In just over half a century of development, artificial intelligence has achieved a leap from academic theory to industrial application, and has realized industrial empowerment in many fields such as finance, medical treatment, education, energy and so on. The research and application of artificial intelligence technology in the field of network security has also attracted the attention of science and technology companies, and its application value began to emerge.
1、 Application advantages of artificial intelligence in the field of network security
The application advantages of artificial intelligence technology in the field of network security are mainly reflected in three aspects. First, artificial intelligence technology has the ability of self-learning and can deal with unknown attack means and rapidly changing network risk environment. Second, artificial intelligence technology is based on big data technology, which has the ability to process massive data efficiently, making it possible to process massive network security traffic data. Third, artificial intelligence has the ability to automate intelligent decision-making, which can minimize the intervention of “human factors”, reduce personnel costs and improve the efficiency and stability of network security operation.
The main applications of artificial intelligence in the field of network security include AI firewall, AI vulnerability scanning, AI security control platform, etc. The new generation of robot firewall (ai-waf) realizes dynamic verification mechanism based on artificial intelligence technology. The combination of artificial intelligence technology and firewall technology greatly improves the efficiency and ability of automatic attack interception, traffic security detection and filtering and risk intelligent blocking. In terms of vulnerability scanning, combined with artificial intelligence technology, the method of in-depth learning is applied to security detection, and unknown vulnerabilities are actively excavated, which can “detect and discover” vulnerabilities, enhance the ability to help users “manage vulnerabilities” focus on “repair”, realize the real closed-loop vulnerability repair, and deal with the changing security vulnerability situation. At the same time, the AI security management and control platform based on artificial intelligence technology forms a security management center to coordinate business management and control by integrating data security risk, business security risk, audit security risk, terminal security risk and whole process management and control of transaction processing, and with the help of device fingerprint, biological probe, decision engine, rule engine and situation awareness, Strengthen security management and control capabilities and expansion capabilities, improve business risk control and identification capabilities, and assist enterprise institutions to achieve security digital management and control.
2、 Network security application of artificial intelligence in finance and energy
1,Artificial intelligence helps bank mobile application network security protection
As the pioneer of digital economy, financial technology has developed rapidly in recent years. While the bank’s virtual network / smart network services are diversified, the security risks are expanding, APP program security, operation security, network security and business fraud security issues emerge, and security incidents such as vulnerability attack, application tampering, “picking wool”, plundering promotion resources and sensitive information disclosure emerge one after another. In the face of emerging security shocks, traditional security technologies obviously lag behind emerging threats. Problems such as constantly finding vulnerabilities, patching, lagging response, passive defense and complex management are prominent. Customers need more leading and innovative dynamic security solutions to ensure the uninterrupted operation of online business.
Artificial intelligence can be applied to mobile application security reinforcement and Internet Financial situational awareness services, build a “mobile app situational awareness platform”, conduct network wide security monitoring from multiple perspectives such as application, industry, channel and region, and collect data from multiple information sources. Applying artificial intelligence analysis and modeling technology to carry out association and combination modeling from multiple dimensions such as application threat, application vulnerability, application harm, industry distribution, channel distribution and regional distribution can improve the effectiveness and accuracy of data, and obtain the situation perception data and threat warning data of the whole network. Then, visual technology is used to generate situation evaluation report and network comprehensive situation map to provide auxiliary decision-making information for security managers.
2,Artificial intelligence helps network security management and control in the energy industry
In the energy industry, with the help of artificial intelligence technology, we can create a more perfect security control system, build a three-dimensional and intelligent risk control operation management system, provide a security foundation for the construction of energy Internet enterprises, and achieve the goal of “perceptible security status, discoverable security problems and intelligent security strategy”.
Security state awareness: create a large situation awareness risk screen through data analysis and intelligent reports to realize real-time awareness of security state. Security problem discovery: business flow audit based on AI firewall, combined with big data analysis and artificial intelligence technology, monitors data export risk, sensitive data use risk, important data encryption risk, sensitive data access change and other risks. Based on AI vulnerability scanning, monitor the potential vulnerabilities of intelligent device system, IOT aware device counterfeiting, illegal port opening, microservice vulnerability, configuration file vulnerability, application component vulnerability, database weak password and other risks. Intelligent security strategy: give full play to the advantages of massive data and rich application scenarios, fully tap the potential value of users’ massive risk control data by building a risk control modeling platform with machine learning as the core technology, and complete the data value transformation, which can be used for risk factor screening, network attack behavior path analysis Network security protection model formulation and other risk control means provide important technical support to realize the intelligence of security strategy.
At present, artificial intelligence technology has many application needs, large technical advantages and good industrial development momentum in the field of network security. With the explosive growth of network security data, the optimization and improvement of deep learning algorithms and the significant improvement of computing power, artificial intelligence technology will become the core of the next generation of network security solutions, The application of artificial intelligence in the field of network security will show great leap forward development.