The application value of artificial intelligence in the field of network security
In just over half a century of development, artificial intelligence has achieved a leap from academic theory to industrial application, and has achieved industrial empowerment in many fields such as finance, medical care, education, and energy. The research and application of artificial intelligence technology in the field of network security has also attracted the attention of various technology companies, and its application value has begun to emerge.
1. The 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 to learn independently and can cope with unknown attack methods and rapidly changing cyber risk environment. Second, artificial intelligence technology is based on big data technology and has the ability to efficiently process massive data, making it possible to process massive network security traffic data. Third, artificial intelligence has the ability to automate and intelligent decision-making, which can minimize the intervention of “human factors”, and improve the efficiency and stability of network security operations while reducing personnel costs.
The main applications of artificial intelligence in the field of network security include AI firewalls, AI vulnerability scanning, and AI security management and control platforms. The new-generation robot firewall (AI-WAF) realizes a 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 filtering and risk intelligent blocking. In terms of vulnerability scanning, combined with artificial intelligence technology, the method of deep learning is applied to security detection, actively mining unknown vulnerabilities, “detecting and discovering” vulnerabilities, and enhancing the ability to help users “manage vulnerabilities” and focus on “repair”. A true closed loop of vulnerability repair to deal with the ever-changing situation of security vulnerabilities. At the same time, the AI security management and control platform based on artificial intelligence technology integrates data security risks, business security risks, audit security risks, terminal security risks and transaction processing full-process management and control, with the help of device fingerprints, biological probes, decision-making engines, and rule engines. , situation awareness, form a security management center to coordinate business management and control, strengthen security management and control capabilities and expansion capabilities, improve business risk control identification capabilities, and assist enterprises and organizations to achieve digital security management and control.
2. Cybersecurity applications of artificial intelligence in the fields of finance and energy
1. Artificial intelligence helps bank mobile application network security protection
As the vanguard of the digital economy, financial technology has developed rapidly in recent years. While the bank’s virtual branch/smart branch service has been diversified, security risks have continued to expand. App program security, operation security, network security and business fraud security problems have emerged. Vulnerability attacks, application tampering, “scraping wool”, plundering promotional resources, sensitive Security incidents such as information leakage emerge in an endless stream. In the face of emerging security impacts, traditional security technologies are obviously one step behind emerging threats. Problems such as constantly looking for loopholes, patching, lag in response, passive defense, and complex management are prominent. Customers need more advanced and innovative dynamic security solutions. Ensure the uninterrupted operation of online business.
Artificial intelligence can be applied to mobile application security reinforcement and Internet financial situational awareness services, to build a “mobile app situational awareness platform”, to conduct network-wide security monitoring from multiple perspectives such as applications, industries, channels, and regions, and to collect data from multiple information sources. Applying artificial intelligence analysis and modeling technology to perform correlation and combination modeling from multiple dimensions such as application threats, application vulnerabilities, application hazards, industry distribution, channel distribution, and geographical distribution can improve the effectiveness and accuracy of data, and obtain a network-wide result. Situational awareness data and threat warning data. Visualization technology is then used to generate a situational assessment report and a comprehensive network situational map to provide auxiliary decision-making information for security managers.
2. Artificial intelligence helps energy industry network security management and control
In the energy industry, artificial intelligence technology can be used to build a more complete security management and 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 “perceivable security status, discoverable security problems, and The goal of “Intelligent Security Policy”.
Security status awareness: Create a large screen of situational awareness and risk through data analysis and intelligent reports to realize real-time awareness of security status. Security problem discovery: AI firewall-based business traffic audit, combined with big data analysis and artificial intelligence technology, monitors data export risks, sensitive data usage risks, important data encryption risks, sensitive data access changes and other risks. Based on AI vulnerability scanning, it can monitor the potential risks of smart device system vulnerabilities, IoT-aware device counterfeiting, illegal port opening, microservice vulnerabilities, configuration file vulnerabilities, application component vulnerabilities, database weak passwords and other risks. Intelligent security strategy: Give full play to the advantages of massive data and rich application scenarios, build a risk control modeling platform with machine learning as the core technology, fully tap the potential value of users’ massive risk control data, complete the transformation of data value, and become a risk factor Screening, network attack behavior path analysis, network security protection model formulation and other risk control methods provide important technical support to realize intelligent security policies.
At present, artificial intelligence technology has many application needs in the field of network security, has great technical advantages, and has a good momentum of industrial development. With the explosive growth of network security data, the optimization and improvement of deep learning algorithms, and the substantial improvement of computing power, artificial intelligence technology will inevitably As the core of next-generation network security solutions, the application of artificial intelligence in the field of network security is bound to develop by leaps and bounds.