| 利用分组过滤加强SSDF攻击防御的方案设计 |
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| 引用本文： | 陈青青,季薇,郑宝玉.利用分组过滤加强SSDF攻击防御的方案设计[J].信号处理,2018,34(5):558-565. |
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| 作者姓名： | 陈青青 季薇 郑宝玉 |
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| 作者单位： | 南京邮电大学通信与信息工程学院 |
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| 基金项目： | 国家自然科学基金(61471200,61603197,61671253);南京邮电大学科研基金(NY215104)资助课题;江苏高校优势学科建设工程资助项目
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| 摘 要： | 在协作频谱感知网络中,设备故障、信道阴影衰落和噪声等会导致频谱感知器(如手机、平板等)发送的信息不可靠,而恶意用户在协作频谱感知网络中,也会发送错误的感知信息以混淆视听,干扰诚实用户的判决结果。不可靠消息在邻居用户间的传递必将导致感知结果产生偏差和错误,大大降低了协作频谱感知的效率。为解决上述问题,本文将置信传播算法和信誉模型相结合,提出一种基于次用户分组的频谱感知数据伪造(SSDF,Spectrum Sensing Data Falsification)攻击防御方案。该方案分两个阶段对不可靠信息进行过滤:首先,在频谱感知阶段,通过置信传播算法对次用户进行分组,过滤掉因设备故障等因素产生的不可靠用户,剩余用户则视为正常工作用户进行数据融合。然后,在数据融合阶段,根据以信誉值作为权重因子的置信传播算法来计算最终的判决值。本文所提方案分别在感知阶段和融合阶段采取了防御措施,可有效地过滤网络中的不可靠信息,减小恶劣的频谱环境对次用户感知结果的影响。仿真结果表明,本文所提方案迭代次数少、收敛快,有效地减弱了SSDF攻击带来的损害,提高了感知结果的准确性、增强了认知无线网络的安全性。
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| 关 键 词： | 分布式协作频谱感知 分组 置信传播 信誉模型 频谱感知数据伪造 |
| 收稿时间： | 2017-12-25 |
Scheme Design for Enhancing SSDF Attack Defense with Packet Filtering |
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| Affiliation: | College of Telecommunication & Information Engineering, Nanjing University of Posts and Telecommunications |
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| Abstract: | In cooperative spectrum sensing networks, the information sent by spectrum sensors (such as mobile phones, tablets, etc.) is often unreliable due to equipment failures, channel shadow fading and noise. Malicious users in collaborative spectrum sensing network also send erroneous perceptions to confuse and interfere with the decisions of honest users. The transmission of unreliable messages between neighbor nodes will inevitably lead to the deviation and error of the perceived results and greatly reduce the efficiency of cooperative spectrum sensing. In order to solve the above problems, this paper combines belief propagation algorithm with reputation model, and proposes a scheme based on secondary users grouping to defense against SSDF attack. The scheme filters out unreliable information in two phases: firstly, in spectrum sensing phase, grouping the secondary users according to belief propagation algorithm can filter out the users which are unreliable due to equipment failure and other factors. The remaining users will be regarded as normally working users for data fusion. Then, in data fusion phase, reputation values will be used as weighting factors in the belief propagation algorithm to calculate the final decision value. The scheme proposed in this paper adopts defensive measures respectively in the spectrum sensing phase and the data fusion phase, which can effectively filter the unreliable information in the network and reduce the impact of the harsh spectrum environment on the secondary users. Simulation results show that the proposed scheme has fewer iterations and faster convergence. And it can effectively reduce the damage caused by SSDF attacks, improve the accuracy of sensing results and enhance the security of cognitive radio networks. |
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