Dynamic reverse verification network security system driven by artificial intelligence and network security method

By using an AI-driven dynamic reverse verification network security system, which combines AI behavior analysis and dynamic verification mechanisms to generate unique verification strings and integrate them with the content delivery network, the system addresses the shortcomings of traditional network security systems in responding to new and internal threats, achieving rapid response and comprehensive network security defense.

CN121966908APending Publication Date: 2026-05-01ECCOM INTELLIGENCE CO LTD +1
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Patent Information

Application Number
CN202511539979.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Priority Date
2024-10-30
Filing Date
2025-10-27
Publication Date
2026-05-01

AI Technical Summary

Technical Problem

Traditional cybersecurity systems have limited capabilities in dealing with new and complex cyber threats, especially attacks from within organizations, and traditional verification methods are vulnerable to attack, necessitating more secure and dynamic verification mechanisms.

Method used

An AI-driven dynamic reverse verification network security system is adopted, which combines AI-driven behavioral analysis and dynamic verification mechanisms to enhance security by generating unique 32-byte verification strings (au strings), integrates a content delivery network (CDN) to mitigate large-scale DDoS attacks, uses AI to monitor user behavior patterns to identify internal threats, and initiates a layered defense response.

Benefits of technology

It provides comprehensive defense against both external and internal threats, enables rapid response to and mitigation of cyberattacks, enhances the security and availability of enterprise networks, and offers a dynamic, adaptable, and robust cybersecurity solution.

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Abstract

The invention discloses an artificial intelligence-driven dynamic reverse verification network security system and a network security method, which are used for actively detecting and relieving network threats in an enterprise network environment. The network security system integrates AI-driven behavioral analysis to monitor and model normal network activity to identify abnormal patterns that may indicate potential security vulnerabilities. The network security system executes a reverse verification algorithm to generate a unique 32-byte verification string by combining a disguised timestamp, a random hexadecimal number, and a search string dynamically derived from an ASCII random string table. This mechanism enhances security by preventing predictive and replay attacks, thereby ensuring robust verification. When abnormal activity or verification failure is detected, the network security system initiates hierarchical defense responses, including packet filtering, IP blocking, execution of custom threat neutralization scripts, and integration of the content delivery network to combat distributed denial of service attacks.
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