Controller: issues control information according to pre-given commands, so that the entire computer instruction execution process proceeds step by step. It is the nerve center of the computer. Its function is to interpret the control information specified by the program and control it according to its requirements, and schedule the program. , data and addresses, coordinate the work of various parts of the computer and access to memory and peripherals, etc.

The main function: Retrieve an instruction from the memory and indicate the location of the next instruction in the memory, decode or test the instruction, and generate corresponding operation control signals to initiate specified actions; command and control the CPU, memory and input/output The direction of data flow between devices.

The function of the arithmetic unit is to perform various arithmetic operations and logical operations on data, that is, to process the data.

The basic operations of the arithmetic unit include the four arithmetic operations of addition, subtraction, multiplication, and division, logical operations such as AND, OR, NOT, and XOR, as well as operations such as shifts, comparisons, and transmissions. It is also called the Arithmetic Logic Unit (ALU). When the computer is running, the operation and type of operation of the arithmetic unit are determined by the controller. The arithmetic unit accepts the commands of the controller and performs actions. That is, all operations performed by the arithmetic unit are directed by the control signals sent by the controller.

The function of memory is to store programs, data, various signals, commands and other information, and to provide this information when needed. Memory is divided into memory inside the computer (referred to as memory) and memory outside the computer (referred to as external memory). Internal memory can be functionally divided into two categories: read-write memory RAM and read-only memory ROM.

Computer storage capacity is measured in bytes, which are: byte B (1Byte=8bit), kilobyte (1KB=1024B), megabyte (1MB=1024KB), gigabyte (1GB=1024MB), terabyte section (1TB = 1024GB).

Computer external memories generally include: floppy disks and floppy drives, hard disks, optical disks, etc., as well as USB interface-based mobile hard disks, rewritable electronic hard disks, USB flash drives, etc.

Input devices are an important part of the computer. Input devices and output devices are collectively called external devices, referred to as peripherals. The function of the input device is to input information such as programs, original data, text, characters, control commands or data collected on site into the computer. computer.

Commonly used input devices include keyboards, mice, microphones, cameras, scanners, code scanners, handwriting pads, touch screens, etc.

The output device is also an important part of the computer. It outputs the intermediate results or final results of the external computer, various data symbols and text in the computer, or various control signals and other information.

Commonly used output devices include: monitors, printers, laser printers, plotters, etc.

System software refers to a system that controls and coordinates computers and external devices, and supports the development and operation of application software. It is a collection of various programs that do not require user intervention. Its main function is to schedule, monitor and maintain computer systems; it is responsible for managing various aspects of computer systems. Independent hardware allows them to work in harmony. System software allows computer users and other software to treat the computer as a whole without having to consider how the underlying hardware works.

Application software is a collection of various programming languages ​​that users can use and application programs compiled in various programming languages. It is divided into software packages and user programs.

An application software package is a collection of programs designed to use computers to solve certain types of problems, mostly for users to use. Application software is software provided to meet the application needs of users in different fields and problems.

Middleware is software that sits between the operating system and applications. It uses the basic services (functions) provided by the system software to connect various parts of the application system or different applications on the network, and can achieve the purpose of resource sharing and function sharing. Middleware is a common service located between the platform (hardware and operating system) and the application. These services have standard program interfaces and protocols. For different operating systems and hardware platforms, no matter how the underlying computer hardware and system software are updated, as long as the middleware is upgraded and the external interface definition of the middleware remains unchanged, the application software hardly needs any modification, thus Ensure the continuous and stable operation of application software.

1||| digital communication technology

2||| information transmission technology

3||| Communication network technology

An ad hoc network that connects personal electronic devices (such as portable computers, etc.) using wireless technology at a person's work place, so it is often called a wireless personal area network WPAN (Wireless PAN). From a computer network perspective, PAN is a local area network, and its range is usually around 10m.

Usually refers to using microcomputers or workstations connected through high-speed communication lines (the rate is usually above 10Mb/s), and its geographical range is usually about 1km. Usually covers a campus, a unit, a building, etc.

The range of action can span several blocks or even the entire city, and its range is approximately 5-50km.

Node switches are used to connect each host, and the connection links between the node switches are generally high-speed links with large communication capacity. The scope of a wide area network is usually tens to thousands of kilometers, and it can transmit data over long distances across a country or a continent.

Refers to a large-scale network funded and built by telecommunications companies to provide services to the public, also known as a public network.

Refers to the network built by a certain department to meet the special business work of the unit. This network does not provide services to people outside the unit. For example, electric power, military, railways, banks, etc. all have dedicated networks for this system.

Based on TCP

Based on UDP

TCP is one of the most important protocols in the entire TCP/IP protocol suite. Based on the unreliable data services provided by the IP protocol, it uses retransmission technology to provide applications with a reliable, connection-oriented, full-double data transfer service. The TCP protocol is generally used in situations where the amount of data transmitted is relatively small and reliability requirements are high.

UDP is an unreliable, connectionless protocol that ensures communication between application processes. Compared with TCP, UDP is a connectionless protocol, and its error detection function is much weaker. It can be said that TCP helps in providing reliability while UDP helps in increasing the transfer rate. The UDP protocol is generally used in situations where a large amount of data is transmitted and the reliability requirements are not very high, but fast speed is required.

DAS, also known as SAS (Server-Attached Storage, server-attached storage). DAS is defined as a data storage device directly connected to various server or client expansion interfaces. It relies on the server and is a stack of hardware without any storage operating system. In this approach, the storage device is connected directly to the server via a cable (usually a SCSI interface cable), and I/O (input/output) requests are sent directly to the storage device.

a. Network-Attached Storage (NAS)

b. Storage Area Network (SAN)

The hierarchical model is the earliest model used in database systems. It uses a "tree" structure to represent the association between entity sets, in which the entity sets (represented by rectangular boxes) are nodes, and the connections between the nodes in the tree represent the relationship between them. (Can only handle one-to-many entity relationships)

Any given record value in the hierarchical model can only be viewed according to its hierarchical path. No child record value can exist independently from the parent record value.

Key benefits include:

The main disadvantages include:

A data structure model that uses a directed graph structure to represent entity types and relationships between entities is called a network model.

In the network model, records are used as the storage unit of data. A record contains several data items. Data items in a network database can be multi-valued and composite data. Each record has an internal identifier that uniquely identifies it, called a code (DatabaseKey, DBK), which is automatically assigned by the database management system DBMS when a record is stored in the database. DBK can be regarded as the logical address of the record, can be used as a "stand-in" for the record, or can be used to find records. The network database is a navigation database. When operating the database, users not only explain what to do, but also how to do it. For example, in the search statement, not only the search object must be specified, but also the access path must be specified.

Key benefits include:

The main disadvantages include:

The relational model is a model that uses a two-dimensional table to represent entities and the connections between entities in a relational structured database. The relational model is developed based on the relational concept in set theory. In the relational model, both entities and the connections between entities are represented by a single structural type relationship.

Key benefits include:

The main disadvantages include:

1||| The order of rows and columns in the table is not important

2||| Row: Each row in the table, also called a record

3||| Column: Each column in the table, also known as attributes and fields

4||| Primary key PK (Primary key): the field foreign key FK field used to uniquely determine a record

5||| Domain: The value range of the attribute. For example, gender can only have two values: "male" and "female"

1||| unstructured storage

2||| Based on multidimensional relational model

3||| Have specific usage scenarios

1||| key-value database

2||| Column-oriented database

3||| Document-Oriented database

4||| graph database

The user extracts all the data from the data source, and after data cleaning and conversion, the data is finally loaded into the data warehouse according to the predefined data warehouse model.

Data about data refers to key data related to data source definitions, target definitions, conversion rules, etc. generated during the data warehouse construction process. Metadata also contains business information about the meaning of the data. Typical metadata includes: the structure of the data warehouse table, the attributes of the data warehouse table, the source data of the data warehouse (recording system), the mapping from the recording system to the data warehouse, the specification of the data model, the extraction of logs and the utility of accessing the data. Routines etc.

The level of granularity or comprehensiveness of data stored in a data warehouse's data warehouse. The higher the degree of refinement, the smaller the granularity level; conversely, the lower the degree of refinement, the larger the granularity level.

Data with the same structure is divided into multiple physical units of data. Any given unit of data is subject to exactly one partition.

Small, department- or workgroup-level data warehouse.

A data collection that can support an organization's daily global applications is a new data environment different from DB, and is a hybrid form obtained after DW expansion. It has four basic characteristics: topic-oriented, integrated, variable, and current or near-current.

Logical data structure, including the operations and constraints provided by a database management system for efficient database processing; a system used to represent data.

A design technique that uses 1-1 to represent referential integrity in a decision support system environment.

It is the foundation of the data warehouse system and the data source of the entire system. Usually includes information internal to the organization and information external to the organization. Internal information includes storing various business processing data and various document data in the relational database management system. External information includes various laws and regulations, market information, competitor information, etc.

It is the core of the entire data warehouse system. The organization and management method of the data warehouse determines that it is different from traditional databases, and also determines its representation of external data. Extract, digest and effectively integrate data from existing business systems, and organize it according to themes. Data warehouses can be divided into organizational-level data warehouses and department-level data warehouses (often called data marts) according to the scope of data coverage.

OLAP effectively integrates the data required for analysis and organizes it according to multi-dimensional models to conduct multi-angle and multi-level analysis and discover trends. Its specific implementation can be divided into: OLAP (Relational OLAP, ROLAP) based on relational database, OLAP (Multidimensional OLAP, MOLAP) based on multidimensional data organization, and OLAP (Hybrid OLAP, HOLAP) based on hybrid data organization. ROLAP basic data and aggregate data are stored in RDBMS; MOLAP basic data and aggregate data are stored in multi-dimensional databases; HOLAP basic data are stored in Relational Database Management System (RDBMS), and aggregate data are stored in in a multidimensional database.

Front-end tools mainly include various query tools, report tools, analysis tools, data mining tools, and various application development tools based on data warehouses or data marts. Among them, data analysis tools are mainly aimed at OLAP servers, while reporting tools and data mining tools are mainly aimed at data warehouses.

meaning

Way to achieve

meaning

Three aspects of checking integrity:

meaning

（1） authenticity

（2） Verifiability

（3） non-repudiation

（4） reliability

The security of information system equipment is the primary issue of information system security. The equipment security of information systems is the material basis for information system security. In addition to hardware devices, software systems are also devices, and the security of software devices must also be ensured.

mainly include

In many cases, even if the information system equipment is not damaged, its data security may have been compromised, such as data leakage, data tampering, etc. Since behaviors that endanger data security are highly concealed and data application users are often unaware of them, they are very harmful.

Its security properties include

Content security is a requirement for information security at the political, legal, and moral levels.

Content security includes

Broadly defined content security also includes

If the data is filled with unhealthy, illegal, and unethical content, even if it is confidential and has not been tampered with, it cannot be said to be safe.

Data security is essentially a static security, while behavioral security is a dynamic security.

include

Behavioral security emphasizes process safety, which is reflected in the fact that the coordinated work procedures (execution sequences) of the hardware devices, software devices and application systems that make up the information system meet the expectations of the system design. Only in this way can the overall security of the information system be ensured.

1||| The signer cannot repudiate his signature afterwards.

2||| No one else can forge the signature.

3||| If the parties dispute the authenticity of a signature, they can confirm its authenticity by verifying the signature before an impartial arbiter.

1||| Authentication is always based on some kind of confidential data shared by both sender and receiver to verify the authenticity of the object being authenticated, while the data used to verify the signature in a digital signature is public.

2||| Authentication allows the sending and receiving parties to verify each other's authenticity and does not allow third parties to verify, while digital signatures allow both the sending and receiving parties and a third party to verify.

3||| Digital signatures cannot be repudiated by the sender, cannot be forged by the receiver, and have the ability to resolve disputes before a notary public, while certification does not necessarily have the ability.

Ensuring the safe operation of computer equipment is one of the most important aspects of information system security

In addition to integrity, confidentiality and availability, it also includes

As the main carrier of information collection, storage, distribution, transmission and application, the security of the network plays a vital or even decisive role in the security of the entire information. The network environment creates an ideal space for information sharing, information exchange, and information services. The inherent openness, interactivity and decentralization characteristics of the Internet, while allowing people to share information openly, flexibly and quickly, also bring about network security-related issues.

Network security related issues:

Common cyber threats include:

According to the manifestations of security threats, they are as follows:

A database system is a platform for storing, managing, using and maintaining data. Database security mainly refers to the security of database management systems, and its security issues can be considered as security issues for data used for storage rather than transmission.

Application system security is based on computer equipment security, network security and database security. At the same time, effective anti-virus, anti-tampering and version checking and auditing are adopted to ensure the legality and integrity of the system's own execution programs and configuration files, which are extremely important security assurance measures.

Use the web page detection program to read out the web pages to be monitored in a polling manner, compare them with the real web pages to determine the integrity of the web page content, and alarm and restore tampered web pages.

The so-called core embedded technology is password watermarking technology. This technology embeds the tampering detection module in the Web server software. It performs integrity checks when each network member leaves the network, blocks tampered web pages in real time, and provides alarms and recovery.

It is to use the file system or driver interface of the operating system to check the legality when the web page file is modified, and to alarm and recover illegal operations.

It is a simple, efficient, safe and extremely high anti-tampering technology. Through the event triggering method, the file contents in all folders of the web server are compared with the underlying file attributes and the built-in hash fast algorithm is used for real-time monitoring; if the attribute changes are found, the contents of the backup path folder are copied to the monitoring file. The corresponding file location of the folder makes the tampered page invisible to the public.

NGFW’s DPI function includes IPS

NGFW blocks or allows packets depending on where they are going. They do this by analyzing traffic at Layer 7 (the application layer). Traditional firewalls do not have this capability because they only analyze Layer 3 and Layer 4 traffic.

Various types of information outside the firewall can be collected and used to improve blocking decisions or serve as the basis for optimizing blocking rules. For example, use directory integration to enforce blocking based on user identity or blacklist and whitelist based on address.

It is composed of various sensors, including temperature sensors, QR code tags, RFID tags, readers, cameras, GPS and other sensing terminals. The perception layer is the source of identifying objects and collecting information in the Internet of Things.

It is composed of various networks, including the Internet, radio and television networks, network management systems and cloud computing platforms. It is the hub of the entire Internet of Things and is responsible for transmitting and processing information obtained by the perception layer.

It is the interface between the Internet of Things and users. It is combined with industry needs to realize intelligent applications of the Internet of Things.

Virtualization is a broad term that generally refers to computing elements running on a virtual basis rather than a real basis. Virtualization technology can expand the capacity of hardware and simplify the reconfiguration process of software. CPU virtualization technology can simulate multiple CPUs in parallel with a single CPU, allowing one platform to run multiple operating systems at the same time, and applications can run in independent spaces without affecting each other, thereby significantly improving computer work efficiency.

Container technology is a new virtualization technology in a new sense, which belongs to the category of operating system virtualization, that is, the operating system provides virtualization support. The most popular container environment currently is Docker. Container technology divides the resources of a single operating system into isolated groups to better balance conflicting resource usage needs among isolated groups. Using container technology can isolate the application in an independent running environment, which can reduce the additional consumption caused by running the program and can run in the same way almost anywhere.

Cloud storage technology is a new information storage and management method developed based on traditional media systems. This method integrates the software and hardware advantages of computer systems and can process large batches of data online quickly and efficiently. Through a variety of cloud The application of technology platforms enables in-depth data mining and security management.

As an important part of cloud storage technology, distributed file systems improve system replication and fault tolerance functions while maintaining compatibility.

It is one of the core issues in cloud computing applications. Research on cloud computing access control mainly focuses on cloud computing access control models, cloud computing access control based on ABE cryptography, multi-tenant and virtualization access control in the cloud.

The cloud computing access control model is a method to describe the security system according to specific access policies and establish a security model. According to the different functions of the access control model, the research content and methods are also different. Common ones include task-based access control model, attribute model-based cloud computing access control, UCON model-based cloud computing access control, and BLP model-based cloud computing. access control etc.

Cloud computing access control based on the ABE password mechanism includes four parties: data providers, trusted third-party authorization centers, cloud storage servers, and users. First, the trusted authorization center generates the master key and public parameters, and passes the system public key to the data provider. After the data provider receives the system public key, it uses the policy tree and system public key to encrypt the file, and converts the ciphertext and policy The tree is uploaded to the cloud server; then, when a new user joins the system, he uploads his attribute set to the trusted authorization center and submits a private key application request. The trusted authorization center calculates and generates the attribute set and master key submitted by the user. The private key is passed to the user; finally, the user downloads the data of interest. If its attribute set satisfies the policy tree structure of the ciphertext data, the ciphertext can be decrypted; otherwise, access to the data fails.

Cloud security research mainly includes two aspects. One is the security protection of cloud computing technology itself, involving corresponding data integrity and availability, privacy protection, service availability, etc.; the other is the use of cloud services. To ensure the security protection needs of client users, Internet security is achieved through cloud computing technology, involving cloud computing-based virus prevention and Trojan detection technology, etc.

In terms of research on cloud security technology, it mainly includes:

Jump from TB level to PB level (IPB=l024TB), EB level (IEB=I024PB), and even reach ZB level (IZB=I024EB).

There are many types of data in big data, which are generally divided into structured data and unstructured data. Compared with the text-based structured data that has been stored in the past, there are more and more unstructured data, including web logs, audio, video, pictures, geographical location information, etc. These multiple types of data have greater data processing capabilities. Higher demands were made.

The level of data value density is inversely proportional to the size of the total data abundance. Take video as an example. For a one-hour video, under continuous and uninterrupted monitoring, the useful data may only be one or two seconds. How to "purify" the value of data more quickly through powerful machine algorithms has become an urgent problem to be solved in the current context of big data.

In order to quickly mine data value from massive amounts of data, it is generally required to quickly process different types of data. This is the most significant feature of big data that distinguishes it from traditional data mining.

Research on big data acquisition mainly focuses on three aspects: data collection, integration and cleaning. Data acquisition technology achieves the acquisition of data sources, and then ensures data quality through integration and cleaning technology.

Data collection technology mainly obtains data information from websites through distributed crawling, distributed high-speed and high-reliability data collection, and high-speed whole-network data imaging technology. In addition to the content contained in the network, the collection of network traffic charges can be processed using bandwidth management technologies such as DPI or DFI.

Data integration technology is based on data collection and entity recognition to achieve high-quality integration of data into information. Data integration technology includes multi-source and multi-modal information integration models, heterogeneous data intelligent conversion models, intelligent pattern extraction and pattern matching algorithms for heterogeneous data integration, automatic fault-tolerant mapping and conversion calibration and algorithms, and correctness verification methods for integrated information. , usability evaluation methods of integrated information, etc.

Data cleaning technology generally removes unreasonable and erroneous data based on correctness conditions and data constraint rules, repairs important information, and ensures data integrity. Including data correctness semantic model, association model and data constraint rules, data error model and error recognition learning framework, automatic detection and repair algorithms for different error types, evaluation models and evaluation methods of error detection and repair results, etc.

Distributed computing emerged with the development of distributed systems. Its core is to decompose tasks into many small parts and assign them to multiple computers for processing. Through the mechanism of parallel work, it can save overall computing time and improve computing efficiency. the goal of. Currently, the mainstream distributed computing systems include Hadoop, Spark and Storm. Hadoop is often used for offline complex big data processing, Spark is often used for offline fast big data processing, and Storm is often used for online, real-time big data processing.

Big data analysis and mining technology mainly refers to improving existing data mining and machine learning technologies: new data mining technologies such as Shengfa data network mining, specific group mining, and graph mining; innovating big data such as object-based data connections and similarity connections. Fusion technology: breakthroughs in field-oriented big data mining technologies such as user interest analysis, network behavior analysis, and emotional semantic analysis.

Big data management technology mainly focuses on big data storage, big data collaboration, security and privacy.

Big data storage technology mainly has three aspects:

Collaborative management technology of multiple data centers is another important direction of big data research. Through the distributed workflow engine, workflow scheduling and load balancing are realized, and storage and computing resources of multiple data centers are integrated to provide support for building a big data service platform.

Research on big data privacy technology mainly focuses on new data release technologies, trying to maximize user privacy while minimizing the loss of data information, thereby achieving the needs of data security and privacy protection.

1||| Big data application and service technologies mainly include analysis application technology and visualization technology.

2||| Big data analysis applications are mainly business-oriented analysis applications. Based on the analysis and mining of distributed sea level data, big data analysis application technology is driven by business needs, carries out special data analysis for different types of business needs, and provides users with highly available and easy-to-use data analysis services.

3||| Visualization helps people explore and understand complex data through interactive visual representations. Big data visualization technology mainly focuses on text visualization technology, network (graph) visualization technology, spatiotemporal data visualization technology, multi-dimensional data visualization and interactive visualization, etc.

The verification, accounting, storage, maintenance and transmission of data on the chain all rely on the distributed system structure. Pure mathematical methods are used to replace centralized organizations to build trust relationships between multiple distributed nodes, thereby establishing a trusted distributed system. system.

The incentive mechanism ensures that all nodes in the distributed system can participate in the verification process of data blocks, and select specific nodes through the consensus mechanism to add newly generated blocks to the blockchain.

Blockchain uses a chain structure with timestamp information to store data information and adds time dimension attributes to the data information, thereby achieving traceability of data information.

Blockchain technology can provide users with flexible and variable script codes to support the creation of new smart contracts.

In the blockchain system, because the subsequent blocks between adjacent blocks can verify the previous blocks, if the data information of a certain block is tampered with, the block and all subsequent blocks will be recursively modified. However, the cost of each hash recalculation is huge and must be completed within a limited time, so the non-tamperability of the data on the chain can be guaranteed.

In the blockchain network, each physical device can serve as a node in the network, and any node can join freely and have a complete copy of the database.

Data security can be achieved by encrypting data on the chain based on asymmetric encryption technology. Each node in the distributed system uses the computing power formed by the blockchain consensus algorithm to resist external attacks and ensure that the data on the chain is not tampered with or forged. As a result, it has higher confidentiality, credibility and security.

Also called data digest or hash algorithm, its principle is to convert a piece of information into a fixed-length string with the following characteristics: If two pieces of information are the same, then the characters are also the same: even if the two pieces of information are very similar, But as long as they are different, the strings will be very messy, random, and have no relationship at all between the two strings. Typical hashing algorithms include MD5, SHA and SM3. Currently, blockchain mainly uses the SHA256 algorithm.

An encryption method consisting of a corresponding pair of unique keys (ie, public key and private key). Anyone who knows the user's public key can use the user's public key to encrypt information and achieve secure information interaction with the user. Due to the dependency between the public key and the private key, only the user himself can decrypt the information, and no unauthorized user or even the sender of the information can decrypt the information. Commonly used asymmetric encryption algorithms include RSA, Elgamal, D-H, ECC (elliptic curve encryption algorithm), etc.

（1） Compliance supervision

（2） Performance efficiency

（3） LF

（4） fault tolerance

Drawing on the research results of brain science and cognitive science is an important research direction of artificial intelligence. Human-machine hybrid intelligence aims to introduce human functions or cognitive models into artificial intelligence systems to improve the performance of artificial intelligence systems, making artificial intelligence a natural extension and expansion of human intelligence, and solving complex problems more efficiently through human-machine collaboration. .

Current major research in the field of artificial intelligence focuses on deep learning, but the limitation of deep learning is that it requires a lot of manual intervention. Therefore, scientific researchers have begun to pay attention to autonomous intelligence methods that reduce manual intervention and improve the ability of machine intelligence to autonomously learn from the environment.

Artificial intelligence is a comprehensive cutting-edge discipline and a highly interdisciplinary composite discipline that requires deep integration with disciplines such as computer science, mathematics, cognitive science, neuroscience, and social science. With the help of breakthroughs in biology, brain science, life science, psychology and other disciplines, and turning mechanisms into computable models, artificial intelligence will deeply interpenetrate with more disciplines.

The innovative model of "Artificial Intelligence

In order to ensure the healthy and sustainable development of artificial intelligence and make its development results benefit the people, it is necessary to systematically and comprehensively study the impact of artificial intelligence on human society from a sociological perspective, and formulate and improve artificial intelligence laws and regulations.