一种基于感知数据特性的概率型SSDF攻击节点检测方法
By using a method for detecting SSDF attack nodes based on the characteristics of sensing data, and by utilizing the inconsistency of historical reporting data in two consecutive sensing time slots to calculate the decision quantity and threshold, the problem of insufficient detection of large-scale SSDF attacks in existing technologies is solved, achieving effective detection and network security assurance with low complexity.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- UNIV OF ELECTRONIC SCI & TECH OF CHINA SHENZHEN RES INST
- Filing Date
- 2022-12-29
- Publication Date
- 2026-07-17
AI Technical Summary
Existing defense mechanisms against SSDF attacks in cognitive radio networks are insufficient in large-scale probabilistic attack scenarios, and most rely on trusted fusion centers or additional information, making it impossible to effectively detect attack nodes.
By using a probabilistic SSDF attack node detection method based on the characteristics of sensing data, the inconsistency characteristics of historical reporting data received by the fusion center in two consecutive sensing time slots are utilized to calculate the inconsistency decision quantity and detection threshold, and to determine whether each sensing user is an attack node.
It achieves efficient detection with low computational complexity, large-scale probabilistic SSDF attack nodes, and ensures the security of cooperative spectrum sensing in cognitive radio networks.
Smart Images
Figure CN116056086B_ABST