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协作式感知可以提升感知精度,但也可能使系统暴露于可能存在的恶意用户的危险之下,甚至会有恶意用户对网络发起拒绝服务攻击.为此给出了一种新的检测算法——恶意用户检测算法(malicious users detection algorithm,MUDA).首先,通过感知服务器对次要用户进行多种感知测试,根据接收到的被测节点的信号强度估计该节点是否为恶意节点.然后,采取主动传输策略,提高其检测精度并降低其开销.最后,将其与当前算法进行性能对比,对比结果表明MUDA在提高精度的同时将感知操作导致的吞吐量损失降低了65%.
Collaborative awareness can improve the perceived accuracy, but may also expose the system to the danger of possible malicious users, and even malicious users will launch denial of service attacks on the network.Therefore, a new detection algorithm is given - Firstly, the perceptual server conducts a variety of perceptual tests for secondary users, and estimates whether the node is a malicious node according to the received signal strength of the measured node.After that, the active users (MUDA) Transmission strategy to improve its detection accuracy and reduce its overhead.Finally, compared with the performance of the current algorithm, the comparison results show that MUDA reduces the throughput loss of perceptual operation by 65% while improving the accuracy.