Securing Cognitive Radio Networks with Dynamic Trust against Spectrum Sensing Data Falsification
Securing Cognitive Radio Networks with Dynamic Trust against Spectrum Sensing Data Falsification
复制标题
通过动态信任保护认知无线电网络，防止频谱感知数据伪造
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Y. Sagduyu
中科院分区：
文献类型：
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作者：
Y. Sagduyu
针对协作感知中的频谱感知数据伪造（SSDF）攻击问题，提出了一种动态信任管理方案，以可靠地检测和缓解认知无线电网络中的此类攻击。次用户（SU）感测频谱以识别并动态地接入可用的主用户（PU）信道。为了提高感测可靠性，SU发送它们的感测报告（受制于个体频谱传感器的感测误差，例如，能量检测器）发送到融合中心，在融合中心，感测报告被组合以识别信道状态（空闲或忙碌）。三种类型的SU被认为是：（i）正常用户报告他们的感知结果诚实，（ii）攻击者报告他们的感知结果不准确的形式随机开关攻击，（iii）无关用户观察独立的频谱事件。在融合中心检查感知结果与预定传输的信道结果（在可能的反馈错误下获得）的一致性，并使用贝叶斯规则更新每个用户的概率信任。然后，动态确定最佳决策规则的合作感知与新的信任分配。分别在高斯信号假设和实际无线电收集的无线传输数据下评估性能。结果表明，动态信任管理可靠地检测用户类型，消除SSDF攻击的影响。与所有用户都被默认为正常用户的情况相比，感知错误概率和吞吐量都得到了显着提高。随着认知无线电网络中攻击者或无关用户数量的增加，这种性能增益得以保持。
The paper addresses the problem of spectrum sensing data falsification (SSDF) attacks in cooperative sensing and develops a dynamic trust management scheme to reliably detect and mitigate such attacks in cognitive radio networks. Secondary users (SUs) sense the spectrum to identify and dynamically access the available primary user (PU) channel. To improve sensing reliability, SUs send their sensing reports (subject to sensing error of individual spectrum sensor, e.g., Energy detector) to a fusion center, where sensing reports are combined to identify the channel state (idle or busy). Three types of SUs are considered: (i) normal users reporting their sensing results honestly, (ii) attackers reporting their sensing results inaccurately in form of random on off attacks, (iii) irrelevant users observing independent spectrum events. The consistency of sensing results is checked at the fusion center with channel outcome of scheduled transmissions (obtained under possible feedback errors) and the probabilistic trust of each user is updated with Bayes rule. Then, the optimal decision rule for cooperative sensing is determined dynamically with new trust assignments. Performance is evaluated separately under Gaussian signal assumption and with wireless transmission data collected with actual radios. Results show that dynamic trust management reliably detects user types and eliminates effects of SSDF attacks. Both the sensing error probability and the throughput are significantly improved compared to the case when all users are by default trusted to be normal users. This performance gain is maintained as the number of attackers or irrelevant users increases in the cognitive radio network.