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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.

Today is the era of intelligent cognitive radio network technology that allows the utilization of available spectrum efficiently by allocation of the spectrum dynamically to unlicensed users. The technology utilizes the free spectrum bands which are not being used by the authorized users without causing any obstruction to the existing transmission. Cognitive radio technology promises interference free spectrum access by users. However, there exist many security attacks on spectrum impacting on spectrum access probability and network services. This will result in significant degradation of the performance of a cognitive radio network. This paper discusses the several attacks on different layers, their motives and various mechanisms to prevent them. The specific threats based on issues with configurability are explored on the basis of the related work. In this paper the role of authentication mechanism to prevent the attacks for hassle free spectrum utilization and its performance in resolving the cognitive network security issues are discussed. The need for effective sensing and decision mechanisms to enhance the security of cognitive networks is demonstrated in the paper. Hence, the presented paper gives an overview of existing research efforts at first and secondly, the research challenges are identified that can address the ways to secure the cognitive radio network and lastly the countermeasures in cognitive radio network security strategies are demonstrated.

Cognitive Radio Network (CRN) is the future scope wireless technology that aims to enhance the spectrum utilization. It meets out the increasing demand in spectrum access by all possible wireless applications and services. Security is an important issue but not focused much in CRN. In this research, the detection and defensive approach for Primary User Emulation Attack (PUEA) is presented. In order to secure cognitive radio network against PUEA, two level of detection algorithm is proposed. Energy detection with three threshold value and localization technique is used to detect the attackers. To enhance the Quality of Service (QoS) of the Secondary Users (SU), guard channel is allocated to the secondary user by the fusion center. This process is carried out whenever the communication between the SUs is intervened by the licensed primary user or an attacker.

Cognitive radio technology addresses the problem of spectrum scarcity by allowing secondary users to use the vacant spectrum bands without causing interference to the primary users. However, several attacks could disturb the normal functioning of the cognitive radio network. Primary user emulation attacks are one of the most severe attacks in which a malicious user emulates the primary user signal characteristics to either prevent other legitimate secondary users from accessing the idle channels or causing harmful interference to the primary users. There are several proposed approaches to detect the primary user emulation attackers. However, most of these techniques assume that the primary user location is fixed, which does not make them valid when the primary user is mobile. In this paper, we propose a new approach based on the Kalman filter framework for detecting the primary user emulation attacks with a non-stationary primary user. Several experiments have been conducted and the advantages of the proposed approach are demonstrated through the simulation results.

Currently, there are several ongoing efforts for the definition of new regulation policies, paradigms, and technologies aiming a more efficient usage of the radio spectrum. In this context, cognitive radio (CR) emerges as one of the most promising players by enabling the dynamic access to vacant frequency bands on a non-interference basis. However, the intrinsic characteristic of CR opens new ways for attackers, namely in the context of the effective detection of incumbent or primary users (PUs), the most fundamental and challenging requirement for the successful operation of CR networks. In this article, we provide a global and integrated vision of the main threats affecting CR environments in the context of the detection of primary users, with a particular focus on spectrum sensing data falsification and primary user emulation attacks. We also address solutions and research challenges still required to address such threats. Our discussion aims at being complete and self-contained, while also targeting readers with no specific background on this important topic of CR environments. It is, as far as our knowledge goes, the first work providing a global and clear vision of security threats and countermeasures in the context of primary user detection in CR.

In this paper, we propose a novel algorithm for primary user emulation attack detection and removal in cognitive radio networks, which are driven by chaotic tag-based sequencing for communication. Our proposed approach demonstrates the use of the look-up table-based challenge sequences which are monitored by the cognitive base station and act as the first line of defense against any primary user emulation attacker. This ensures that almost all of the attackers are suppressed, and for the remaining attackers if any, we use a tag-based chaotic communication system, wherein each of the requests from secondary users is sent like a chaotic noise sequence on the channel, and the receiving entity decodes this sequence in order to get the signal communicated by an authorized transmitter. If there is any communication by an attacker, then it is detected immediately, as none of the receiving entities can decode the signals sent by these unwanted attacker nodes. This ensures that our system guarantees greater than 99% detection and identification of attackers in primary user emulation attacks.

Cognitive radio (CR) systems have been proposed for efficient usage of spare spectrum licensed to primary systems. This leads to the issue of providing as much spectrum to CR users as possible while not degrading the quality of service (QoS) of primary users of the spectrum. This paper proposes a novel cooperation scheme between primary and CR users to guarantee QoS of primary users up to the cell edge while making the licensed spectrum available for opportunistic access by the CR users. We suggest that the primary users at the cell edge, who have poor QoS, should allow secondary users to access their spectrum, while at the same time, the secondary users would help to enhance the primary users QoS using superposition coding on the primary users transmissions. Thus the proposed method can provide a so called “win-win strategy” by benefiting both primary and CR users. The proposed cooperative access scheme in cognitive radios solves efficiently the sum-rate maximization problem on cognitive Gaussian Multiple Access Channels (GMACs) for power allocation of primary systems that cooperates with CR systems in a distributed fashion. We solved the problem using iterative Jacobian method in a distributed manner. A totally asynchronous distributed power allocation for sum-rate maximization on cognitive GMACs is suggested. Numerical results show that the QoS of primary users at the cell edge is improved by the proposed cooperative access scheme.

The rapid advancement of wireless communication combined with insufficient spectrum exploitation opens the door for the expansion of novel wireless services. Cognitive radio network (CRN) technology makes it possible to periodically access the open spectrum bands, which in turn improves the effectiveness of CRNs. Spectrum sensing (SS), which allows unauthorized users to locate open spectrum bands, plays a fundamental part in CRNs. A precise approximation of the power spectrum is essential to accomplish this. On the assumption that each SU’s parameter vector contains some globally and partially shared parameters, spectrum sensing is viewed as a parameter estimation issue. Distributed and cooperative spectrum sensing (CSS) is a key component of this concept. This work introduces a new component-specific cooperative spectrum sensing model (CSCSSM) in CRNs considering the amplitude and phase components of the input signal including Component Specific Adaptive Estimation (CSAE) for mean squared deviation (MSD) formulation. The proposed concept ensures minimum information loss compared to the traditional methods that consider error calculation among the direct signal vectors. The experimental results and performance analysis prove the robustness and efficiency of the proposed work over the traditional methods.

In this paper, we propose a new protocol called LoRaCog to introduce the concept of Cognitive Radio (CR) in the LoRa network. LoRaCog will enable access to a wider spectrum than that of LoRaWAN by using the unutilized spectrum and thus has better efficiency without impacting the end devices’ battery consumption. LoRa networks are managed by LoRaWAN protocol and operate on the unlicensed Industrial, Scientific and Medical (ISM) band. LoRaWAN is one of thriving protocols for Low-Power Wide-Area Networks (LPWAN) implemented for the Internet of Things (IoT). With the growing demand for IoT, the unlicensed spectrum is expected to be congested, unlike the licensed spectrum, which is not fully utilized. This can be fairly balanced by applying CR to the LoRa network, where the End Devices (EDs) may change the operating channel opportunistically over the free/available licensed spectrum. Spectrum sensing, channel selection and channel availability relevance become essential features to be respected by the proposed protocol. The main objective of adding CR to LoRaWAN is reducing the congestion and maintaining LoRaWAN’s suitability for battery-operated devices. This is achieved by modifying LoRaWAN components such as the ED receive window RX2 rearrangement, spectrum sensing functionality by gateway (GW) for identifying unused channels, and reaching a decision on the unused channels by network server (NS). These changes will create LoRaCog meeting spectrum efficiency and maintain the same level of battery consumption as in LoRaWAN. Numerical simulations show a significant decrease in the rejected packet rate (more than 50%) with LoRaCog when more EDs use cognitive channels. As the results prove, LoRaWAN can reach above 50% rejected packets for the simulated environment versus 24% rejection for LoRaCog using only one additional channel (means total two channels). This means that the system can eliminate rejected packets almost completely when operating over the possible many channels. As well, these results show the flexibility in the system to utilize the available frequencies in an efficient and fair way. The results also reveal that a lower number of GWs is needed for LoRaCog from LoRaWAN to cover the same area.

In this paper, dual-hops and multi-hops cognitive radio Ad Hoc networks has been considered. It is vital mentioning that the primary user interference effect on the secondary user has also been considered. The design of the problem is to achieve an optimal solution for channel allocation and power in dual and multi hop in Cognitive Radio Ad Hoc Networks (CRNs). The main goal is to minimize the outage probability and increasing the length of your network life time, while simultaneously observing the transmission power constraints and the threshold of interference with the primary user. This problem was solved using the standard technique of solving convex optimization problem and weighted bipartite matching. All of the analysis is for both DF, and amplifying and transmission AF protocols. Comparison and measurement of the systems performance is outage probability. Simulation results have shown that the proposed scheme not only minimizes the outage probability compared to existing ones, but also reduces PU interference and saves overall transmission efficiency by Secondary Users.