The four mainstream applications of artificial intelligence in network security
With the rapid development of science and technology in recent years, words such as artificial intelligence, cloud computing, and big data have become hot searches. Artificial intelligence can be said to be one of the "red-hot chicken", both domestic and foreign, has received considerable attention, and artificial intelligence plays a pivotal role in more and more fields.
Then, in the computer network security management technology, the most important contents include anti-spam, firewall and intrusion detection. At the same time, network control and network monitoring are the two most important steps in the network management system process. Combining these advantages of artificial intelligence in computer networks can better manage computer network security.
1. Intelligent anti-spam system
Artificial intelligence is applied in the anti-spam system. In addition to protecting the security of user data, the most important thing is to detect and scan the user's emails and identify them intelligently, and take effective precautions to prevent malicious emails. Users are protected from spam harassment. The currently used Tencent Enterprise Mailbox has already applied this artificial intelligence anti-spam system to it, and the effect is remarkable.
2. Intelligent firewall system
Firewalls have become commonplace as network security devices. Traditional firewalls rely on network administrators to set security rules to permit what packets can pass and what packets should be rejected. It is more dependent on the administrator to ensure the security of the data packet. The firewall itself cannot judge whether a normal data packet is different from a malicious data packet. The identification technology referenced by the intelligent firewall can analyze and process the corresponding data on its own, and at the same time, it can skillfully integrate the proxy technology and the filtering technology, which can not only reduce the calculation amount of the computer, but also broaden the monitoring range, effectively Intercept the data flow that is harmful to the network, so as to better protect the security of the network environment.
3. Intelligent intrusion detection system
Today, with the increasing threat of cybersecurity, the importance of intrusion detection technology is self-evident. Traditional intrusion detection techniques have shortcomings in terms of detection speed, detection range, and architecture. In order to make up for these shortcomings, the intelligent intrusion detection system enhances the efficiency of intrusion detection by means of fuzzy information recognition, rule generation expert system, data mining and artificial neural network in artificial intelligence, and can best resist the viruses from all parties. The potential threat posed by the invasion.
4. Network monitoring and control
In order to grasp the information in the computer network in real time, the network needs to have the function of uploading data information. At present, systems such as Deep Packet Inspection (DPI) use probes to collect network traffic data information, and DPI can further collect network operation status, network service quality information, and resource usage.
Through the massive data collected from DPI, artificial intelligence technology can use its powerful understanding and reasoning ability to quickly analyze and judge whether there is an abnormality in the information. For example, if there is a sudden large traffic situation, the artificial intelligence system can speculate that there is a distributed denial of service (DDoS) attack in the network, and immediately analyze the software package characteristics, and then coordinate the probe cooperation tasks, all of which have the same characteristics. The software package is discarded to minimize the loss of other network services. In the event of a new virus attack or hacking, artificial intelligence can also use its own learning ability to write relevant records in a secure database.
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