scholarly journals An SETM Algorithm for Combating SSDF Attack in Cognitive Radio Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
S. Tephillah ◽  
J. Martin Leo Manickam

Security is a pending challenge in cooperative spectrum sensing (CSS) as it employs a common channel and a controller. Spectrum sensing data falsification (SSDF) attacks are challenging as different types of attackers use them. To address this issue, the sifting and evaluation trust management algorithm (SETM) is proposed. The necessity of computing the trust for all the secondary users (SUs) is eliminated based on the use of the first phase of the algorithm. The second phase is executed to differentiate the random attacker and the genuine SUs. This reduces the computation and overhead costs. Simulations and complexity analyses have been performed to prove the efficiency and appropriateness of the proposed algorithm for combating SSDF attacks.

2018 ◽  
Vol 7 (2.20) ◽  
pp. 335
Author(s):  
Shweta Alpna ◽  
Amrit Mukherjee ◽  
Amlan Datta

The proposed work illustrates a novel technique for cooperative spectrum sensing in a cognitive radio (CR) network. The work includes an approach of identifying secondary users (SUs) based on Hierarchical Maximum Likelihood (HML) technique followed by Vector Quantization. Initially, the arrangement of the SUs are been observed using HML with respect to a spatial domain and then the active SUs among them are identified using VQ. The approach will not only save the energy, but the decision of the real-time and dynamic cooperative communication network becomes more accurate as we can predict the behavior of SUs movement and spectrum sensing by each individual SU at that particular  place. The results and simulations of the real-time experiment justifies with the proposed approach. 


Frequenz ◽  
2012 ◽  
Vol 66 (7-8) ◽  
Author(s):  
Hang Hu ◽  
Ning Li ◽  
Youyun Xu

AbstractTo improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. We focus on the optimization of cooperative spectrum sensing in which multiple secondary users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in heterogeneous cognitive radio (CR) networks. Rayleigh fading and Nakagami fading are considered respectively in cognitive network I and cognitive network II. For each cognitive network, we derive the optimal randomized rule for different decision threshold. Then, the optimal decision threshold is derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each secondary user which is randomly distributed in the heterogeneous cognitive radio networks.


2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Hui Lin ◽  
Jia Hu ◽  
Chuan Huang ◽  
Li Xu ◽  
Bin Wu

Cognitive radio networks (CRNs) are an emerging wireless communications technique for resolving the significant spectrum scarcity problem. Despite their promising characteristics, CRNs also introduce new security threats, especially the internal attacks during the spectrum sensing and allocation process, which can degrade the efficiency of spectrum sensing and allocation. To address this issue, this paper proposes a distributed secure cooperative spectrum sensing strategy (DSCS) based on a dynamic reputation model to defend against attacks and provide reliable spectrum sensing. Moreover, the reputation values are used as weights in a novel distributed cheat-proof spectrum allocation strategy (DCSA) based on the Vickrey-Clarke-Groves (VCG) mechanism. Both theoretical analysis and simulation results indicate that the proposed DSCS and DCSA strategies can provide an effective countermeasure against the internal spectrum sensing data falsification (SSDF) attacks through enabling secondary users to obtain more accurate cooperative sensing results in adversarial environments.


2013 ◽  
Vol 347-350 ◽  
pp. 1773-1779
Author(s):  
Shou Tao Lv ◽  
Ze Yang Dai ◽  
Jian Liu

In cognitive radio networks (CRNs), the secondary users (SUs) need to continuously detect whether the primary users (PUs) occupy the spectrum. In order to improve the spectrum sensing accuracy, a novel reliable cooperative spectrum sensing strategy based on the detection results relayed twice from the secondary relays (SRs) to the secondary source (SS), referred to as CSS-DRT, is proposed in this paper. In this scheme, the spectrum sensing slot is divided into four equal sub-slots. In the first and third sub-slots, the SS and SRs detect the PU by themselves. Then, in the second sub-slot, if the SRs that detect the PU during the first sub-slot are more than or equal to a prespecified quantity, the corresponding SRs will send their flag signals (FSs) to the SS while the others keep quiet, where the FS is narrowband and indicates that the PU is present. Otherwise, if the SRs that detect the PU during the first sub-slot are less than the prespecified quantity, all the SRs will keep quiet in the second sub-slot. Meanwhile, the SS detects the PU based on the received signals from the PU and SRs. And, the SS uses the same method as employed in the second sub-slot to detect the PU in the last sub-slot wherein the SRs send their FSs based on their detections made during the third sub-slot. Finally, an ultimate decision is made by the OR ruler based on the SS detection results obtained during the spectrum sensing slot. Besides, we derive the closed-form expressions of the false alarm and detection probabilities for the proposed CSS-DRT scheme. In the end, simulation and numerical results show that our proposed scheme can achieve better performance than the non-cooperative method and an existing cooperative spectrum sensing method.


2021 ◽  
Author(s):  
Lamiaa Khalid

In this thesis, we focus on two important design aspects of cooperative spectrum sensing (CSS) in cognitive radio networks which are the selection criterion of cooperating secondary users and the fusion technique for combining their local sensing decisions. We propose a novel adaptive user-group assignment algorithm that addresses the problem of sensing accuracy-efficiency trade-off in group-based CSS with heterogeneous cooperating secondary users. The performance of the proposed algorithm is bounded by 4.2% of the optimal solution. Through extensive simulations, we demonstrate that the proposed algorithm can effectively improve the performance of CSS in terms of the opportunistic throughput, sensing overhead and the number of sensing rounds needed to discover an available channel. Considering the different detection performance of cooperating secondary users, we propose a novel reliability-based decision fusion scheme in which a weight is assigned to each secondary user's local decision based on its reliability. Since the knowledge of the local probabilities of detection and false alarm for each secondary detector may not be known in practice, we employ a counting process to estimate those probabilities based on past global and local decisions. We then formulate the problem of minimizing the network probability of sensing error and develop a dual search algorithm, based on a non-linear Lagrangian approach, to solve the formulated problem. Our simulation results show that the dual algorithm converges to the optimal value with zero duality gap using few numbers of iterations. We also show that the probability of error is reduced by 18% and 88% compared to the OR and AND fusion rules, respectively, when the number of secondary users is eight. We then address the practical concern of secondary users reporting correlated local decisions to the fusion center. For this scenario, we formulate the problem of minimizing the network probability of sensing error optimization problem and employ the genetic algorithm to jointly find the optimal K*-out-of-M fusion rule and the optimal local threshold for a certain correlation index. Simulation results show that the network probability of sensing error degrades as the degree of correlation between cooperating secondary users increases. We also study the problem of multiband cooperative joint detection in the presence of sensing errors due to time offset. We derive the aggregate opportunistic throughput and aggregate interference to primary users for multiband cooperative joint detection in the presence of time offset. Our numerical results demonstrate the negative impact of the time offset on the aggregate opportunistic throughput of multiband cooperative joint detection.


2021 ◽  
Author(s):  
Lamiaa Khalid

In this thesis, we focus on two important design aspects of cooperative spectrum sensing (CSS) in cognitive radio networks which are the selection criterion of cooperating secondary users and the fusion technique for combining their local sensing decisions. We propose a novel adaptive user-group assignment algorithm that addresses the problem of sensing accuracy-efficiency trade-off in group-based CSS with heterogeneous cooperating secondary users. The performance of the proposed algorithm is bounded by 4.2% of the optimal solution. Through extensive simulations, we demonstrate that the proposed algorithm can effectively improve the performance of CSS in terms of the opportunistic throughput, sensing overhead and the number of sensing rounds needed to discover an available channel. Considering the different detection performance of cooperating secondary users, we propose a novel reliability-based decision fusion scheme in which a weight is assigned to each secondary user's local decision based on its reliability. Since the knowledge of the local probabilities of detection and false alarm for each secondary detector may not be known in practice, we employ a counting process to estimate those probabilities based on past global and local decisions. We then formulate the problem of minimizing the network probability of sensing error and develop a dual search algorithm, based on a non-linear Lagrangian approach, to solve the formulated problem. Our simulation results show that the dual algorithm converges to the optimal value with zero duality gap using few numbers of iterations. We also show that the probability of error is reduced by 18% and 88% compared to the OR and AND fusion rules, respectively, when the number of secondary users is eight. We then address the practical concern of secondary users reporting correlated local decisions to the fusion center. For this scenario, we formulate the problem of minimizing the network probability of sensing error optimization problem and employ the genetic algorithm to jointly find the optimal K*-out-of-M fusion rule and the optimal local threshold for a certain correlation index. Simulation results show that the network probability of sensing error degrades as the degree of correlation between cooperating secondary users increases. We also study the problem of multiband cooperative joint detection in the presence of sensing errors due to time offset. We derive the aggregate opportunistic throughput and aggregate interference to primary users for multiband cooperative joint detection in the presence of time offset. Our numerical results demonstrate the negative impact of the time offset on the aggregate opportunistic throughput of multiband cooperative joint detection.


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