Eigen is sent to detector unit 140, and wherein black and white sample carried out detection setting by user before feature inflow.
Detector unit 140, is configured to based on any one characteristic element f and sample in the feature 1 and feature 2 for receiving
The compare mode of checking of feature produces testing result；The testing result includes what is be consistent with characteristic element f or do not correspond
Sample characteristics number.
Wherein, will be any one characteristic element f special with some samples that extraction unit 130 sends in detector unit 140
Levying carries out comparison one by one, it is preferred that detect the black and white sample number difference in the sample characteristics matched with characteristic element f
Represented with n, m, wherein n, m are positive integer.
Sequencing unit 150, is configured to wrap one or more features based on the ranking function result of testing result
Include the sequence of order.
Wherein, detector unit 140 will be sent to sequencing unit 150 including these testing results.Sequencing unit 150 is received
After testing result, scored using score function S (f) in ranking function, and one or more feature ranking functions are tied
Fruit is ranked up, it is preferred that sequencing unit 150 can be ranked up by the way of descending using ranking function.
In certain embodiments, ranking function also including below equation come score function S (f) for calculating：
S(f)=S+n-m；
Wherein, its initial score of arbitrary characteristics element f is set to S, and n is verified by arbitrary characteristics element f in representing sample characteristics
Black number of samples, m is verified as the white number of samples of black sample by arbitrary characteristics element f in representing sample characteristics.
In certain embodiments, sequencing unit 150 can carry out descending sort using ranking function.Wherein, sequencing unit
150 can also carry out ascending sort using ranking function.
Specifically, if using the sortord of descending, one or more features deleted rearward form specific
The feature of quantity；If using the sortord of ascending order, delete one or more forward feature and form specific quantity
Feature.Here sequence and the relation between deleting can be set according to the demand of user.
In certain embodiments, also include：
Unit 160 is deleted, is configured to delete one or more features and form certain amount of feature based on sequence.
In certain embodiments, also include：
Unit 160 is deleted, and is configured to one or more features be deleted based on m values, wherein m>3, then delete corresponding feature
Element f.
Specifically, as the white sample number m for detecting>When 3, unit 160 is deleted by corresponding characteristic element f directly from feature
Delete in set, then the feature of the deletion will not be ranked up again.
In certain embodiments, delete unit 160 to be configured to based on sequence and delete and rank behind or forward default
The feature of quantity forms certain amount of feature.
Specifically, the quantity of deletion can be arranged according to different production environments in advance by user.
In another embodiment, one or more features of deletion are identical with the quantity of the feature 2.Wherein, delete
Feature quantity it is identical with the quantity of feature 2 with produce feature 1 gather, and ensure quantity and user setting specific quantity phase
Together.
The flow chart that Fig. 2 shows the feature extracting method based on sort algorithm according to embodiments of the present invention, as shown in Fig. 2
Method comprises the steps：
S210, based on the certain amount of feature including one or more behavioural informations stored in Database Unit 110, wherein
Feature-set is characterized 1；
S220, feature based flow into unit 120 and carry out feature extraction to one or more black samples and produce individual features, and will
Individual features are stored in Database Unit, and wherein individual features setting is characterized 2；
One or more samples to be detected are carried out feature extraction based on extraction unit 130 and produce respective sample feature by S230；
S240, is carried out with sample characteristics based on any one characteristic element f in feature 1 and feature 2 that detector unit 140 is received
The mode of comparison produces testing result；
S250, based on sequencing unit 150 for testing result ranking function result one or more features are carried out including it is suitable
The sequence of sequence.
In certain embodiments, ranking function also including below equation come score function S (f) for calculating：
S(f)=S+n-m
Wherein, its initial score of arbitrary characteristics element f is set to S, and n is verified by arbitrary characteristics element f in representing sample characteristics
Black number of samples, m is verified as the white number of samples of black sample by arbitrary characteristics element f in representing sample characteristics.
In certain embodiments, sequencing unit 150 can carry out descending or ascending sort using ranking function.
In certain embodiments, also include：
S260, deletes one or more features and forms certain amount of feature for sequence based on unit 160 is deleted.
In certain embodiments, also include：
One or more features are deleted for m values based on unit 160 is deleted, wherein m>3, then delete corresponding characteristic element
f。
Specifically, as the white sample number m for detecting>When 3, unit 160 is deleted by corresponding characteristic element f directly from feature
Delete in set, then the feature of the deletion will not be ranked up again.
In certain embodiments, delete unit 160 deleted based on sequence rank behind or forward predetermined number spy
Levy to form certain amount of feature.
Specifically, the quantity of deletion can be arranged according to different production environments in advance by user.
In another embodiment, one or more features of deletion are identical with the quantity of the feature 2.Wherein, delete
Feature quantity it is identical with the quantity of feature 2 with produce feature 1 gather, and ensure quantity and user setting specific quantity phase
Together.
To sum up, above-described embodiment disclosed in this invention, it is special by persistently flowing into data base using substantial amounts of black and white sample
Storehouse is levied, all features in this feature storehouse is detected using the feature extracted, is carried out comparison and detection, with reference to sort algorithm
Eliminate ranking is carried out to testing result, periodically delete, so as to be effectively realized the detection for quickly drawing checking feature and wrong report
Feature in situation, and constantly improve feature database, can also extract high-quality feature while the efficiency for improving feature extraction.
So far already in connection with preferred embodiment, invention has been described.It should be understood that those skilled in the art are not
In the case of departing from the spirit and scope of the present invention, various other changes can be carried out, replace and add.Therefore, the present invention
Scope be not limited to above-mentioned specific embodiment, and should be defined by the appended claims.
Claims (12)
1. a kind of Feature Extraction System based on sort algorithm, it is characterised in that include：
Database Unit, is configured to store the certain amount of feature including one or more behavioural informations, wherein the spy
Levy setting and be characterized 1；
Feature flows into unit, is configured for one or more black samples are carried out feature extraction and produce individual features, and
The individual features are stored in into Database Unit, wherein individual features setting is characterized 2；
Extraction unit, is configured for carrying out feature extraction to one or more samples to be detected and producing respective sample spy
Levy；
Detector unit, is configured to enter with sample characteristics based on any one characteristic element f in the feature 1 and feature 2 for receiving
The mode of row comparison produces testing result；And
Sequencing unit, is configured to one or more features be carried out including order based on the ranking function result of testing result
Sequence.
2. system according to claim 1, it is characterised in that the ranking function is also including below equation come commenting for calculating
Divide function S (f)：
S(f)=S+n-m；
Wherein, its initial score of the arbitrary characteristics element f is set to S, and n is represented in the sample characteristics by the arbitrary characteristics
The black number of samples that element f is verified, m are verified as black sample by the arbitrary characteristics element f in representing the sample characteristics
White number of samples.
3. system according to claim 1, it is characterised in that the sequencing unit can be carried out using the ranking function
Descending or ascending sort.
4. the system according to any one of claims 1 to 3, it is characterised in that also include：
Unit is deleted, is configured to delete one or more features and form the certain amount of feature based on the sequence.
5. system according to claim 2, it is characterised in that also include：
Unit is deleted, and is configured to one or more of features be deleted based on the m values, wherein m>3, then delete corresponding
The characteristic element f.
6. system according to claim 4, it is characterised in that the deletion unit is configured to delete based on the sequence
Except ranking behind or the feature of forward predetermined number forms the certain amount of feature.
7. a kind of feature extracting method based on sort algorithm, it is characterised in that include：
Based on the certain amount of feature including one or more behavioural informations stored in the Database Unit, wherein described
Feature-set is characterized 1；
Feature extraction is carried out to one or more black samples based on feature inflow unit and individual features are produced, and will be described
Individual features are stored in Database Unit, wherein individual features setting is characterized 2；
Feature extraction is carried out to one or more samples to be detected based on the extraction unit and respective sample feature is produced；
Compared with sample characteristics based on any one characteristic element f in feature 1 and feature 2 that the detector unit is received
The mode of checking produces testing result；And
One or more features are carried out including order based on ranking function result of the sequencing unit for testing result
Sequence.
8. method according to claim 7, it is characterised in that the ranking function is also including below equation come commenting for calculating
Divide function S (f)：
S(f)=S+n-m
Wherein, its initial score of the arbitrary characteristics element f is set to S, and n is represented in the sample characteristics by the arbitrary characteristics
The black number of samples that element f is verified, m are verified as black sample by the arbitrary characteristics element f in representing the sample characteristics
White number of samples.
9. method according to claim 7, it is characterised in that the sequencing unit can be carried out using the ranking function
Descending or ascending sort.
10. the method according to any one of claim 7 to 9, it is characterised in that also include：
Delete one or more features and form the certain amount of feature for the sequence based on unit is deleted.
11. methods according to claim 8, it is characterised in that also include：
One or more of features, wherein m are deleted for the m values based on unit is deleted>3, then delete corresponding described
Characteristic element f.
12. methods according to claim 10, it is characterised in that the deletion unit deletes ranking based on the sequence
Rearward or the feature of forward predetermined number forms the certain amount of feature.
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