加密流量识别方法、装置、电子设备和存储介质
By combining sliding window detection with multiple randomness detection algorithms and the split-half expansion algorithm, the problem of low accuracy in identifying explicit and implicit fields in encrypted bitstream data is solved, achieving more efficient network protocol parsing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- INSTITUTE OF INFORMATION ENGINEERING CHINESE ACADEMY OF SCIENCES
- Filing Date
- 2023-11-15
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, the accuracy of identifying the explicit and implicit fields of encrypted bitstream data is low, resulting in low accuracy in parsing unknown network protocols.
The algorithm employs a sliding window-based detection process, using multiple randomness detection algorithms to perform randomness detection on the bitstream data. The detection results determine the locations of the dense-to-light boundary and the light-to-dense boundary, and the binary expansion algorithm is combined to accurately identify the light-to-dense field.
This improves the accuracy of identifying explicit and implicit fields in encrypted bitstream data, providing more accurate basic data for subsequent network protocol analysis and enhancing the accuracy of network protocol parsing.
Smart Images
Figure CN117792675B_ABST