Secure Cognitive Radio Networks Research Articles

Analysis of Secure Cognitive Radio Network with Optimal Resource Management

During the last decade, Cognitive Radio Network (CRN) technology has been a significant advance in addressing the ever-increasing spectrum demand. As the number of licensed and unlicensed users in a network rises to complete a certain activity, the information exchange between various types of traffic becomes more complex and difficult. Congestion in CRN is also caused by the conflict among several users for channel access (PUs and SUs). In a very crowded network, many applications perform badly owing to packet collisions and, as a result, packet loss before significant buffer queue building. This circumstance is aggravated by an increase in network users. Congestion control is a vital and essential aspect of the present research issue in communication networks. Several recent reviews in the literature indicate that the congestion issue in the CRN has not been thoroughly studied. Thus, effective and efficient congestion control strategies are sought to optimize network resource usage and management. To prevent congestion, it is crucial for CRN to do research on the creation of an efficient congestion management system. This will improve the network's resource consumption and performance. "Performance improvement via efficient spectrum management through optimum resource management and congestion control in the CRN by mitigating different threats" is the primary target of this project. This research also focused on enhancing performance by addressing security issues in an IoT-based CRN environment. This study provides a comprehensive review of several similar studies and their limitations, which may be used to formulate a new research target.

Robust resource allocation for IRS‐assisted secure cognitive radio networks

In this paper, a robust resource allocation problem in an intelligent reflecting surface (IRS) assisted artificial noise (AN)-aided cognitive radio network is investigated. Considering that the channel state information (CSI) of the eavesdropper channel and interference channel cannot be perfectly known in practice, the aim is to minimise the power consumption of the secondary user transmitter (SU-TX) by jointly optimising the transmit beamforming and covariance matrix of AN at the SU-TX as well as the phase shifts of the IRS. The formulated problem is non-convex and challenging to tackle due to the coupling among multiple variables. An efficient alternative optimisation algorithm to solve it by exploiting the S-procedure and semi-definite relaxation. Simulation results demonstrate that the IRS helps in reducing the power consumption significantly even under imperfect CSI conditions.

Optimal Power Allocation for Achieving Secure Green Cognitive Radio Networks

In cognitive radio networks, wireless nodes adapt to the surrounding radio environment and utilize the spectrum of licensed users. The cognitive radio environment is dynamic, and wireless channels are accessible by both legitimate and illegitimate users. Therefore, maintaining the security of cognitive radio networks is a challenging task, which must be addressed thoroughly. Further, with the recent exponential surge in wireless nodes and associated high data rate requirements, energy consumption is also growing at an unprecedented rate. Hence, energy efficiency becomes an important metric that must be considered in the design of future wireless networks. Accordingly, by considering the great ecological and economic benefits of green wireless networks, this work focus on energy-efficient resource allocation in secure cognitive radio networks. Since physical-layer security is an emerging technique that improves the security of communication devices, in this paper, an ergodic secure energy efficiency problem for a cognitive radio network is formulated with a primary user, a secondary user, and an eavesdropper. As the formulated problem is non-convex, a concave lower bound is applied to transform the original non-convex problem into a convex one. Further, by adopting the fractional programming and dual decomposition techniques, optimal power allocation strategies are obtained with the aim of maximizing the ergodic secure energy efficiency of the secondary user with constraints on the average interference power and average transmit power. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.

Secrecy capacity results for a secure NOMA-based cognitive radio network with an external eavesdropper

In this paper, we investigate a secure cognitive radio network (CRN), which deploys non-orthogonal multiple access (NOMA) to deliver a mixed multicast and unicast traffic to the intended receivers, while keeping them secret from the eavesdroppers. This model represents a cognitive interference channel with an external eavesdropper (CIC-EE). In this model, there are one pair of primary nodes, one pair of secondary nodes, and an external eavesdropper. The primary transmitter multicasts a confidential message to both primary and secondary receivers, while trying to keep it secret from the eavesdropper. The secondary transmitter helps the primary user to deliver its message in exchange of transmission opportunity. The secondary message is unicasted to the secondary receiver, while concealing it from both primary receiver and the eavesdropper. This scenario models a NOMA-based overlay cognitive radio paradigm with an external eavesdropper. For this scenario, the achievable rate-equivocation region is obtained and its optimality is shown for a class of degraded channels. Then, the results obtained for the discrete memoryless channel are extended to the Gaussian channel model. Furthermore, by deploying numerical examples, a comparison is made between the proposed secure NOMA-based scheme, its orthogonal multiple access (OMA) based counterpart, and a cognitive interference channel without an external eavesdropper. It is shown that the NOMA-based method achieves significantly higher rates than its OMA based counterpart.

Energy-Efficient Resource Allocation for Secure Cognitive Radio Network With Delay QoS Guarantee

A joint resource allocation policy for an underlay multi-user secure cognitive radio network (CRN) adopting the time-division multiple-access scheme with the guarantee of the statistical delay quality-of-service is proposed in this paper. Through the problem formulation of the resource allocation for the multi-user secure CRN with perfect channel state information (CSI), the energy-efficient joint power and time optimization scheme is proposed, which aims at minimizing the β-fair cost functions subject to fairness, delay, and security constraints. Furthermore, considering the multi-user secure CRN with imperfect CSI, we also propose a robust resource allocation scheme and the tradeoff between the robustness and the achievable sum-power is analyzed. Numerical results show that the optimal resource allocation scheme with perfect CSI can effectively balance the tradeoff between the energy efficiency and the fairness and is superior to the other conventional resource allocation strategies. Moreover, the robust resource allocation policy with imperfect CSI makes the theoretical research much closer to the practical applications.

Spatiotemporal diversification by moving-target defense through benign employment of false-data injection for dynamic, secure cognitive radio network

The future of wireless technology struggles to cope with information and resource exchange among different users over various systems. Given the latest advances in Cognitive Radio (CR) networks, and Software Defined Radio (SDR), spectrum resources are shared between Primary Users (PU) and Secondary Users (SU) by enabling frequency hopping through dynamic reconfiguration of active frequency bands. The elasticity and dynamic re-programmability offered by that merge opened the doors for transformative evolutions towards more secure and reliable wireless communication. In this paper, we exploit such unique features to present a novel Moving-target defense technique enabling multidimensional spatiotemporal diversification of the SU's traffic to obfuscate signal transmission-patterns, and the transmitted data across the entire spectrum. Such obfuscation extremely complicates malicious signal traceability and eavesdropping. In time, we benignly inject false data into the communication stream to conceal the real data among the false. In space, we employ dynamic prioritized manipulations of the active frequency over time, hopping between all the frequencies available for the secondary user to access. Simulation results showed that for a powerful malicious user with multiple access points, and no pre-knowledge of the diversification patterns used by the system, it is very complicated to eavesdrop a meaningful portion of the signal or the data stream.

Energy Efficiency of Secure Cognitive Radio Networks with Cooperative Spectrum Sharing

Energy-efficient and secure wireless communications have recently earned tremendous interests due to economic, environmental, and military concerns. This paper investigates the tradeoff between the secrecy throughput and the energy efficiency in cognitive radio networks (CRNs), where primary and secondary users with different priorities of spectrum access can either interfere or cooperate with each other. To gain an understanding of the intricate effects that system parameters have on underlay network's performance, we exclusively focus on characterizing several key aspects that may have potential impacts on secure underlay CRNs, including the transmission power, the number of interfering users, and the designed interference resistance coefficient. Based on the obtained analytical results, we further propose a cooperative spectrum sharing paradigm to improve both the secrecy throughput and the energy efficiency of primary users. The main idea is that primary users allow secondary users to simultaneously access the licensed spectrum and in return, the secondary transmitter acts as both a relay for primary transmissions and a friendly jammer against eavesdropping, in case the primary transmission fails. Both theoretical and numerical results reveal that: (i) When the interference from secondary transmitters is small, there is an optimal transmission power that maximizes the secrecy throughput for primary users compared to CRNs without the security issue. (ii) When the interference from secondary transmitters is large, the secrecy throughput increases with the transmission power for primary users. (iii) The transmission power that maximizes the energy efficiency is smaller than that maximizes the secrecy throughput for primary users. (iv) The number of interfering users has a slight impact on the secrecy throughput and the energy efficiency of primary users due to the secondary power control. (v) The proposed cooperative paradigm is an efficient approach to boost both the secrecy throughput and the energy efficiency of primary users compared with the traditional non-cooperative spectrum sharing, and provides an alternative method to compensate for the interference caused by secondary users.

Secure cognitive radio networks with source selection and unreliable backhaul connections

In this study, the secrecy performance of cooperative half-duplex cognitive relay networks (CRNs) comprised of multiple primary users (PUs) and multiple eavesdroppers under the effect of unreliable wireless backhauls is studied. The authors consider relay networks with single relay assisting multiple sources under power constraints at PUs and secondary transmitters, and based on the availability of channel-state information at the sources, they propose two best source selection schemes, namely: (i) optimal source selection (OSS) and (ii) sub-optimal source selection (SoSS). For both scenarios, they obtain exact closed-form and asymptotic expressions for the system's outage probability and carry out numerical simulations to justify their analyses. From the results, source selection is proven to be capable of counteracting the negative impact of unreliable backhaul on CRNs. The secrecy performance limitations are also verified to be influenced by the backhaul reliability. Furthermore, OSS is more desirable compared to SoSS in low signal-to-noise ratio (SNR) regime, while the secrecy performance for both schemes converge to an asymptotic limit in high-SNR ranges.

Generalized Quadratic Matrix Programming: A Unified Framework for Linear Precoding With Arbitrary Input Distributions

This paper investigates a new class of nonconvex optimization, which provides a unified framework for linear precoding in single/multiuser multiple-input multiple-output channels with arbitrary input distributions. The new optimization is called generalized quadratic matrix programming (GQMP). Due to the nondeterministic polynomial time hardness of GQMP problems, instead of seeking globally optimal solutions, we propose an efficient algorithm that is guaranteed to converge to a Karush-Kuhn-Tucker point. The idea behind this algorithm is to construct explicit concave lower bounds for nonconvex objective and constraint functions, and then solve a sequence of concave maximization problems until convergence. In terms of application, we consider a downlink underlay secure cognitive radio network, where each node has multiple antennas. We design linear precoders to maximize the average secrecy (sum) rate with finite-alphabet inputs and statistical channel state information at the transmitter. The precoding problems under secure multicast/broadcast scenarios are GQMP problems, and thus, they can be solved efficiently by our proposed algorithm. Several numerical examples are provided to show the efficacy of our algorithm.

Dual Antenna Selection in Secure Cognitive Radio Networks

This paper investigates data transmission and physical-layer secrecy in cognitive radio (CR) networks. We propose to apply full-duplex transmission and dual antenna selection at a secondary destination node. With the full-duplex transmission, the secondary destination node can simultaneously apply the receiving and jamming antenna selection to improve the secondary data transmission and primary secrecy performance, respectively. This describes an attractive scheme in practice: Unlike that in most existing approaches, the secrecy performance improvement in the CR network is no longer at the price of the data transmission loss. The outage probabilities for both the data transmission and physical-layer secrecy are analyzed. Numerical simulations are also included to verify the performance of the proposed scheme.

Multiantenna Secure Cognitive Radio Networks With Finite-Alphabet Inputs: A Global Optimization Approach for Precoder Design

This paper considers the precoder design for multiantenna secure cognitive radio networks. We use finite-alphabet inputs as the signaling and exploit statistical channel state information (CSI) at the transmitter. We maximize the secrecy rate of the secondary user and control the transmit power and the power leakage to the primary receivers that share the same frequency spectrum. The secrecy rate maximization is important for practical systems, but challenging to solve, mainly due to two reasons. First, the secrecy rate with statistical CSI is computationally prohibitive to evaluate. Second, the optimization over the precoder is a nondeterministic polynomial-time hard (NP-hard) problem. We utilize an accurate approximation of the secrecy rate to reduce the computational effort and then propose a global optimization approach based on branch-and-bound method. The idea is to define a simplex and transform the secrecy rate into a concave function. The derived concave function converges to the secrecy rate when the defined simplex shrinks down. Using this feature, we solve a sequence of concave maximization problems over iteratively shrinking simplices and eventually attain the globally optimal solution that maximizes the approximation of the secrecy rate. When the complexity is concerned, a low-complexity variant with limited number of iterations can be used in practice. We demonstrate the performance gains when compared with others through numerical examples.

Multi-Phase Smart Relaying and Cooperative Jamming in Secure Cognitive Radio Networks

In this paper we investigate cooperative secure communications in a four-node cognitive radio network where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The secondary user is allowed to transmit his own signals under the condition that the primary user's secrecy rate and transmission scheme are intact. Under this setting we derive the secondary user's achievable rates and the related constraints to guarantee the primary user's weak secrecy rate, when Gelfand-Pinsker coding is used at the secondary transmitter. In addition, we propose a multi-phase transmission scheme to include 1) the phases of the clean relaying with cooperative jamming and 2) the latency to successfully decode the primary message at the secondary transmitter. A capacity upper bound for the secondary user is also derived. Numerical results show that: 1) the proposed scheme can outperform the traditional ones by properly selecting the secondary user's parameters of different transmission schemes according to the relative positions of the nodes; 2) the derived capacity upper bound is close to the secondary user's achievable rate within 0.3 bits/channel use, especially when the secondary transmitter/receiver is far/close enough to the primary receiver/transmitter, respectively. Thereby, a smart secondary transmitter is able to adapt its relaying and cooperative jamming to guarantee primary secrecy rates and to transmit its own data at the same time from relevant geometric positions.

Matched-Filter-based Spectrum Sensing for Secure Cognitive Radio Network Communications

increasing demand for wireless communication introduces efficient spectrum utilization challenge. To address this challenge, Cognitive Radio (CR) has emerged as the key technology, which enables opportunistic access to the spectrum. However, security is a very important issue but not well addressed in CR networks. In this paper, we focus on security problems arising from Primary User Emulation (PUE) attacks in CR networks where the selfish or malicious node emulates primary user's signals to prevent other secondary users from accessing that frequency band. Our system is based on the deployment of multiple stages of nodes, helper nodes in the first stage are stationary, close to primary user and responsible for detecting and authenticating primary user's signal based on matched filter spectrum-sensing technique. However, helper nodes in the next stages are placed within the primary user's coverage area and serve as bridges for forwarding the spectrum status information to enable secondary users to verify the cryptographic signature carried by the helper nodes' signals. Moreover, the effect of PUE attack on the performance of matched-filter-based spectrum-sensing technique is illustrated.

Managing Security Levels in a Cognitive Radio Network

The open network architecture commonly envisioned for cognitive radio networks (CRNs), while offering flexibility, increases vulnerability from a security standpoint. Therefore, understanding and managing the trade-off between CRN performance and secu- rity is critical for practical operation. In this paper, we attempt to design a secure CRN by optimizing the total throughput performance subject to constraints on expected security level. We employ block cipher as the security mechanism, vulnerability level as the security metric, and consider an exponential adversary attack model. In order to balance physical layer security and throughput in CRNs, we propose a security level adjustment (SLA) algorithm based on the idea of water-filling. The SLA algorithm can distribute the optimal security levels as well as the optimal cipher block length for each communication link in the CRN depending on the corresponding channel quality. Simulation results for throughput show that our SLA algorithm outperforms conventional fixed block length cipher. Keywords-Cognitive Radio Networks; Physical Layer Security; Encryption; Optimization.

Privacy Preserving Security Framework for Cognitive Radio Networks

To address the ever-increasing demand for wireless bandwidth, cognitive radio networks (CRNs) have been proposed to improve the efficiency of channel utilization. CRN permits unlicensed users to utilize the idle spectrum as long as it does not introduce interference to the primary users due to the Federal Communications Commission’s recent regulatory policies. In this article, we first identify the security challenges on CRNs. Then, we present main security issues together with privacy issues on CRNs and provide a privacy preserving security framework as a potential solution. The proposed framework provides a privacy preserving yet accountable security among the CRN entities. Finally, we suggest directions of future work on secure CRNs by describing several open issues.

Secure communication over MISO cognitive radio channels

In this paper, we address the physical-layer security issue of a secondary user (SU) in a spectrum-sharing cognitive radio network (CRN) from an information-theoretic perspective. Specially, we consider a secure multiple-input single-output (MISO) cognitive radio channel, where a multi-antenna SU transmitter (SU-Tx) sends confidential information to a legitimate SU receiver (SU-Rx) in the presence of an eavesdropper and on the licensed band of a primary user (PU). The secrecy capacity of the channel is characterized, which is a quasiconvex optimization problem of finding the capacity-achieving transmit covariance matrix under the joint transmit power and interference power constraints. Two numerical approaches are proposed to derive the optimal transmit covariance matrix. The first approach recasts the original quasiconvex problem into a single convex semidefinite program (SDP) by exploring its inherent convexity; while the second one explores the relationship between the secure CRN and the conventional CRN and transforms the original problem into a sequence of optimization problems associated with the conventional CRN, which helps to prove that beamforming is the optimal strategy for the secure MISO CR channel. In addition, to reduce the computational complexity, three suboptimal schemes are presented, namely, scaled secret beamforming (SSB), projected secret beamforming (PSB) and projected cognitive beamforming (PCB). Lastly, computer simulation results show that the three suboptimal schemes can approach the secrecy capacity well under certain conditions.