Throughput of cognitive radio networks with improved energy detector under security threats

Spectrum sensing in cognitive radio networks (CRNs) is subjected to some security threats such as primary user emulation (PUE) attack and spectrum sensing data falsification (SSDF) attack. In PUE attack, a malicious user (MU_PUE) transmits an emulated primary signal throughout the spectrum sensing interval to secondary users (SUs) to forestall them from accessing the primary user (PU) spectrum bands. In SSDF attack, malicious users (MU_SSDF) intentionally report false sensing decisions to the fusion center (FC) to influence the overall decision. While most of the existing literatures have studied the effects of these 2 types of attacks separately, the present paper evaluates the secondary network performance in terms of throughput under both the PUE and SSDF attacks with improved energy detectors (IEDs) where SU's spectrum access is hybrid, ie, either in overlay or in underlay mode. An analytical expression on throughput of SU under the simultaneous influence of both of these attacks is developed. Impact of several parameters such as IED parameter, attacker probabilities, and attacker strength on the throughput of SU is investigated. Performance of the present scheme is also compared with only PUE and only SSDF attacks. A simulation test bed is developed in MATLAB to validate our analytical results.     

Mitigating spectrum sensing data falsification attack in ad hoc cognitive radio networks

In a cognitive radio ad hoc network, there is no central authority. Hence, distributed collaborative spectrum sensing (CSS) plays a major role in achieving an accurate spectrum sensing result. However, CSS is sensitive to spectrum sensing data falsification (SSDF) attack, in which a malicious user falsifies its local sensing report before disseminating it into the network. To capture such abnormal behavior of a node, we present an approach for detecting SSDF attack based on dissimilarity score. A secondary user (SU) computes the dissimilarity score of its neighbors from the messages received from its h‐hop neighbors. Further, we also present how the proposed scheme can be used on the sequence of sensing reports to detect and isolate the malicious SUs on the fly.     

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。      

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。     

Channel assignment scheme in clustered multichannel cognitive radio networks with outdated CSI over Rayleigh fading channels

This work investigates channel assignment for cooperative spectrum sensing in multichannel cognitive radio networks, where the heterogeneity of primary user (PU) activity and the effect of varying channel condition on the received signal‐to‐noise ratio during cluster formation are considered. With the objective to minimize interference to the PU while enhancing multiple spectrum utilization of the secondary user (SU), an overlapping cluster‐based assignment is formulated into a nonlinear integer optimization problem. To obtain an efficient solution, the nonlinear integer problem is transformed into a mixed integer linear problem, based on which, this paper proposes an exact solution and then two new heuristic algorithms for suboptimal solutions, respectively. Furthermore, a comparative study of four different cluster head selection schemes with respect to their performance in cooperative spectrum sensing, under cluster's heterogeneity in terms of SUs distribution relative to PU transmitter location is presented. Based on the study, a robust cluster head selection scheme is proposed. Simulation results show that good sensing performance and increased opportunistic spectrum utilization in multichannel cognitive radio networks are two sides of a coin that depend on the ratio of the SUs to the number of PU channels. How far away the PU is from the cluster center is also seen to be key in the optimal selection of cluster heads in cooperative spectrum sensing.     

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。     

Recognition and elimination of SSDF attackers in cognitive radio networks

The nature of cognitive radio (CR) technology creates a lot of opportunities for attackers. When an attack occurs, the function of the primary network is affected and thus the overall system performance will be reduced. In the present paper, we introduce and simulate a novel method for identifying spectral sensing data falsification (SSDF) attack and recognizing the malicious users (MU), which we refer to as “Recognition and Elimination of SSDF Attackers”. Our proposed scheme uses the generalized likelihood ratio test (GLRT) approach for solving the MUs detection problem. In this method, we do not need previous information about the network and number of the MUs and secondary users (SUs). In addition to detecting the occurrence of an attack, our method can recognize attackers. By recognizing the MUs, their negative effect will be eliminated and the cognitive radio network (CRN) performance will return to normal condition. Consequently, our scheme can save resources by identifying the strategy of the known attackers. Simulation results reveal that our detection and recognition scheme is better than some of methods available.

     

Spectrum leasing based on Nash Bargaining Solution in cognitive radio networks

Cognitive radio is becoming an emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum resource. In this paper, we focus on the dynamic spectrum access of cognitive radio networks, in which the primary user (PU) and secondary users (SUs) coexist. In property-rights model, the PU has property of the bandwidth and may decide to lease it to secondary network for a fraction of time in exchange for appropriate remuneration. We propose a cooperative communication-aware spectrum leasing framework, in which, PU selects SUs as cooperative relays to help transmit information, while the selected SUs have the right to decide their payment made for PU in order to obtain a proportional access time to the spectrum. Then, the spectrum leasing scheme is cast into a Nash Bargaining Problem, and the Nash Bargaining Solution (NBS) can be used to fairly and efficiently address the resource allocation between PU and secondary network, enhancing both the utility of PU and secondary network. Numerical results show that spectrum leasing based on NBS is an effective method to improve performance for cognitive radio networks.     

一种SSDF攻击检测的证据理论合作频谱感知算法

现有的基于证据理论的合作频谱感知认为所有认知用户都是诚实的,没有考虑恶意用户的存在。当恶意用户篡改本地感知的结果,发送错误的数据到数据融合中心,将会降低合作频谱感知的性能,这种攻击称为频谱感知数据篡改（spectrum sensing data falsification,SSDF）攻击。由于恶意用户发送的证据与其它认知用户的证据存在差别,本文使用Jousselme距离来衡量证据的可信度,提出一种SSDF攻击检测算法。数据融合中心接收所有认知用户的证据,让可信度低的证据不参与融合判决,可信度高的证据根据可信度进行加权融合。仿真结果表明,所提出的SSDF攻击检测算法在恶意用户发起SSDF攻击时可以很好的改善频谱感知性能。      

认知无线电网络中基于信誉度的分层合作频谱感知方案（英文）

Cooperative spectrum sensing in cognitive radio is investigated to improve the detection performance of Primary User(PU).Meanwhile,cluster-based hierarchical cooperation is introduced for reducing the overhead as well as maintaining a certain level of sensing performance.However,in existing hierarchically cooperative spectrum sensing algorithms,the robustness problem of the system is seldom considered.In this paper,we propose a reputation-based hierarchically cooperative spectrum sensing scheme in Cognitive Radio Networks(CRNs).Before spectrum sensing,clusters are grouped based on the location correlation coefficients of Secondary Users(SUs).In the proposed scheme,there are two levels of cooperation,the first one is perfonned within a cluster and the second one is carried out among clusters.With the reputation mechanism and modified MAJORITY rule in the second level cooperation,the proposed scheme can not only relieve the influence of the shadowing,but also eliminate the impact of the PU emulation attack on a relatively large scale.Simulation results show that,in the scenarios with deep-shadowing or multiple attacked SUs,our proposed scheme achieves a better tradeoff between the system robustness and the energy saving compared with those conventionally cooperative sensing schemes.     

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.     

Towards trustworthy collaboration in spectrum sensing for ad hoc cognitive radio networks

Cognitive radio networks (CRN) make use of dynamic spectrum access to communicate opportunistically in frequency bands otherwise licensed to incumbent primary users such as TV broadcast. To prevent interference to primary users it is vital for secondary users in CRNs to conduct accurate spectrum sensing, which is especially challenging when the transmission range of primary users is shorter compared to the size of the CRN. This task becomes even more challenging in the presence of malicious secondary users that launch spectrum sensing data falsification (SSDF) attacks by providing false spectrum reports. Existing solutions to detect such malicious behaviors cannot be utilized in scenarios where the transmission range of primary users is limited within a small sub-region of the CRN. In this paper, we present a framework for trustworthy collaboration in spectrum sensing for ad hoc CRNs. This framework incorporates a semi-supervised spatio-spectral anomaly/outlier detection system and a reputation system, both designed to detect byzantine attacks in the form of SSDF from malicious nodes within the CRN. The framework guarantees protection of incumbent primary users’ communication rights while at the same time making optimal use of the spectrum when it is not used by primary users. Simulation carried out under typical network conditions and attack scenarios shows that our proposed framework can achieve spectrum decision accuracy up to 99.3 % and detect malicious nodes up to 98 % of the time.     

A game approach for cooperative spectrum sharing in cognitive radio networks

We consider the problem of cooperative spectrum sharing among primary users (PUs) and secondary users (SUs) in cognitive radio networks. In our system, each PU selects a proper set of SUs to serve as the cooperative relays for its transmission and in return, leases portion of channel access time to the selected SUs for their own transmission. PU decides how to select SUs and how much time it would lease to SUs, and the cooperative SUs decide their respective power levels in helping PU's transmission, which are proportional to their access times. We assume that both PUs and SUs are rational and selfish. In single‐PU scenario, we formulate the problem as a noncooperative game and prove that it converges to a unique Stackelberg equilibrium. We also propose an iterative algorithm to achieve the unique equilibrium point. We then extend the proposed cooperative mechanism to a multiple‐PU scenario and develop a heuristic algorithm to assign proper SUs to each PU considering both performance and fairness. The simulation results show that when the competition among SUs is fierce, the performance gap between our heuristic algorithm and the optimal one is smaller than 3%. Copyright © 2013 John Wiley & Sons, Ltd.     

一种基于信誉度的航空无线电协作频谱感知方法

摘要：传统的航空无线电协作频谱感知算法无法区分节点的性质（普通/恶意）,而新的加权序贯检测（weighted sequential probability ratio test,WSPRT）算法虽然解决了这个问题,但在具有频谱感知数据篡改（spectrum sensing data falsification,SSDF）攻击节点的环境中,无法保持高的感知正确率。提出了一种改进型WSPRT 算法,在传统的 WSPRT 算法基础上改进了信誉度奖惩方案,增加了临近时间内感知稳定度的量化。从实验仿真结果看,改进后的算法不仅时间复杂度更低,而且能够有效地识别恶意节点,对于恶意用户的判定更准确。     

Optimal Energy Harvesting-based Weighed Cooperative Spectrum Sensing in Cognitive Radio Network

In cognitive radio (CR) network, to improve spectrum sensing performance to primary user (PU) and decrease energy wastage of secondary user (SU) in cooperative spectrum sensing, an energy harvesting-based weighed cooperative spectrum sensing is proposed in this paper. The SU harvests the radio frequency (RF) energy of the PU signal and then converts the RF energy into the electric energy to supply the power used for energy detection and cooperation. The time switching model and power splitting model are developed to realize the notion. In the time switching model, the SU performs either spectrum sensing or energy harvesting at any time, while in the power splitting model, the received PU signal is split into two signal streams, one for spectrum sensing and the other one for energy harvesting. A joint optimization problem is formulated to maximize the spectrum access probability of the SU by jointly optimizing sensing time, number of cooperative SUs and splitting factor. The simulation results have shown that compared to the traditional cooperative spectrum sensing, the proposed energy harvesting-based weighed cooperative spectrum sensing can decrease the energy wastage obviously while guaranteeing the maximum spectrum access probability.     

Neighbor Detection-Based Spectrum Sensing Algorithm in Distributed Cognitive Radio Networks

Security issues of spectrum sensing have drawn a lot of attentions in Cognitive radio networks (CRNs). Malicious users can m islead the network to m ake wrong decision about the states of channels by tampering spectrum sensing data. To defense against Spectrum sens-ing data falsification (SSDF) attack, we propose a neighbor detection-based spectrum sensing algorithm in distributed CRNs, which can detect attackers with the help of neigh-bors during spectrum sensing to improve the accuracy of decision making. The proposed scheme can also guarantee the connectivity of the network. Simulation results illus-trate that the proposed scheme can defense against SSDF attacks effectively and reach the unified information of spectrum sensing data.     

Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks

Cognitive radio offers a promising technology to mitigate spectrum shortage in wireless communications. It enables secondary users (SUs) to opportunistically access low-occupancy primary spectral bands as long as their negative effect on the primary user (PU) access is constrained. This PU protection requirement is particularly challenging for multiple SUs over a wide geographical area. In this paper, we study the fundamental performance limit on the throughput of cognitive radio networks under the PU packet collision constraint. With perfect sensing, we develop an optimum spectrum access strategy under generic PU traffic patterns. Without perfect sensing, we quantify the impact of missed detection and false alarm, and propose a modified threshold-based spectrum access strategy that achieves close-to-optimal performance. Moreover, we develop and evaluate a distributed access scheme that enables multiple SUs to collectively protect the PU while adapting to behavioral changes in PU usage patterns. Our results provide useful insight on the trade-off between the protection of the primary user and the throughput performance of cognitive radios.     

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...     

Delay QoS Guaranteed Cooperative Double-Threshold Sensing Scheme in Cognitive Radio Networks

In cognitive radio networks, cooperation can greatly improve the performance of spectrum sensing. This paper proposes a delay (QoS) quality-of-service guaranteed cooperative spectrum sensing frame structure in which secondary users (SUs) conduct spectrum sensing and data transmission concurrently over two different parts of the primary user spectrum band. A double-threshold sensing scheme is employed in the local sensing step, only the SUs with reliable sensing information are allowed to transmit their “one bit” local decisions to the fusion center. The sensing performance and the SU transmission delay are analyzed in detail in this paper. Computer simulations show that the delay QoS guaranteed cooperative double-threshold sensing scheme could not only decrease the SU transmission delay but also save the reporting overhead of the SUs compared with the conventional detection method with one threshold.     

Enhancing the Spectrum Sensing Performance of Cluster-Based Cooperative Cognitive Radio Networks via Sequential Multiple Reporting Channels

In cluster-based cooperative cognitive radio networks (CCRNs), spectrum sensing and decision making processes to determine whether the primary user (PU) signal is present or absent in the network are very important and vital issues to the utilisation of the idle spectrum. The reporting time delay is a very important matter to make quick and effective global decisions for the fusion center (FC) in a cluster-based CCRNs. In this paper, we propose the concept of multiple reporting channels (MRC) for cluster-based CCRNs to better utilize the reporting time slot by extending the sensing time of secondary users (SUs). A multiple reporting channels concept is proposed based on frequency division multiple access to enhance the spectrum sensing performance and reduce the reporting time delay of all cluster heads (CHs). In this approach, we assign an individual reporting channel to each cluster for reporting purposes. All the SUs in each cluster sequentially pass their sensing results to the corresponding cluster head (CH) via the assigned single reporting channel, which extends the sensing time duration of SUs. Each CH uses the dedicated reporting channel to forward the cluster decision to the FC that makes a final decision by using the “K-out-of-N” rule to identify the presence of the PU signal. This approach significantly enhances the sensing time for all SUs than the non-sequential as well as minimize the reporting time delay of all CHs than sequential single channel reporting approach. These two features of our proposed approach increase the decision accuracy of the FC more than the conventional approach. Simulation results prove that our proposed approach significantly enhances the sensing accuracy and mitigate the reporting time delay of CH compared to the conventional approach.