一种基于多模态数据融合的网络通信风险动态识别方法
By using an improved reversible residual network and a time capsule-style immune cloning algorithm for multimodal data fusion, the shortcomings of existing technologies in network communication risk identification are addressed, enabling real-time, accurate risk assessment and dynamic updates in complex network environments.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHANGSHA HONGZHENG TECHNOLOGY CO LTD
- Filing Date
- 2025-12-22
- Publication Date
- 2026-07-17
AI Technical Summary
Existing network security technologies struggle to perform real-time and accurate multimodal data fusion identification of network communication risks in complex, heterogeneous, and dynamically changing network environments, especially when faced with encrypted, obfuscated, or segmented hidden risky communication behaviors, where their identification capabilities are insufficient.
An improved reversible residual network and a time capsule-style immune cloning algorithm are employed to extract features and characterize risks through multimodal data fusion. Combined with reversible reconstruction, controllable shrinkage mapping layer and two-layer immune synergy mechanism, dynamic identification and assessment of network communication risks are achieved.
It significantly improves the accuracy and adaptability of network communication risk identification, maintains robustness under high noise and covert attack modes, and enables real-time dynamic assessment and continuous optimization of risk status.
Smart Images
Figure CN121690803B_ABST