CN111600890A - Network security perception system based on big data - Google Patents
Network security perception system based on big data Download PDFInfo
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- CN111600890A CN111600890A CN202010421601.5A CN202010421601A CN111600890A CN 111600890 A CN111600890 A CN 111600890A CN 202010421601 A CN202010421601 A CN 202010421601A CN 111600890 A CN111600890 A CN 111600890A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0861—Network architectures or network communication protocols for network security for authentication of entities using biometrical features, e.g. fingerprint, retina-scan
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1433—Vulnerability analysis
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- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
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Abstract
The invention discloses a network security sensing system based on big data, which comprises a data acquisition module, a distributed processing module, a cloud computing module, a sensing technology module, a storage counting module, a data protection module, a database missing scanning module, a data asset combing module, a big database application access module and a big data auditing module, wherein the output end of the data acquisition module is connected with the input end of the distributed processing module, the output end of the distributed processing module is connected with the input end of the cloud computing module, the output end of the cloud computing module is connected with the input end of the sensing technology module, the output end of the sensing technology module is connected with the input end of the storage module, the output end of the data protection module is connected with the input end of the big data application access control module, the core technology and privacy of a database are encrypted by the sensing technology in the data asset combing module, the protection of personal information privacy in a big data application scene is strengthened.
Description
Technical Field
The invention relates to the technical field of network security, in particular to a network security perception system based on big data.
Background
The big data era comes, the data scale of each industry is TB-level growth, and enterprises with high-value data sources occupy a vital core position in a big data industry chain. After large data concentration is realized, how to ensure the integrity, availability and confidentiality of network data is not influenced by security threats of information leakage and illegal tampering, and the method becomes a core problem to be considered for informatization and health development of government agencies and public institution.
The network security includes network device security, network information security and network software security, which means that the hardware, software and data in the system of the network system are protected and are not damaged, changed and leaked due to accidental or malicious reasons, the system continuously, reliably and normally operates, and the network service is not interrupted. The system has the characteristics of confidentiality, integrity, availability, controllability and auditability.
The existing network security awareness of big data has the following disadvantages: 1. the centralized security configuration management and security mechanism deployment in the aspect of platform security can basically meet the security requirements of the current platform, and the vulnerability scanning and attack monitoring technology of the large data platform is relatively weak. 2. Data security is relatively mature in data security monitoring and anti-leakage technology, and data sharing security, security protection of unstructured databases and data leakage tracing technology need to be improved. 3. The development of the technology in the aspect of privacy protection obviously cannot meet the current urgent privacy protection requirement, and a technical guarantee system needs to be established for the personal information protection problem in a big data application scene.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a big data-based network security awareness system.
In order to achieve the purpose, the invention adopts the following technical scheme: comprises a data acquisition module, a distributed processing module, a cloud computing module, a perception technology module, a storage counting module, a data protection module, a database missing scanning module, a data asset combing module, a big database application access module and a big data auditing module, the output end of the data acquisition module is connected with the input end of the distributed processing module, the output end of the distributed processing module is connected with the input end of the cloud computing module, the output end of the cloud computing module is connected with the input end of the perception technology module, the output end of the perception technology module is connected with the input end of the storage module, the output end of the data protection is connected with the input end of the big data application access control module, the output end of the data protection is connected with the input end of the big data auditing module, the output end of the data protection is connected with the input end of the database missing scanning module, and the output end of the data protection is connected with the input end of the data asset combing module.
In a preferred embodiment: the output end of the database missing scanning module is connected with the input end of the resource safety vulnerability detection, the input end of the data asset combing module is used for connecting the input end of the sensitive data, the output end of the sensitive data is connected with the input end of the sensitive data, the output end of the data asset combing module is connected with the input end of the database, the output end of the database is connected with the input end of the database encryption, the output end of the database encryption is connected with the input end of the database safety operation and maintenance, the output end of the database safety operation and maintenance is in operation with the prevention of operation and maintenance personnel, and the output end of the database safety operation and maintenance with the large size is connected with the input end of the operation with the prevention of high risk of the operation and.
In a preferred embodiment: the distributed processing module is a computer system which connects a plurality of computers in different places, or with different functions, or with different data through a communication network and coordinately completes large-scale information processing tasks under the unified management control of a control system. The cloud computing module is used for decomposing a huge data computing processing program into countless small programs through a network cloud, then processing and analyzing the small programs through a system consisting of a plurality of servers to obtain results and returning the results to a user, and the cloud computing module is not only distributed computing, but also results of mixed evolution and leap of computer technologies such as distributed computing, utility computing, load balancing, parallel computing, network storage, hot backup, redundancy, virtualization and the like.
In a preferred embodiment: the perception technology module is a technology of face recognition, voice command, eyeball tracking, gesture control and the like. Voice commands and facial recognition are widely used. The big data auditing module forms detailed logs of the operation behaviors of the host and the object, and has the functions of user name, IP, operation, resources, access type, time, authorization result, summary of specific design and new events, risk event, report management, system maintenance, rule management, log retrieval and the like. The data desensitization is to desensitize sensitive information for a large data storage data full table or field, and start data desensitization does not need to read any content of a large data assembly, and only needs to configure a corresponding desensitization strategy.
In a preferred embodiment: the big data application access control module can perform unified management and control and centralized authorization management on the big data platform account. And fine-grained authorization and access control are provided for users and application programs of the large data platform. The resource security vulnerability detection is the periodical vulnerability scanning and baseline detection of the big data platform assembly, and the vulnerability scanning and baseline configuration potential safety hazard of the big data platform are detected; the system comprises functional modules such as risk display, vulnerability detection, report management and a knowledge base. The data asset combing module can automatically identify and classify sensitive data, and enable a sensitive data discovery strategy without changing any content of the big data component.
In a preferred embodiment: the data acquisition module is combined with a computer or other special test platform-based measurement software and hardware products to realize a flexible and user-defined measurement system. The acquisition is generally a sampling mode, that is, the same point data is repeatedly acquired at certain time intervals (called sampling period). The acquired data are mostly instantaneous values, but also characteristic values within a certain period of time.
In a preferred embodiment: when the resource security vulnerability detection is the resource security vulnerability detection, the large data platform component is subjected to periodic vulnerability scanning and baseline detection, the large data platform vulnerability is scanned, potential safety hazards are configured on the baseline, and sensitive data are automatically identified through the data asset combing module during data protection.
In a preferred embodiment: the database is used for encrypting the core technology and the privacy of the database, and the database can be safely operated and maintained, so that operation and maintenance personnel are prevented from being badly operated and high-risk operation of the operation and maintenance personnel is prevented.
The invention has the following beneficial effects:
1. according to the invention, when the data protection detects the security vulnerability of a designated remote or local computer system through means such as scanning of a database vulnerability scanning module, a security detection of available vulnerabilities is found, when resources in a database pass through the resource security vulnerability detection, the large data platform component is subjected to periodic vulnerability scanning and baseline detection, the vulnerabilities of the large data platform are scanned and the potential safety hazards of baseline configuration are detected, and the relative weakness of vulnerability scanning and attack monitoring technologies of the large data platform is compensated.
2. According to the invention, the sensing technology module is used for checking through the face recognition and voice command, the data is stored through the storage module after checking, and when the data is checked and shared again after storage, the face recognition and voice command of the sensing technology is also needed, the recording, analysis and report of the behavior of a user accessing the database are carried out, so that the user is helped to generate a compliance report and accident tracing, the network behavior records of the internal and external databases are enhanced, and the sharing safety of data, the safety protection of the unstructured database and the data leakage tracing technology are improved.
3. According to the invention, the core technology and the privacy of the database are encrypted by the data asset combing module through the sensing technology, so that the protection of personal information privacy in a big data application scene is enhanced.
Drawings
FIG. 1 is a schematic diagram of a big data-based network security awareness system according to the present invention;
fig. 2 is a system flowchart of the big data based network security awareness system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: the system comprises a data acquisition module, a distributed processing module, a cloud computing module, a perception technology module, a storage counting module, a data protection module, a database missing scanning module, a data asset combing module, a large database application access module and a large data auditing module, wherein the output end of the data acquisition module is connected with the input end of the distributed processing module, the acquired data are connected with a plurality of computers in different places, or with different functions, or with different data through the distributed processing module, through a communication network, and under the unified management control of a control system, the computer system coordinately completes large-scale information processing tasks. The cloud computing module decomposes a huge data computing processing program into countless small programs through a network cloud, then processes and analyzes the small programs through a system consisting of a plurality of servers to obtain results and returns the results to a user, the results are not only distributed computing, but also the results of mixed evolution and leap of computer technologies such as distributed computing, utility computing, load balancing, parallel computing, network storage, hot backup redundancy, virtualization and the like, the output end of the distributed processing module is connected with the input end of the cloud computing module, the output end of the cloud computing module is connected with the input end of a perception technology module, the output end of the perception technology module is connected with the input end of a storage module, the output end of a data protector is connected with the input end of a big data application access control module, and the big data auditing module is used for forming detailed logs of the operation behaviors of a host object and an object, The method comprises the functions of user name, IP, operation, resource, access type, time, authorization result, summary of specific design and new event, risk event, report management, system maintenance, rule management, log retrieval and the like. The data desensitization is to desensitize sensitive information and start data desensitization aiming at a big data storage data full table or a big data field without reading any content of a big data assembly, only a corresponding desensitization strategy needs to be configured, the output end of a data protection is connected with the input end of a big data auditing module, the output end of the data protection is connected with the input end of a database missing scanning module, the output end of the data protection is connected with the input end of a data asset combing module, the output end of the database missing scanning module is connected with the input end of resource security vulnerability detection, the input end of the data asset combing module is used for connecting the input end of sensitive data, the output end of the sensitive data is connected with the input end of the sensitive data, the output end of the data asset combing module is connected with the input end of a database, the output end of the database encryption is connected with the input end of database security operation and maintenance, the output of database safety fortune dimension with prevent that fortune dimension personnel from operating badly, the big output of database safety fortune dimension with prevent that fortune dimension personnel high-risk operation input is connected, the database is encrypted the core technology and the privacy of database, can carry out database safety fortune dimension in the database, and then prevent fortune dimension personnel from operating badly and prevent fortune dimension personnel high-risk operation.
The working principle of the invention is as follows: the system performs proper signal processing after signal acquisition through a data acquisition module, then connects a plurality of computers in different places or with different functions or with different data through a communication network under the distributed processing module, coordinately completes information processing tasks under the unified management control of a control system, decomposes huge data calculation processing programs into countless small programs through a cloud computing module, then processes and analyzes the small programs through a system composed of a plurality of servers to obtain results and returns the results to a user, then a perception technology module is used for checking through face recognition and voice commands, the checked data are stored through a storage module, the face recognition and voice commands of perception technology are needed when the data are checked and shared again after being stored, data protection is also provided in the safety perception of big data, and the data protection module performs the compliance management of fine-grained audit on database operation through the big data module The method has the advantages that the method can give an alarm to the risky behaviors suffered by the database, block the attack behaviors, record, analyze and report the behaviors of the user accessing the database, and is used for helping the user generate a compliance report and accident tracing and tracing sources after the incident, meanwhile, the network behavior records of the internal and external databases are strengthened, and the data asset safety is improved. The data protection identifies all functions in the system through a large database application access control module, organizes and hosts the functions, organizes and identifies all data to be hosted, and then provides a simple and unique interface, wherein one end of the interface is an application system and the other end of the interface is a permission engine. The rights engine answers only: who has the right to perform some action (motion, computation) on some resource. The returned results are only: with or without, the rights engine is abnormal. The data protection detects the security vulnerability of a designated remote or local computer system through means of scanning of a database vulnerability scanning module and the like, finds one security detection of available vulnerabilities, and scans vulnerability of a large data platform and potential security hazards of baseline configuration by periodic vulnerability scanning and baseline detection of large data platform components when resources in a database pass through resource security vulnerability detection. Sensitive data are automatically identified through a data asset combing module in data protection, the sensitive data are classified, and any content of a big data assembly cannot be changed by using a sensitive data discovery strategy, so that data desensitization is performed to perform sensitive information desensitization on a big data storage data full table or field, data desensitization is started without reading any content of the big data assembly, and only a corresponding desensitization strategy needs to be configured. The core technology and the privacy of the database are encrypted through the sensing technology in the data asset combing module, and the database can be safely operated and maintained in the database, so that operation and maintenance personnel are prevented from being badly operated and high-risk operation of the operation and maintenance personnel is prevented.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (8)
1. Network security perception system based on big data, including data acquisition module, distributed processing module, cloud computing module, perception technology module, storage count module, data protection, database miss-scanning module, data asset carding module, big database application access module, big data audit module, its characterized in that: the output end of the data acquisition module is connected with the input end of the distributed processing module, the output end of the distributed processing module is connected with the input end of the cloud computing module, the output end of the cloud computing module is connected with the input end of the perception technology module, the output end of the perception technology module is connected with the input end of the storage module, the output end of the data protection is connected with the input end of the big data application access control module, the output end of the data protection is connected with the input end of the big data auditing module, the output end of the data protection is connected with the input end of the database missing scanning module, and the output end of the data protection is connected with the input end of the data asset combing module.
2. The big data based network security awareness system according to claim 1, wherein: the output end of the database missing scanning module is connected with the input end of the resource safety vulnerability detection, the input end of the data asset combing module is used for connecting the input end of the sensitive data, the output end of the sensitive data is connected with the input end of the sensitive data, the output end of the data asset combing module is connected with the input end of the database, the output end of the database is connected with the input end of the database encryption, the output end of the database encryption is connected with the input end of the database safety operation and maintenance, the output end of the database safety operation and maintenance is in operation with the prevention of operation and maintenance personnel, and the output end of the database safety operation and maintenance with the large size is connected with the input end of the operation with the prevention of high risk of the operation and.
3. The big data based network security awareness system according to claim 1, wherein: the distributed processing module is a computer system which connects a plurality of computers in different places, or with different functions, or with different data through a communication network and coordinately completes large-scale information processing tasks under the unified management control of a control system. The cloud computing module is used for decomposing a huge data computing processing program into countless small programs through a network cloud, then processing and analyzing the small programs through a system consisting of a plurality of servers to obtain results and returning the results to a user, and the cloud computing module is not only distributed computing, but also results of mixed evolution and leap of computer technologies such as distributed computing, utility computing, load balancing, parallel computing, network storage, hot backup, redundancy, virtualization and the like.
4. The big data based network security awareness system according to claim 1, wherein: the perception technology module is a technology of face recognition, voice command, eyeball tracking, gesture control and the like. Voice commands and facial recognition are widely used. The big data auditing module forms detailed logs of the operation behaviors of the host and the object, and has the functions of user name, IP, operation, resources, access type, time, authorization result, summary of specific design and new events, risk event, report management, system maintenance, rule management, log retrieval and the like. The data desensitization is to desensitize sensitive information for a large data storage data full table or field, and start data desensitization does not need to read any content of a large data assembly, and only needs to configure a corresponding desensitization strategy.
5. The big data based network security awareness system according to claim 1, wherein: the big data application access control module can perform unified management and control and centralized authorization management on the big data platform account. And fine-grained authorization and access control are provided for users and application programs of the large data platform. The resource security vulnerability detection is the periodical vulnerability scanning and baseline detection of the big data platform assembly, and the vulnerability scanning and baseline configuration potential safety hazard of the big data platform are detected; the system comprises functional modules such as risk display, vulnerability detection, report management and a knowledge base. The data asset combing module can automatically identify and classify sensitive data, and enable a sensitive data discovery strategy without changing any content of the big data component.
6. The big data based network security awareness system according to claim 1, wherein: the data acquisition module is combined with a computer or other special test platform-based measurement software and hardware products to realize a flexible and user-defined measurement system. The acquisition is generally a sampling mode, that is, the same point data is repeatedly acquired at certain time intervals (called sampling period). The acquired data are mostly instantaneous values, but also characteristic values within a certain period of time.
7. The big data based network security awareness system according to claim 1, wherein: when the resource security vulnerability detection is the resource security vulnerability detection, the large data platform component is subjected to periodic vulnerability scanning and baseline detection, the large data platform vulnerability is scanned, potential safety hazards are configured on the baseline, and sensitive data are automatically identified through the data asset combing module during data protection.
8. The big data based network security awareness system according to claim 1, wherein: the database is used for encrypting the core technology and the privacy of the database, and the database can be safely operated and maintained, so that operation and maintenance personnel are prevented from being badly operated and high-risk operation of the operation and maintenance personnel is prevented.
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