CN106656677A - Deep packet detection system and method oriented to big data - Google Patents
Deep packet detection system and method oriented to big data Download PDFInfo
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- CN106656677A CN106656677A CN201710024886.7A CN201710024886A CN106656677A CN 106656677 A CN106656677 A CN 106656677A CN 201710024886 A CN201710024886 A CN 201710024886A CN 106656677 A CN106656677 A CN 106656677A
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Abstract
The invention discloses a deep packet detection system and method oriented to big data, and relates to the field of deep packet detection. A core component of the deep packet detection system comprises a deep packet detection engine, and realizes a deep packet detection function on the basis of a deep packet detection strategy rule. The deep packet detection engine comprises a data packet scanning sub-function entity, a data packet analysis sub-function entity, a data pre-extraction sub-function entity, a data pre-conversion sub-function entity and a data packet operation execution sub-function entity, wherein the data packet scanning sub-function entity is used for finishing initial detection of data packets of the deep packet detection system; the data packet analysis sub-function entity is used for finishing basic analysis of data packets entering the deep packet detection system; the data pre-extraction sub-function entity is used for realizing data pre-extraction of a big data demand; the data pre-conversion sub-function entity is used for realizing data pre-conversion specific to the big data demand; and the data packet operation execution sub-function entity is used for realizing final operation of the data packets entering the system. Through adoption of the deep packet detection system and method, the real-time performance and efficiency of a big data relevant technology can be improved remarkably.
Description
Technical field
The present invention relates to deep-packet detection field, is specifically related to a kind of deep-packet detection system towards big data and side
Method.
Background technology
DPI (Deep Packet Inspection, deep-packet detection) technology is based on from two layers to seven layer network agreements
Analysis, can realize the accurate perception to data in network, so as to accomplish the accurate assurance to network presence, deep-packet detection skill
Data in network can also be classified, be analyzed and preliminary treatment by art, to be supplied to other application or technology to enter traveling one
Step is processed and used.On the other hand, the big data epoch arrived, big data is referred to cannot be used in the time range that can be born
The data acquisition system that conventional software instrument is caught, managed and processed, that is to say, that big data needs new technology and method,
It is immeasurable constantly to create and be continuously present in the information value that the big data in network includes by network, but due to ichthyosauru
Mix, big data is extracted using exceedingly difficult so that each side in a network of place had both wished the income from big data, again cannot be light
Pine freely valuable information is obtained from big data.
In the big data epoch, when big data correlation technique network-oriented is analyzed in real time, great difficulty and challenge are faced.One side
The big data that torus network is produced is huge, and on the other hand, the related application of network is higher to requirement of real-time.So, how to solve
The problems referred to above are just worth further investigation.
The content of the invention
The invention aims to overcome the shortcomings of above-mentioned background technology, there is provided a kind of deep packet towards big data is examined
Examining system and method, can significantly improve the real-time and efficiency of big data correlation technique.
The present invention provides a kind of deep-packet detection system towards big data, and the core component of the deep-packet detection system is
Deep-packet detection engine, it realizes deep-packet detection function, deep-packet detection engine based on deep-packet detection policing rule storehouse
Including packet scanning sub-functional entities, data packet analysis sub-functional entities, data preextraction sub-functional entities, data pre-converted
Sub-functional entities, data package operation perform sub-functional entities, wherein：
Packet scanning sub-functional entities are used for the Preliminary detection of the packet for completing to enter deep-packet detection system；
Data packet analysis sub-functional entities are used for the fundamental analysis of the packet for completing to enter deep-packet detection system；
Data preextraction sub-functional entities are used to realize the data preextraction for big data demand；
Data pre-converted sub-functional entities are used to realize the data pre-converted for big data demand；
Data package operation performs sub-functional entities to be used to realize the final operation to the packet into system.
On the basis of above-mentioned technical proposal, the data preextraction sub-functional entities and data pre-converted sub-functional entities
Bypass condition is configured to, to realize that the deep-packet detection system is compatible with conventional depth bag detecting system.
On the basis of above-mentioned technical proposal, packet scanning sub-functional entities, data packet analysis sub-functional entities,
Data preextraction sub-functional entities, data pre-converted sub-functional entities, data package operation perform sub-functional entities respectively by one
Or multiple corresponding first engines, realizing, first engine is the basic element of character for realizing a certain specific function.
On the basis of above-mentioned technical proposal, the packet scanning sub-functional entities are by a packet scanning unit engine
Packet scan function is implemented separately, or first engine cooperative achievement packet scan function is scanned by multiple packets；
Data packet analysis sub-functional entities are implemented separately data packet analysis function by a packet analysis elements engine, or by
Multiple data packet analysis units engine cooperative achievement data packet analysis function；
Data preextraction sub-functional entities are implemented separately data pre-fetching feature by data preextraction unit engine, or by
Multiple data preextraction units engine cooperative achievement data pre-fetching feature；
Data pre-converted sub-functional entities are implemented separately data pre-converted function by data pre-converted unit engine, or by
Multiple data pre-converted units engine cooperative achievement data pre-converted function；
Data package operation performs sub-functional entities and data package operation is implemented separately by a data package operation execution unit engine
Perform function, or perform first engine cooperative achievement data package operation perform function by multiple data package operations.
On the basis of above-mentioned technical proposal, packet scanning sub-functional entities, data packet analysis sub-functional entities,
Data preextraction sub-functional entities, data pre-converted sub-functional entities, data package operation perform first engine number of sub-functional entities
Amount determines by the hardware and software resource distribution situation inside deep-packet detection system, the corresponding first engine quantity of each sub-functional entities
It is identical or different.
On the basis of above-mentioned technical proposal, inhomogeneous first engine is according to streamline serial operation, similar first engine
Work according to parallel, serial or hybrid mode, determined according to configuration information.
On the basis of above-mentioned technical proposal, the multiple first engine in same sub-functional entities is according to parallel, serial
Or mixed mode work, different multiple first engines in a sub-functional entities are according to serial mode work.
The present invention also provides a kind of deep packet inspection method towards big data for being applied to above-mentioned deep-packet detection system,
Comprise the following steps：
S1, deep-packet detection system obtain the demand that given big data is gathered and changed；
The demand is converted into the configuration information of system for S2, deep-packet detection system；
Configuration information is assigned packet scan function fructification, data packet analysis function by S3, deep-packet detection system
In entity, data pre-fetching feature fructification, data pre-converted function fructification, data package operation perform function fructification；
S4, packet scan function fructification, data packet analysis function fructification, data pre-fetching feature fructification, number
According to pre-converted function fructification, data package operation perform function fructification decomposition function, and it is assigned in corresponding first engine；
The all first engine collaboration for having obtained configuration in S5, deep-packet detection system completes the demand.
Compared with prior art, advantages of the present invention is as follows：
The core component of the deep-packet detection system of the present invention is deep-packet detection engine, and it is based on deep-packet detection strategy
Rule base realizing deep-packet detection function, deep-packet detection engine by packet scanning, data packet analysis, data preextraction,
The sub-functional entities compositions such as data pre-converted, the execution of data package operation, meanwhile, above-mentioned five kinds of sub-functional entities are by corresponding unit
Engine is realizing.Specifically, deep-packet detection engine includes one or more the first engine of packet scanning, one or more numbers
According to bag analysis elements engine, one or more data preextraction unit engines, one or more data pre-converted unit's engines and one
Or multiple data package operations perform first engine.The deep packet inspection method of the present invention is comprised the following steps：Deep-packet detection system
Obtain big data collection and the demand changed；The demand is converted into configuration information by deep-packet detection system；Under configuration information
Up in the function fructifications such as packet scanning, data packet analysis, data preextraction, data pre-converted, the execution of data package operation；On
State function fructification decomposition function and be assigned in corresponding first engine；All units for having obtained configuration in deep-packet detection system
Engine collaboration completes the demand.Framework of the present invention based on big data analytical technology, with reference to the advantage of deep packet inspection technical,
So that deep packet inspection technical plays the part of prior role in big data collection, traditional deep-packet detection can not only be realized
Function, while the big data that can as needed realize part is extracted and translation function, subtracts for big data upper layer techniques and application
Light burden, can significantly improve the real-time and efficiency of big data correlation technique.
Description of the drawings
Fig. 1 be in the embodiment of the present invention towards big data deep-packet detection system structured flowchart.
Fig. 2 is the illustrative view of functional configuration of typical big data analysis system.
Fig. 3 is the work in series schematic diagram of the multiple similar first engines of deep-packet detection system in the embodiment of the present invention.
Fig. 4 is the concurrent working schematic diagram of the multiple similar first engines of deep-packet detection system in the embodiment of the present invention.
Fig. 5 is the mixed mode of operation schematic diagram of the multiple similar first engines of deep-packet detection system in the embodiment of the present invention.
Fig. 6 be in the embodiment of the present invention towards big data deep packet inspection method flow chart.
Fig. 7 is the deep-packet detection system in the embodiment of the present invention towards big data and big data Analysis server and control
Or the relation schematic diagram of management server.
Specific embodiment
Below in conjunction with the accompanying drawings and specific embodiment the present invention is described in further detail.
Shown in Figure 1, the embodiment of the present invention provides a kind of deep-packet detection system towards big data, the deep packet inspection
The core component of examining system is deep-packet detection engine, and it realizes deep-packet detection work(based on deep-packet detection policing rule storehouse
Can, deep-packet detection engine includes packet scanning sub-functional entities, data packet analysis sub-functional entities, the sub- work(of data preextraction
Energy entity, data pre-converted sub-functional entities, data package operation perform sub-functional entities, wherein：
Packet scanning sub-functional entities are used for the Preliminary detection of the packet for completing to enter deep-packet detection system；
Data packet analysis sub-functional entities are used for the fundamental analysis of the packet for completing to enter deep-packet detection system；
Data preextraction sub-functional entities are used to realize the data preextraction for big data demand, above-mentioned data preextraction
Function can need according to application and the resource situation of deep-packet detection system is configured, it can the data of big data extract
All or part of function.
Data pre-converted sub-functional entities are used to realize the data pre-converted for big data demand, equally, above-mentioned data
Pre-converted function can need according to application and the resource situation of deep-packet detection system is configured, and the data after conversion can be more square
Just for big data upper layer techniques and application memory, process and use.
Data package operation performs sub-functional entities to be used to realize the final operation to the packet into system.
It is pre- that data preextraction sub-functional entities and data pre-converted sub-functional entities can be configured to bypass condition, i.e. data
Extracting sub-functional entities, the corresponding function of data pre-converted sub-functional entities can not perform, to realize the embodiment of the present invention in
Deep-packet detection system is compatible with conventional depth bag detecting system.
Fig. 2 is the exemplary functions structural representation of big data system.Figure it is seen that big data system starts from data
Collect, also needed to extract cleaning before into database and change, respectively by data preextraction sub-functional entities, data pre-converted
Sub-functional entities are partially or completely realized.
Packet scanning sub-functional entities, data packet analysis sub-functional entities, data preextraction sub-functional entities, data are pre-
Conversion sub-functional entities, data package operation perform sub-functional entities and are realized by one or more corresponding first engines respectively, unit
Engine is the basic element of character for realizing a certain specific function.
Packet scans sub-functional entities and is implemented separately packet scan function by the first engine of packet scanning, or by
Multiple packet scanning unit engine cooperative achievement packet scan functions.
Data packet analysis sub-functional entities are implemented separately data packet analysis function by a packet analysis elements engine, or by
Multiple data packet analysis units engine cooperative achievement data packet analysis function.
Data preextraction sub-functional entities are implemented separately data pre-fetching feature by data preextraction unit engine, or by
Multiple data preextraction units engine cooperative achievement data pre-fetching feature.
Data pre-converted sub-functional entities are implemented separately data pre-converted function by data pre-converted unit engine, or by
Multiple data pre-converted units engine cooperative achievement data pre-converted function.
Data package operation performs sub-functional entities and data package operation is implemented separately by a data package operation execution unit engine
Perform function, or perform first engine cooperative achievement data package operation perform function by multiple data package operations.
Packet scanning sub-functional entities, data packet analysis sub-functional entities, data preextraction sub-functional entities, data are pre-
Conversion sub-functional entities, data package operation perform sub-functional entities first engine quantity by inside deep-packet detection system it is hard,
Software resource configuring condition determines that the corresponding first engine quantity of each sub-functional entities can be with identical, it is also possible to different.
If class unit engine has multiple, the function of multiple similar first engine implementations can be with identical, it is also possible to differs.Such as
The function phase of really multiple similar first engine implementations is same, then the input of multiple similar first engines should be differed (to realize reliability
Except the redundancy of design), to ensure the resource utilization of first engine.
It is similar if arbitrary sub-functional entities include multiple first engines, then this multiple first engine first engine similar each other
The function of first engine implementation is not identical, and for example, data preextraction sub-functional entities have the first engines of A, B, C tri-, A, B, C
There can be identical design, for processing different packets；A, B, C can also be designed to different, process respectively
The different piece of same packet.Similar first engine can have various execution relations, respectively serial, parallel and hybrid mode.
Inhomogeneous first engine is according to streamline serial operation.Similar first engine can be according to parallel, serial or mixing
Mode works, and this determines according to configuration information.Packet scanning sub-functional entities, data packet analysis sub-functional entities, data are pre-
Extract sub-functional entities, data pre-converted sub-functional entities, the corresponding function of data package operation execution sub-functional entities to go here and there successively
Row is performed.
Multiple first engine in same sub-functional entities can work according to parallel, serial or mixed mode.Difference exists
Multiple first engine in one sub-functional entities works according to serial mode.
Fig. 3, Fig. 4, Fig. 5 describe respectively above-mentioned serial, parallel and hybrid mode.Above-mentioned three kinds of modes can be according to deep packet
The resource situation and conditions of demand of detecting system is selected.
Packet scanning sub-functional entities, data packet analysis sub-functional entities, data preextraction sub-functional entities, data are pre-
Conversion sub-functional entities, data package operation perform first engine of sub-functional entities and can configure and dispatch according to demand, for
One specific demand, is not required to the realization that all of first engine is involved in the demand.
Each sub-functional entities in the embodiment of the present invention realize corresponding function based on corresponding first engine.First engine is
The basic element of character of a certain function is realized, can be the hardware resource being logically independent, such as polycaryon processor a core (CORE),
Can also be the software resource being logically independent, such as a process on same server.
Respectively corresponding data bag scans sub-functional entities, data packet analysis sub-functional entities, data preextraction subfunction reality
It is foreign peoples unit engine that body, data pre-converted sub-functional entities, data package operation perform first engine of sub-functional entities, and foreign peoples unit draws
Hold up and perform in a serial fashion.
It is shown in Figure 6, the embodiment of the present invention also provide it is a kind of be applied to above-mentioned deep-packet detection system towards big number
According to deep packet inspection method, comprise the following steps：
S1, deep-packet detection system obtain the demand that given big data is gathered and changed, and the demand is based on whole big
Depending on the function and performance of data analysis system and the resource of deep-packet detection system.On the one hand, the demand can be deep
The resource of degree bag detecting system is supported that another aspect realizes that the demand can improve the function of whole big data analysis system
And performance.
Shown in Figure 7, deep-packet detection system occurs with corresponding control or management server and big data system
Contact, this is a most simplified model, and network is increasingly complex during practical application.Therefore, the demand can come from control
Or management server, it is also possible to arise directly from big data system.
It should be noted that the demand is the function and performance based on whole big data analysis system and deep packet inspection
Depending on the resource of examining system.On the one hand, the demand can support by the resource of deep-packet detection system, on the other hand,
Realize that the demand can improve the function and performance of whole big data analysis system.
The demand is converted into the configuration information of system for S2, deep-packet detection system.
Demand needs the communication protocol for following deep-packet detection system and outside outside deep-packet detection system.But
The configuration information of deep-packet detection system then depends on the situation of system resource, needs mapping, this step to realize reflecting between the two
Penetrate function.
Configuration information is assigned packet scan function fructification, data packet analysis function by S3, deep-packet detection system
In entity, data pre-fetching feature fructification, data pre-converted function fructification, data package operation perform function fructification.
S4, packet scan function fructification, data packet analysis function fructification, data pre-fetching feature fructification, number
According to pre-converted function fructification, data package operation perform function fructification decomposition function, and it is assigned in corresponding first engine.
Deep-packet detection system needs the situation based on each sub-functional entities of system, and configuration information is decomposed so that point
Configuration information after solution can be received by each sub-functional entities, and corresponding function can also be realized by each sub-functional entities.
First engine is the basic element of character of demand of realizing, therefore, final function all should be implemented in specific unit's engine.No
Same design, the configuring condition difference of first engine can be very big.And, realize that a certain demand is also not necessarily required to all first engines
Participate in, accordingly, it would be desirable to clearly information carrys out the corresponding unit's engine of configuration schedules.
The all first engine collaboration for having obtained configuration in S5, deep-packet detection system completes the demand.
Above-mentioned five steps are to realize the key step of the method for the present invention, and the details that implements of each step is relied on
In specific design, different designs can have larger difference.
Those skilled in the art can carry out various modifications and variations to the embodiment of the present invention, if these modifications and change
Within the scope of the claims in the present invention and its equivalent technologies, then these modifications and modification are also in protection scope of the present invention for type
Within.
The prior art that the content not described in detail in specification is known to the skilled person.
Claims (8)
1. a kind of deep-packet detection system towards big data, it is characterised in that：The core component of the deep-packet detection system is
Deep-packet detection engine, it realizes deep-packet detection function, deep-packet detection engine based on deep-packet detection policing rule storehouse
Including packet scanning sub-functional entities, data packet analysis sub-functional entities, data preextraction sub-functional entities, data pre-converted
Sub-functional entities, data package operation perform sub-functional entities, wherein：
Packet scanning sub-functional entities are used for the Preliminary detection of the packet for completing to enter deep-packet detection system；
Data packet analysis sub-functional entities are used for the fundamental analysis of the packet for completing to enter deep-packet detection system；
Data preextraction sub-functional entities are used to realize the data preextraction for big data demand；
Data pre-converted sub-functional entities are used to realize the data pre-converted for big data demand；
Data package operation performs sub-functional entities to be used to realize the final operation to the packet into system.
2. as claimed in claim 1 towards the deep-packet detection system of big data, it is characterised in that：Data preextraction
Functional entity and data pre-converted sub-functional entities are configured to bypass condition, to realize the deep-packet detection system and tradition depth
The compatibility of degree bag detecting system.
3. as claimed in claim 1 towards the deep-packet detection system of big data, it is characterised in that：Packet scanning
Functional entity, data packet analysis sub-functional entities, data preextraction sub-functional entities, data pre-converted sub-functional entities, data
Package operation performs sub-functional entities and is realized by one or more corresponding first engines respectively, and first engine is a certain specific to realize
The basic element of character of function.
4. as claimed in claim 3 towards the deep-packet detection system of big data, it is characterised in that：Packet scanning
Functional entity is implemented separately packet scan function by a packet scanning unit engine, or scans first engine by multiple packets
Cooperative achievement packet scan function；
Data packet analysis sub-functional entities are implemented separately data packet analysis function by a packet analysis elements engine, or by multiple
Data packet analysis unit engine cooperative achievement data packet analysis function；
Data preextraction sub-functional entities are implemented separately data pre-fetching feature by a data preextraction unit engine, or by multiple
Data preextraction unit engine cooperative achievement data pre-fetching feature；
Data pre-converted sub-functional entities are implemented separately data pre-converted function by a data pre-converted unit engine, or by multiple
Data pre-converted unit engine cooperative achievement data pre-converted function；
Data package operation performs sub-functional entities and the execution of data package operation is implemented separately by a data package operation execution unit engine
Function, or perform first engine cooperative achievement data package operation perform function by multiple data package operations.
5. as claimed in claim 3 towards the deep-packet detection system of big data, it is characterised in that：Packet scanning
Functional entity, data packet analysis sub-functional entities, data preextraction sub-functional entities, data pre-converted sub-functional entities, data
Package operation performs first engine quantity of sub-functional entities and is determined by the hardware and software resource distribution situation inside deep-packet detection system
Calmly, the corresponding first engine quantity of each sub-functional entities is identical, or different.
6. as claimed in claim 3 towards the deep-packet detection system of big data, it is characterised in that：Inhomogeneous first engine is pressed
According to streamline serial operation, similar first engine works according to parallel, serial or hybrid mode, is determined according to configuration information.
7. as claimed in claim 3 towards the deep-packet detection system of big data, it is characterised in that：In same subfunction reality
Internal multiple first engine works according to parallel, serial or mixed mode, and different multiple units in a sub-functional entities draw
Hold up and worked according to serial mode.
8. a kind of deep packet inspection method towards big data for being applied to deep-packet detection system described in claim 1, it is special
Levy and be, comprise the following steps：
S1, deep-packet detection system obtain the demand that given big data is gathered and changed；
The demand is converted into the configuration information of system for S2, deep-packet detection system；
S3, deep-packet detection system by configuration information assign packet scan function fructification, data packet analysis function fructification,
In data pre-fetching feature fructification, data pre-converted function fructification, data package operation perform function fructification；
S4, packet scan function fructification, data packet analysis function fructification, data pre-fetching feature fructification, data are pre-
Translation function fructification, data package operation perform function fructification decomposition function, and be assigned in corresponding first engine；
The all first engine collaboration for having obtained configuration in S5, deep-packet detection system completes the demand.
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Application publication date: 20170510 |