协作频谱感知中抗SSDF攻击的认知用户不确定性行为评估

针对认知用户的协作感知行为不确定性,提出一种基于D-S证据理论的信任评估机制——Hard Guard,为硬判决融合算法提供保护,使其成为具有抑制频谱感知数据伪造(SSDF)攻击能力的可信协作频谱感知算法。Hard Guard采取感知数据预处理措施,在融合之前有效过滤虚假感知数据,规避了恶意用户的影响。仿真结果表明,Hard Guard能使硬判决融合算法面对SSDF攻击时保持较好的感知性能。     

利用SSDF攻击特征的加权分布式频谱感知算法

协作频谱感知可以提高频谱感知的可靠性,但易遭到篡改感知数据(Spectrum Sensing Data Falsification,SSDF)攻击。该文利用SSDF攻击特征,判断邻居节点发送值是否是恶意状态值,并提出一种加权分布式协作频谱感知算法。该算法根据状态值在本地节点网络中的偏离程度,设定其融合权值。仿真结果表明,所提算法在节点收敛率和鲁棒性两方面,比基于梯度的协作频谱感知算法和基于最大差值的协作频谱感知算法都有所提升,检测性能也因此显著提高。      

可信的反馈声誉保护协作频谱感知软判决算法

协作频谱感知中信任机制的引入,起到了抑制恶意用户频谱感知数据伪造( SSDF)攻击行为的作用。然而,数据融合中心不加区分地接收协作感知结束后的反馈信息,为恶意用户带来了实施“掺沙子”攻击的机会。恶意用户向数据融合中心反馈错误的主用户频谱状态,使信任机制不能得出准确的信任值。为此,提出了一种基于反馈声誉的信任机制,考虑反馈中的个体性特征,引入反馈声誉的思想来量化认知用户信任值。同时,将信任值量化结果用于权重经典软判决算法———序贯概率比检测( SPRT)算法,消除SSDF恶意用户参与软判决数据融合的影响,形成可信序贯概率比检测算法( FSPRT)。仿真结果表明FSPRT算法的性能优于传统SPRT算法,能有效降低网络信任值计算误差,并保持较好的感知性能。     

合作频谱感知安全技术研究

频谱感知是认知无线电实现动态频谱接入的前提和关键技术。由于阴影效应和多径衰落等因素,单个认知用户的频谱感知的结果可能不可靠,因此通过多个认知用户检测结果的融合来提高频谱感知的性能,即合作频谱感知。目前,合作频谱感知存在两类安全威胁：主用户假冒攻击（IE,Incumbent Emulation）和频谱感知数据篡改攻击（SSDF,Spectrum Sensing Data Falsification）。由于这两种攻击的存在,将会大大降低频谱感知的性能,减少认知用户接入空闲授权频段的机会。因此,有必要对这两类攻击开展相关的防御技术研究。     

可防御SSDF攻击的宽带压缩频谱感知

SSDF（Spectrum Sensing Data Falsification）攻击是认知无线网络中对频谱感知性能危害最大的攻击方式之一。基于认知无线网络中信号频域的固有稀疏性,本文结合了压缩感知(CS)技术与平均一致(average consensus)算法,建立了可防御SSDF攻击的分布式宽带压缩频谱感知模型。本文建立了次用户的声望值指标,用以在分布式信息融合的过程中更加准确地排除潜在的恶意次用户影响。在感知阶段,各个CR节点对接收到的主用户信号进行压缩采样以减少对宽带信号采样的开销和复杂度,并做出本地频谱估计。在信息融合阶段,各CR节点的本地频谱估计结果以分布式的方式进行信息融合,排除潜在恶意次用户的影响,得到最终的频谱估计结果。仿真结果表明,本文提出的分布式频谱感知模型可以有效地抵御SSDF攻击,提高了频谱感知的性能。      

协作频谱感知中的SSDF攻击及其对策研究

协作频谱感知是认知无线电中实现频谱有效利用的关键环节,但协作频谱感知由于其聚集感知数据的特点,为恶意用户提供了可乘之机。恶意用户可以通过实施频谱感知数据伪造(spectrum sensing data falsification,SSDF)攻击的方式,使认知无线电系统不能如实地根据外界环境进行动态的频谱切换。为深入理解SSDF攻击,掌握其防御对策的研究现状及发展趋势,从攻击手段、攻击形式和攻击策略3个角度细化出具体的SSDF攻击类型,总结了目前SSDF攻击的典型防御对策。同时,针对目前相关研究中所存在的问题,明确了一些有待继续研究的方向。     

CRN合作频谱感知SSDF攻击的博弈分析

由于认知无线电网络(CRN)的特点,合作频谱感知容易遭受各种不同的安全威胁。针对CRN合作频谱感知中的感知数据错误化(SSDF)攻击,利用博弈论分析了SSDF攻击者和数据融合中心在不同条件下的行为与收益,并研究了双方基于博弈论的最佳策略。数据融合中心采用本文所述的策略可以有效对抗SSDF攻击,且SSDF攻击者无法通过自身策略的调整获得更大的收益。     

一种信任度模糊分配的合作频谱感知算法

由于无线信道的多径衰落和阴影效应等因素,单个认知用户无法区分频段空闲还是授权用户的信号处于深度衰落中。合作频谱感知运用信息融合技术,通过融合多个认知用户的结果来提高频谱感知的性能。证据理论作为一种有效的不确定性推理方法,在合作频谱感知中已有较好的应用。本文将模糊集与证据理论相结合,提出一种信任度模糊分配的合作频谱感知的算法。各个认知用户首先进行本地能量检测,然后使用正态形隶属函数进行基本概率赋值,根据认知用户的检测结果分配信任度。融合中心接收所有认知用户的证据,按照Dempster组合规则进行融合,最后进行判决。仿真结果表明,信任度模糊分配的合作频谱感知算法在感知性能上或者在算法复杂度上要优于现有的证据理论合作频谱感知算法。      

抗SSDF攻击的一致性协作频谱感知方案

在分布式认知无线电网络中,一般很难找到合适的融合中心能够收集所有协作用户的感知信息,而且协作过程极可能遭到篡改感知数据(Spectrum Sensing Data Falsification,SSDF)攻击.鉴于此,该文提出了一种改进的一致性协作频谱感知方案.利用Metropolis迭代规则,各次用户仅依靠邻接点之间的...     

面向鲁棒频谱感知的模糊K-means++算法

恶意用户通过向数据融合中心发送伪造的频谱感知数据,解决自身频谱资源短缺问题,但会极大地降低频谱感知系统的检测概率。为了解决此问题,提出了基于模糊K means++的数据融合算法。该算法首先引入模糊处理机制处理样本的数据特征值,以此来增加样本间的差异性;然后将模糊处理后的数据发送到融合中心,融合中心采用离群点挖掘的方法排除恶意用户,并对保留下来的用户进行融合,使样本向量具有鲁棒性;最后运用K means++算法对样本向量进行聚类。该算法利用轮盘法选择聚类中心,可有效抵御恶意用户的攻击,提高系统感知性能;无需知晓信号与噪声的分布等一些先验信息,也避免了繁杂的门限推导。从仿真结果可以看出,该算法对抵御恶意用户攻击具有突出的效果,有效提升了协同频谱感知系统的稳定性和鲁棒性。     

基于信任节点辅助的安全协同频谱感知策略

在认知无线电网络中,多个用户相互协作进行频谱感知能有效地提高系统感知性能。然而这种协同方式也带来了新的安全隐患:当恶意用户出现时,现有协同感知方法无法确保感知结果的鲁棒性。本文针对这一问题,提出了一种基于信任节点辅助的安全协同感知策略。该策略通过借助网络中信任节点的感知结果,在用户域和时间域两个维度上消除恶意用户的影响,确保了算法在较多恶意用户环境中的稳定性。仿真结果表明,新算法的性能优于Kaligineedi所提算法,在恶意用户数目为网络用户总数一半时,仍能有效地进行协同感知,具有良好的鲁棒性。      

Distributed cooperative spectrum sensing based on reinforcement learning in cognitive radio networks

Spectrum sensing is an initial task for the successful operation of cognitive radio networks (CRN). During cooperative spectrum sensing, malicious secondary user (SU) may report false sensing data which would degrade the final aggregated sensing outcome. In this paper, we propose a distributed cooperative spectrum sensing (CSS) method based on reinforcement learning (RL) to remove data fusion between users with different reputations in CRN. This method regards each SU as an agent, which is selected from the adjacent nodes of CRN participating in CSS. The reputation value is used as reward to ensure that the agent tends to merge with high reputation nodes. The conformance fusion is adopted to promote consensus of the whole network, while it’s also compared with the decision threshold to complete CSS. Simulation results show that the proposed method can identify malicious users effectively. As a result, the whole CRN based on RL is more intelligent and stable.     

考虑恶意节点的CRN合作频谱感知方法

基于带有恶意节点的更为实际的频谱感知环境,研究了基于合作感知的频谱共享网络模型,次级用户将会根据合作感知结果动态地调整其发射功率。为了防止恶意节点对感知系统的感知性能造成严重影响,研究了如何进行合作感知以提高感知性能。在一定的检测概率和相关功率约束下,建立了一个以最大化次级网络的吞吐量为目标函数的优化问题。仿真实验首先突出说明了恶意节点数目对频谱感知影响重大,同时还表明无论是否存在恶意节点,提出的算法均可有效地计算出最优的感知时间和发射功率,且在降低最大干扰功率限制和最大发射功率限制时,网络的吞吐量是增大的。     

Fault-Tolerant Cooperative Spectrum Sensing Scheme for Cognitive Radio Networks

In order to solve the uncertainty resulting from shadowing effect and resist the attack from malicious cognitive radio (CR) users, we propose a fault-tolerant cooperative spectrum sensing scheme for CR networks, where an energy detection-based local spectrum sensing is performed at each CR user, a coefficient is used to weight each CR user’s sensing result, a linear weighted fusion process is performed at the fusion center (FC) to combine received sensing results. For a fault-tolerant cooperative spectrum sensing scheme, the most important issue is to distinguish whether the CR user is reliable or not. In this paper, a reputation-based cooperative mechanism is presented to alleviate the influence of the unreliable sensing results from CR users suffering shadowing and the false sensing data from malicious CR users on the detection result at the FC. In proposed fault-tolerant cooperative scheme, each cooperative CR user has a reputation degree which is initialized and adjusted by the FC and used to weight the sensing result from the corresponding user in the fusion process at the FC. And then, two reputation degree adjusting methods are presented to manage the reputation degree of each CR user. Simulation results show that the proposed scheme can not only weaken the harmful influence caused by malicious CR users, but also alleviate the corrupted detection problem resulting from destructive channel condition between the primary transmitter and the CR user. Moreover, the detection performance of the fault-tolerant cooperative scheme, which has a feasible computational complexity and needs no instantaneous SNRs, is close to that of the optimal scheme.     

Cooperative wideband sensing based on cyclostationary features with multiple malicious user elimination

Spectrum sensing is an essential concept in cognitive radio. To overcome the single node sensing issue that arises due to channel impediments, cooperative/multinode sensing is being used. Although cooperation among multiple cognitive users enhances the sensing performance, presence of few malicious cognitive users may severely degrade the efficiency of the system. In this paper, generalized extreme studentized deviate (GESD) and adjusted box-plot (ABP) methods are introduced to increase the sensing reliability of cooperative network by eliminating multiple malicious cognitive users. The performance of the cyclostationary feature detection method is compared with the energy detection method under different channel impediments. The simulation results are carried out with false alarm probability of 0.01 and a detection probability of 0.9. The simulation results reveal that there is a significant improvement in cooperative sensing performance by elimination of multiple malicious user in the network.     

基于可信度的半双工协同频谱检测

提出了基于可信度的半双工协同频谱检测方案.该方案利用贝叶斯方法来确定协同用户的可信度,分别就具有单协同用户和多协同用户的半双工协同频谱检测进行了研究,分析了可信度对协同频谱检测的影响.分析和仿真结果表明,本文策略不但能提高检测概率、降低检测时间,还能排除故障用户对检测性能的影响、减少恶意用户的干扰.     

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to reach a wrong decision. This paper makes a review of secure cooperative spectrum sensing in cognitive radio networks. The main objective of these protocols is to provide an accurate resolution about the availability of some spectrum channels, ensuring the contribution from incapable users as well as malicious ones is discarded. Issues, advantages and disadvantages of such protocols are investigated and summarized.     

基于ESD测试的无线电网络抗SSDF攻击协作频谱感知方案

针对认知无线电网络中协作频谱感知容易遭受数据伪造攻击的问题,提出一种基于检验统计和极端学生化偏差检验法的协作频谱感知方案。首先,将差分进化算法与加权增益合并软决策融合方法相结合,形成一种高效的节点决策融合机制。然后,在协作感知中,根据节点的软决策数据,利用检验统计消除故障认知节点。最后,利用提出的改进型ESD检验法消除恶意认知节点,从而形成全局决策。仿真结果表明,该方案在协作感知中能够有效过滤SSDF攻击数据,具有较低的误检测率。     

Weight sequential log-likelihood ratio detect algorithm with malicious users removing

Due to the openness of the cognitive radio network, spectrum sensing data falsification (SSDF) can attack the spectrum sensing easily, while there is no effective algorithm proposed in current research work, so this paper introduces the malicious users removing to the weight sequential probability radio test (WSPRT). The terminals' weight is weighted by the accuracy of their spectrum sensing information, which can also be used to detect the malicious user. If one terminal owns a low weight, it can be treated as malicious user, and should be removed from the aggregation center. Simulation results show that the improved WSPRT can achieve higher performance compared with the other two conventional sequential detection methods under different number of malicious users.