CN111814183A - Financial real-time wind control system and method based on network layer message analysis - Google Patents
Financial real-time wind control system and method based on network layer message analysis Download PDFInfo
- Publication number
- CN111814183A CN111814183A CN202010641179.4A CN202010641179A CN111814183A CN 111814183 A CN111814183 A CN 111814183A CN 202010641179 A CN202010641179 A CN 202010641179A CN 111814183 A CN111814183 A CN 111814183A
- Authority
- CN
- China
- Prior art keywords
- message
- early warning
- module
- analysis
- rule
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 59
- 238000000034 method Methods 0.000 title claims abstract description 15
- 238000012545 processing Methods 0.000 claims abstract description 82
- 238000001914 filtration Methods 0.000 claims description 18
- 238000000586 desensitisation Methods 0.000 claims description 9
- 238000010801 machine learning Methods 0.000 claims description 7
- 238000012216 screening Methods 0.000 claims description 7
- 238000012549 training Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 4
- 230000009286 beneficial effect Effects 0.000 abstract description 5
- 238000012954 risk control Methods 0.000 abstract description 5
- 238000004891 communication Methods 0.000 description 7
- 230000002159 abnormal effect Effects 0.000 description 4
- 238000013461 design Methods 0.000 description 3
- 230000008520 organization Effects 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000010079 rubber tapping Methods 0.000 description 2
- 102100026278 Cysteine sulfinic acid decarboxylase Human genes 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 108010064775 protein C activator peptide Proteins 0.000 description 1
- 239000000344 soap Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Classifications
-
- 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
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
-
- 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
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
- G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
- G06F21/6254—Protecting personal data, e.g. for financial or medical purposes by anonymising data, e.g. decorrelating personal data from the owner's identification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/22—Parsing or analysis of headers
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Computer Security & Cryptography (AREA)
- Health & Medical Sciences (AREA)
- Bioethics (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Medical Informatics (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Signal Processing (AREA)
- Game Theory and Decision Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Computer And Data Communications (AREA)
Abstract
The invention discloses a financial real-time wind control system and method based on network layer message analysis, wherein the system comprises a network layer message analysis subsystem and a financial wind control subsystem; the network message analysis subsystem comprises: the system comprises a message acquisition module, a message distribution module, a message processing module and a rule server; the financial real-time wind control subsystem comprises: the index processing module is used for carrying out index processing on the message from the message processing module according to a preset message processing rule to obtain index information corresponding to the message; the early warning analysis module is used for carrying out early warning analysis on the message index information obtained by analysis, judging whether early warning is needed or not, and pushing an early warning instruction to the real-time early warning module when early warning is needed; and the real-time early warning module carries out risk early warning when receiving the early warning instruction. The invention compresses the time consumption from the network layer to the application layer, is beneficial to the financial wind control subsystem to acquire data in time for analysis and risk control early warning, and further reduces the risk of the financial system.
Description
Technical Field
The invention relates to the field of financial wind control, in particular to a financial real-time wind control system and method based on network layer message analysis.
Background
Real-time application of big data is increasing, and the application of big data comprises fields such as real-time wind control, customer discovery, accurate marketing, business monitoring. How to improve the real-time aging as much as possible and complete the calculation and analysis within the range of milliseconds is a concern. At present, most of real-time calculation is based on application processing, including real-time extraction from a database of a service system, database synchronization technology such as DSG/OGG, and the like, or log synchronization technology, which are all realized at an application layer. The transition from the network layer to the application layer is still time consuming.
In the financial wind control field, the requirement on time is stricter, and if information acquisition cannot be carried out in time, risk control early warning cannot be carried out in time, so that the risk of a financial system can be increased.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a financial real-time wind control system and method based on network layer message analysis, which compress the time consumption from a network layer to an application layer, perform index processing, early warning analysis and risk control early warning based on the processed messages, are beneficial to timely or abnormal conditions in a financial system, and reduce the risk of the financial system.
The purpose of the invention is realized by the following technical scheme: a financial real-time wind control system based on network layer message analysis comprises a network layer message analysis subsystem and a financial wind control subsystem;
the network message analysis subsystem comprises:
the message acquisition module is used for collecting link layer data packets from a network equipment driving program, filtering the collected data packets according to a predefined rule, and transmitting the filtered data to the message distribution module;
the message distribution module screens and filters the messages needing to be applied in a white list configuration definition mode and then distributes and processes the messages;
the message processing module is used for performing distributed processing on the message data from the message distribution module, sequentially completing message protocol identification, message type identification, protocol distribution, message analysis, message pairing, message encryption and decryption, message desensitization and message assembly on the message data, and transmitting the assembled message to the financial wind control subsystem;
the rule server is used for configuring corresponding data processing rules for the message acquisition module and the message processing module;
the financial real-time wind control subsystem comprises:
the index processing module is used for carrying out index processing on each message from the message processing module according to a preset message processing rule to obtain index information corresponding to the message;
the early warning analysis module is used for carrying out early warning analysis on the message index information obtained by analysis, judging whether early warning is needed or not, and pushing an early warning instruction to the real-time early warning module when the early warning is needed;
and the real-time early warning module is used for carrying out risk early warning when the early warning instruction is received.
A financial real-time wind control method based on network layer message analysis comprises the following steps:
s1, pre-configuring a screening filtering rule, an encryption and decryption rule, an association rule and a replacement rule in a rule server;
s2, collecting link layer data packets from a network equipment driving program by using a message acquisition module, filtering the collected data packets according to a predefined rule, and transmitting the filtered data to a message distribution module;
s3, the message distribution module utilizes the screening and filtering rules in the rule server to screen and filter the data from the message distribution module to obtain the message to be applied, and then the message is distributed;
s4, the message processing module performs distributed processing on the message data from the message distribution module, and sequentially completes message protocol identification, message type identification, protocol distribution, message analysis, message pairing, message encryption and decryption, message desensitization and message assembly on the message data;
s5, the index processing module performs index processing on each message output by the message processing module according to a preset message processing rule to obtain index information corresponding to the message;
s6, the early warning analysis module carries out early warning analysis on the message index information obtained by analysis, judges whether early warning is needed or not, and pushes an early warning instruction to the real-time early warning module when the early warning is needed;
and S7, the real-time early warning module carries out risk early warning when receiving the early warning instruction.
The invention has the beneficial effects that: the invention directly analyzes and recombines the needed service message and index from the communication message, compresses the time consumption from the network layer to the application layer, applies the distributed processing design and the concurrent processing, further compresses the message processing time, and carries out index processing, early warning analysis and risk control early warning based on the processed message, thereby being beneficial to timely or abnormal conditions in the financial system and reducing the risk of the financial system.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
As shown in fig. 1, a financial real-time wind control system based on network layer message parsing includes a network layer message parsing subsystem and a financial wind control subsystem;
the network message analysis subsystem comprises:
the message acquisition module is used for collecting link layer data packets from a network equipment driving program, filtering the collected data packets according to a predefined rule, and transmitting the filtered data to the message distribution module;
in the embodiment of the application, the message acquisition module acquires a message by adopting a PCAP packet capturing and comprises a network tapping unit and a BPF filter; the network tapping unit is used for adding a bypass process in a data link layer, obtaining a copy of a data packet from a link layer driver by using a created Socket when the data packet reaches a network interface, and sending the data packet to the BPF filter through a Tap function; the BPF filter is used for matching the data packets one by one according to the predefined filtering rule, if the matching is successful, the data packets are put into a kernel buffer area and transmitted to the message distribution module, and if the matching is failed, the data packets are directly discarded.
The message distribution module screens and filters the messages needing to be applied in a white list configuration definition mode and then distributes and processes the messages;
in an embodiment of the present application, the message distribution module includes: the white list filtering unit is used for screening and filtering the data output by the message acquisition module in a white list configuration mode to obtain a required application message; the task distribution unit is used for distributing and processing the message: and (4) taking two factors of importance and urgency and weight design into consideration, and carrying out hash distribution on the whole message to be sent by using a hash algorithm on the premise of meeting the application importance and urgency.
The message processing module is used for performing distributed processing on the message data from the message distribution module, sequentially completing message protocol identification, message type identification, protocol distribution, message analysis, message pairing, message encryption and decryption, message desensitization and message assembly on the message data, and transmitting the assembled message to the financial wind control subsystem;
in an embodiment of the present application, the message processing module includes: the protocol identification unit is used for identifying a communication protocol of the received message, wherein the communication protocol comprises a TCP (transmission control protocol), a UDP (user datagram protocol), an HTTP (hyper text transport protocol) or an HTTPS (hypertext transfer protocol); the type identification unit is used for identifying an organization structure of message contents of the received message, wherein the organization structure comprises ISO8583, Json, XML, SOP or SOAP; the protocol shunting unit is used for constructing a message interface specification knowledge base and constructing the message interface specification of the known message in the knowledge base according to the format; according to the identified message communication protocol and message type, searching a corresponding message interface standard format in a message interface standard knowledge base, so that message with different formats are subjected to shunting operation; the protocol analysis unit is used for constructing analyzers corresponding to different message interface standard formats, loading the corresponding analyzers according to the message interface standard formats after receiving the shunted messages, and analyzing the content of the attribute information of each domain of the messages to obtain structured message data, wherein the attribute information comprises domain names, domain data types and domain lengths; the message pairing unit is used for matching the associated request and response messages in the structured message data into pairs; the message encryption and decryption unit is used for connecting the encryption machine to carry out encryption and decryption operations on key domains in the matched pair of messages; the message desensitization unit is used for desensitizing sensitive information in the encrypted and decrypted message; and the message assembling unit is used for assembling the desensitized structured messages into a new message data packet.
The rule server is used for configuring corresponding data processing rules for the message acquisition module and the message processing module;
in an embodiment of the application, the rule server includes: a filtering rule configuration unit, configured to configure a filtering rule for the message distribution module, where the filtering rule includes a white list configuration; the encryption and decryption rule configuration unit is used for configuring encryption and decryption rules for the data processing module so that the data processing module can carry out encryption and decryption operations according to the configuration rules; the management rule configuration unit is used for configuring association rules of the request and the response messages so as to facilitate the data processing module to carry out message pairing; the replacement rule configuration unit is used for configuring the sensitive information and the corresponding replacement rule so as to be convenient for the data processing module to determine the sensitive information in the message when carrying out desensitization processing and replace the sensitive information by using the corresponding replacement rule so as to realize desensitization processing;
the financial real-time wind control subsystem comprises:
the index processing module is used for carrying out index processing on each message from the message processing module according to a preset message processing rule to obtain index information corresponding to the message;
the early warning analysis module is used for carrying out early warning analysis on the message index information obtained by analysis, judging whether early warning is needed or not, and pushing an early warning instruction to the real-time early warning module when the early warning is needed;
and the real-time early warning module is used for carrying out risk early warning when the early warning instruction is received.
In an embodiment of the application, the network message parsing subsystem further includes a message storage module, configured to store a message obtained by processing by the message processing module.
The index processing module includes:
the rule setting unit is used for setting a message processing rule for processing the message to obtain index information corresponding to the message;
and the index processing unit is used for performing index processing on each message from the message processing module according to the set message processing rule to obtain index information corresponding to the message.
The early warning analysis module comprises one of an early warning rule analysis unit or a machine learning classification unit;
the early warning rule analysis unit is used for setting an early warning analysis rule of an index, analyzing the index information of the message according to the set early warning analysis rule, judging whether early warning is needed or not, and generating an early warning instruction to push the early warning instruction to the real-time early warning module when the early warning is needed;
and the machine learning classification unit is used for training an early warning classifier for obtaining index information by utilizing a machine learning mode, sending the index information of the message into the early warning classifier obtained by training, judging whether early warning is needed or not according to output information of the classifier, and generating an early warning instruction to push the early warning instruction to the real-time early warning module when early warning is needed.
When the early warning classifier of index information is trained in a machine learning mode, firstly, a large amount of message index information needs to be collected, each piece of message index information is manually marked to form a training set of the early warning classifier, wherein the mark is generally '0' or '1', and respectively represents 'normal (no early warning needed)' or 'abnormal (early warning needed)', then each piece of message index information in the training set is used as the input of the early warning classifier, and the mark corresponding to the index information is used as the output of the early warning classifier to train the early warning classifier; after training is finished, the method can be used for classifying message index information: for example, the message index information to be analyzed is input into the classifier, if the classifier outputs 0, no early warning is needed, if the classifier outputs 1, early warning is needed, and at this time, an early warning instruction is generated and pushed to the real-time early warning module.
In the embodiment of the application, the early warning mode of the real-time early warning module comprises one or more of short message early warning notification, mail early warning notification and on-site early warning notification.
As shown in fig. 2, a financial real-time wind control method based on network layer message parsing includes the following steps:
s1, pre-configuring a screening filtering rule, an encryption and decryption rule, an association rule and a replacement rule in a rule server;
s2, collecting link layer data packets from a network equipment driving program by using a message acquisition module, filtering the collected data packets according to a predefined rule, and transmitting the filtered data to a message distribution module;
s3, the message distribution module utilizes the screening and filtering rules in the rule server to screen and filter the data from the message distribution module to obtain the message to be applied, and then the message is distributed;
s4, the message processing module performs distributed processing on the message data from the message distribution module, and completes message protocol identification, message type identification, protocol distribution, message analysis, message pairing, message encryption and decryption, message desensitization and message assembly on the message data in sequence, specifically:
carrying out communication protocol identification on the received message;
carrying out message content organization structure identification on the received message;
constructing a knowledge base of message interface specifications, and constructing the message interface specifications of known messages in the knowledge base according to formats; according to the identified message communication protocol and message type, searching a corresponding message interface standard format in a message interface standard knowledge base, so that message with different formats are subjected to shunting operation;
building resolvers corresponding to different message interface standard formats, loading the corresponding resolvers according to the message interface standard formats after receiving the shunted messages, and carrying out content resolution on attribute information of each domain of the messages to obtain structured message data;
matching the associated request and response messages in the structured message data into pairs according to the association rule in the rule server;
connecting an encryption machine to perform encryption and decryption operations on key domains in the matched pair of messages according to encryption and decryption rules in the rule server;
desensitizing the sensitive information in the encrypted and decrypted message according to the sensitive information in the rule server and the corresponding replacement rule;
and assembling the desensitized structured messages into a new message data packet.
S5, the index processing module performs index processing on each message output by the message processing module according to a preset message processing rule to obtain index information corresponding to the message;
s6, the early warning analysis module carries out early warning analysis on the message index information obtained by analysis, judges whether early warning is needed or not, and pushes an early warning instruction to the real-time early warning module when the early warning is needed;
and S7, the real-time early warning module carries out risk early warning when receiving the early warning instruction.
In summary, the invention directly analyzes and recombines the required service message and index from the communication message, compresses the time consumption from the network layer to the application layer, applies the distributed processing design and the concurrent processing, further compresses the message processing time, and carries out index processing, early warning analysis and risk control early warning based on the processed message, thereby being beneficial to timely or abnormal conditions in the financial system and reducing the risk of the financial system.
The foregoing is a preferred embodiment of the present invention, it is to be understood that the invention is not limited to the form disclosed herein, but is not to be construed as excluding other embodiments, and is capable of other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A financial real-time wind control system based on network layer message parsing is characterized in that: the system comprises a network layer message analysis subsystem and a financial wind control subsystem;
the network message analysis subsystem comprises:
the message acquisition module is used for collecting link layer data packets from a network equipment driving program, filtering the collected data packets according to a predefined rule, and transmitting the filtered data to the message distribution module;
the message distribution module screens and filters the messages needing to be applied in a white list configuration definition mode and then distributes and processes the messages;
the message processing module is used for performing distributed processing on the message data from the message distribution module, sequentially completing message protocol identification, message type identification, protocol distribution, message analysis, message pairing, message encryption and decryption, message desensitization and message assembly on the message data, and transmitting the assembled message to the financial wind control subsystem;
the rule server is used for configuring corresponding data processing rules for the message acquisition module and the message processing module;
the financial real-time wind control subsystem comprises:
the index processing module is used for carrying out index processing on each message from the message processing module according to a preset message processing rule to obtain index information corresponding to the message;
the early warning analysis module is used for carrying out early warning analysis on the message index information obtained by analysis, judging whether early warning is needed or not, and pushing an early warning instruction to the real-time early warning module when the early warning is needed;
and the real-time early warning module is used for carrying out risk early warning when the early warning instruction is received.
2. The financial real-time wind control system based on network layer message parsing according to claim 1, characterized in that: the network message analysis subsystem also comprises a message storage module used for storing the message processed by the message processing module.
3. The financial real-time wind control system based on network layer message parsing according to claim 1, characterized in that: the index processing module includes:
the rule setting unit is used for setting a message processing rule for processing the message to obtain index information corresponding to the message;
and the index processing unit is used for performing index processing on each message from the message processing module according to the set message processing rule to obtain index information corresponding to the message.
4. The financial real-time wind control system based on network layer message parsing according to claim 1, characterized in that: the early warning analysis module comprises one of an early warning rule analysis unit or a machine learning classification unit;
the early warning rule analysis unit is used for setting an early warning analysis rule of an index, analyzing the index information of the message according to the set early warning analysis rule, judging whether early warning is needed or not, and generating an early warning instruction to push the early warning instruction to the real-time early warning module when the early warning is needed;
and the machine learning classification unit is used for training an early warning classifier for obtaining index information by utilizing a machine learning mode, sending the index information of the message into the early warning classifier obtained by training, judging whether early warning is needed or not according to output information of the classifier, and generating an early warning instruction to push the early warning instruction to the real-time early warning module when early warning is needed.
5. The financial real-time wind control system based on network layer message parsing according to claim 1, characterized in that: the early warning mode of the real-time early warning module comprises one or more of short message early warning notice, mail early warning notice and on-site early warning notice.
6. A financial real-time wind control method based on network layer message analysis, which adopts the system of any one of claims 1-5, and is characterized in that: the method comprises the following steps:
s1, pre-configuring a screening filtering rule, an encryption and decryption rule, an association rule and a replacement rule in a rule server;
s2, collecting link layer data packets from a network equipment driving program by using a message acquisition module, filtering the collected data packets according to a predefined rule, and transmitting the filtered data to a message distribution module;
s3, the message distribution module utilizes the screening and filtering rules in the rule server to screen and filter the data from the message distribution module to obtain the message to be applied, and then the message is distributed;
s4, the message processing module performs distributed processing on the message data from the message distribution module, and sequentially completes message protocol identification, message type identification, protocol distribution, message analysis, message pairing, message encryption and decryption, message desensitization and message assembly on the message data;
s5, the index processing module performs index processing on each message output by the message processing module according to a preset message processing rule to obtain index information corresponding to the message;
s6, the early warning analysis module carries out early warning analysis on the message index information obtained by analysis, judges whether early warning is needed or not, and pushes an early warning instruction to the real-time early warning module when the early warning is needed;
and S7, the real-time early warning module carries out risk early warning when receiving the early warning instruction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010641179.4A CN111814183A (en) | 2020-07-06 | 2020-07-06 | Financial real-time wind control system and method based on network layer message analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010641179.4A CN111814183A (en) | 2020-07-06 | 2020-07-06 | Financial real-time wind control system and method based on network layer message analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111814183A true CN111814183A (en) | 2020-10-23 |
Family
ID=72841634
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010641179.4A Pending CN111814183A (en) | 2020-07-06 | 2020-07-06 | Financial real-time wind control system and method based on network layer message analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111814183A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546217A (en) * | 2010-12-31 | 2012-07-04 | 上海可鲁系统软件有限公司 | Message filtering method |
| CN104636237A (en) * | 2015-01-19 | 2015-05-20 | 上海新炬网络信息技术有限公司 | Monitoring method for Web application system service performance based on Java platform |
| CN105515180A (en) * | 2015-07-14 | 2016-04-20 | 国家电网公司 | Intelligent substation communication network dynamic monitoring system and monitoring method thereof |
| CN110401624A (en) * | 2018-04-25 | 2019-11-01 | 全球能源互联网研究院有限公司 | The detection method and system of source net G system mutual message exception |
-
2020
- 2020-07-06 CN CN202010641179.4A patent/CN111814183A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546217A (en) * | 2010-12-31 | 2012-07-04 | 上海可鲁系统软件有限公司 | Message filtering method |
| CN104636237A (en) * | 2015-01-19 | 2015-05-20 | 上海新炬网络信息技术有限公司 | Monitoring method for Web application system service performance based on Java platform |
| CN105515180A (en) * | 2015-07-14 | 2016-04-20 | 国家电网公司 | Intelligent substation communication network dynamic monitoring system and monitoring method thereof |
| CN110401624A (en) * | 2018-04-25 | 2019-11-01 | 全球能源互联网研究院有限公司 | The detection method and system of source net G system mutual message exception |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8819807B2 (en) | Apparatus and method for analyzing and monitoring sap application traffic, and information protection system using the same | |
| US9392003B2 (en) | Internet security cyber threat reporting system and method | |
| CN111818041B (en) | Real-time message processing system and method based on network layer message analysis | |
| CN105930363B (en) | HTML5 webpage-based user behavior analysis method and device | |
| CN109714187A (en) | Log analysis method, device, equipment and storage medium based on machine learning | |
| US9231982B2 (en) | Data transfer for network interaction fraudulence detection | |
| CN113612763B (en) | Network attack detection device and method based on network security malicious behavior knowledge base | |
| CN111222547B (en) | Traffic feature extraction method and system for mobile application | |
| CN110633195B (en) | Performance data display method and device, electronic equipment and storage medium | |
| CN111741007B (en) | Financial business real-time monitoring system and method based on network layer message analysis | |
| CN115695541A (en) | Method, device and equipment for monitoring dot polling based on edge calculation and storage medium | |
| CN114710416B (en) | Network flow real-time data acquisition method based on process flow | |
| CN110727947A (en) | Security vulnerability processing method, device, equipment and readable storage medium | |
| CN102271331A (en) | Method and system for detecting reliability of service provider (SP) site | |
| CN111818154B (en) | Service pushing system and method based on network layer message analysis | |
| CN113112038A (en) | Intelligent monitoring and diagnostic analysis system, device, electronic equipment and storage medium | |
| CN108710691A (en) | Log management method and device | |
| CN111814183A (en) | Financial real-time wind control system and method based on network layer message analysis | |
| US20180083992A1 (en) | Multi-tier aggregation for complex event correlation in streams | |
| CN110989537A (en) | Production data processing method, apparatus, medium, and system | |
| CN114915566B (en) | Application identification method, device, equipment and computer readable storage medium | |
| CN115567563A (en) | Comprehensive transportation hub monitoring and early warning system based on end edge cloud and control method thereof | |
| CN114329450A (en) | Data security processing method, device, equipment and storage medium | |
| CN113052493A (en) | Efficiency monitoring system and working method | |
| CN107295087B (en) | System and method for realizing data aggregation between network systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |