Dissertations / Theses on the topic 'Cognitive radio networks – Security measures'

The increasing emergence of wireless applications along with the static spectrum allocation followed by regulatory bodies has led to a high inefficiency in spectrum usage, and the lack of spectrum for new services. In this context, Cognitive Radio (CR) technology has been proposed as a possible solution to reuse the spectrum being underutilized by licensed services. CRs are intelligent devices capable of sensing the medium and identifying those portions of the spectrum being unused. Based on their current perception of the environment and on that learned from past experiences, they can optimally tune themselves with regard to parameters such as frequency, coding and modulation, among others. Due to such properties, Cognitive Radio Networks (CRNs) can act as secondary users of the spectrum left unused by their legal owners or primary users, under the requirement of not interfering primary communications. The successful deployment of these networks relies on the proper design of mechanisms in order to efficiently detect spectrum holes, adapt to changing environment conditions and manage the available spectrum. Furthermore, the need for addressing security issues is evidenced by two facts. First, as for any other type of wireless network, the air is used as communications medium and can easily be accessed by attackers. On the other hand, the particular attributes of CRNs offer new opportunities to malicious users, ranging from providing wrong information on the radio environment to disrupting the cognitive mechanisms, which could severely undermine the operation of these networks. In this Ph.D thesis we have approached the challenge of securing Cognitive Radio Networks. Because CR technology is still evolving, to achieve this goal involves not only providing countermeasures for existing attacks but also to identify new potential threats and evaluate their impact on CRNs performance. The main contributions of this thesis can be summarized as follows. First, a critical study on the State of the Art in this area is presented. A qualitative analysis of those threats to CRNs already identified in the literature is provided, and the efficacy of existing countermeasures is discussed. Based on this work, a set of guidelines are designed in order to design a detection system for the main threats to CRNs. Besides, a high level description of the components of this system is provided, being it the second contribution of this thesis. The third contribution is the proposal of a new cross-layer attack to the Transmission Control Protocol (TCP) in CRNs. An analytical model of the impact of this attack on the throughput of TCP connections is derived, and a set of countermeasures in order to detect and mitigate the effect of such attack are proposed. One of the main threats to CRNs is the Primary User Emulation (PUE) attack. This attack prevents CRNs from using available portions of the spectrum and can even lead to a Denial of Service (DoS). In the fourth contribution of this the method is proposed in order to deal with such attack. The method relies on a set of time measures provided by the members of the network and allows estimating the position of an emitter. This estimation is then used to determine the legitimacy of a given transmission and detect PUE attacks. Cooperative methods are prone to be disrupted by malicious nodes reporting false data. This problem is addressed, in the context of cooperative location, in the fifth and last contribution of this thesis. A method based on Least Median Squares (LMS) fitting is proposed in order to detect forged measures and make the location process robust to them. The efficiency and accuracy of the proposed methodologies are demonstrated by means of simulation.

A cognitive radio is an intelligent wireless communication system that improves spectrum utilisation by allowing secondary users to use the idle radio spectrum from primary licensed networks or to share the spectrum with primary users. Due to several significant challenges for cryptographic approaches of upper layers in protocol stacks | for example, private key management complexity and key transmission security issues | physical layer (PHY) security has drawn significant attention as an alternative for cryptographic approaches at the upper layers of the protocol stack. Security threats may arise from passive eavesdropping node(s), which try to intercept communications between authenticated nodes. Most recent studies consider information theoretic secrecy to be a promising approach. The idea of information theoretic secrecy lies in exploiting the randomness of communication channels to ensure the secrecy of the transmitted messages. Due to the constraints imposed on cognitive radio networks by secondary networks, allocating their resources in an optimal way is a key to maximising their achievable secrecy rates. Therefore, in this thesis, optimal resource allocation and secrecy rate maximisation of cognitive radio networks (CRNs) are proposed. Cooperative jamming is proposed to enhance the primary secrecy rate, and a new chaos-based cost function is introduced in order to design a power control algorithm and analyse the dynamic spectrum-sharing issue in the uplink of cellular CRNs. For secondary users as the game players in underlay scenarios, utility/cost functions are defined, taking into account the interference from and interference tolerance of the primary users. The existence of the Nash equilibrium is proved in this power control game, which leads to significantly lower power consumption and a relatively fast convergence rate when compared to existing game algorithms. The simulation results indicate that the primary secrecy rate is significantly improved by cooperative jamming, and the proposed power control algorithm achieves low power consumption. In addition, an integrated scheme with chaotic scrambling (CS), chaotic artificial noise, and a chaotic shift keying (CSK) scheme are proposed in an orthogonal frequency division multiplexing (OFDM)-based CR system to enhance its physical layer security. By employing the chaos-based third-order Chebyshev map to achieve the optimum bit error rate (BER) performance of CSK modulation, the proposed three-layer integrated scheme outperforms the traditional OFDM system in an overlay scenario with a Rayleigh fading channel. Importantly, under three layers of encryption that are based on chaotic scrambling, chaotic artificial noise, and CSK modulation, a large key size can be generated to resist brute-force attacks and eavesdropping, leading to a significantly improved security rate. Furthermore, a game theory-based cooperation scheme is investigated to enhance physical layer (PHY) security in both the primary and secondary transmissions of a cognitive radio network (CRN). In CRNs, the primary network may decide to lease its own spectrum for a fraction of time to the secondary nodes in exchange for appropriate remuneration. The secondary transmitter (ST) is considered to be a trusted relay for primary transmission in the presence of the ED. The ST forwards a message from the primary transmitter (PT) in a decode-and-forward (DF) fashion and, at the same time, allows part of its available power to be used to transmit an artificial noise (i.e., jamming signal) to enhance secrecy rates. In order to allocate power between the message and jamming signals, the optimisation problem is formulated and solved for maximising the primary secrecy rate (PSR) and secondary secrecy rate (SSR) with malicious attempts from a single eavesdropper or multiple eavesdroppers. Cooperation between the primary and secondary transmitters is also analysed from a game-theoretic perspective, and their interaction modelled as a Stackelberg game. This study proves theoretically and computes the Stackelberg equilibrium. Numerical examples are provided to illustrate the impact of the Stackelberg game-based optimisation on the achievable PSR and SSR. The numerical results indicate that spectrum leasing, based on trading secondary access for cooperation by means of relay and a jammer, is a promising framework for enhancing primary and secondary secrecy rates in cognitive radio networks when the ED can intercept both the primary and secondary transmission. Finally, this thesis focuses on physical-layer security in cognitive radio networks where multiple secondary nodes assist multiple primary nodes in combating unwanted eavesdropping from malicious eavesdroppers. Two scenarios are considered: a single eavesdropper (scenario I) and multiple eavesdroppers (scenario II). The secondary users act as a relay and jammer in scenario I, whereas they act only as a jammer in scenario II. Furthermore, the multiple eavesdroppers are distributed according to a homogenous Poison Point Process (PPP) in scenario II. Closed forms are derived for the outage probability and mean secrecy rate for both the primary and secondary transmissions. Furthermore, the scalability and convergence of the matching theory are proved. Both the analytical and numerical results show that the proposed matching model is a promising approach for exploiting the utility functions of both primary and secondary users.

With the advent of ubiquitous computing and Internet of Things (IoT), potentially billions of devices will create a broad range of data services and applications, which will require the communication networks to efficiently manage the increasing complexity. Cognitive network has been envisioned as a new paradigm to address this challenge, which has the capability of reasoning, planning and learning by incorporating cutting edge technologies including knowledge representation, context awareness, network optimization and machine learning. Cognitive network spans over the entire communication system including the core network and wireless links across the entire protocol stack. Cognitive Radio Network (CRN) is a part of cognitive network over wireless links, which endeavors to better utilize the spectrum resources. Core network provides a reliable backend infrastructure to the entire communication system. However, the CR communication and core network infrastructure have attracted various security threats, which become increasingly severe in pace with the growing complexity and adversity of the modern Internet. The focus of this dissertation is to exploit the security vulnerabilities of the state-of-the-art cognitive communication systems, and to provide detection, mitigation and protection mechanisms to allow security enhanced cognitive communications including wireless communications in CRNs and wired communications in core networks. In order to provide secure and reliable communications in CRNs: emph{first}, we incorporate security mechanisms into fundamental CRN functions, such as secure spectrum sensing techniques that will ensure trustworthy reporting of spectrum reading. emph{Second}, as no security mechanism can completely prevent all potential threats from entering CRNs, we design a systematic passive monitoring framework, emph{SpecMonitor}, based on unsupervised machine learning methods to strategically monitor the network traffic and operations in order to detect abnormal and malicious behaviors. emph{Third}, highly capable cognitive radios allow more sophisticated reactive jamming attack, which imposes a serious threat to CR communications. By exploiting MIMO interference cancellation techniques, we propose jamming resilient CR communication mechanisms to survive in the presence of reactive jammers. Finally, we focus on protecting the core network from botnet threats by applying cognitive technologies to detect network-wide Peer-to-Peer (P2P) botnets, which leads to the design of a data-driven botnet detection system, called emph{PeerClean}. In all the four research thrusts, we present thorough security analysis, extensive simulations and testbed evaluations based on real-world implementations. Our results demonstrate that the proposed defense mechanisms can effectively and efficiently counteract sophisticated yet powerful attacks.
Ph. D.

The tremendous success of various wireless applications operating in unlicensed bands has resulted in the overcrowding of those bands. Cognitive radio (CR) is a new technology that enables an unlicensed user to coexist with incumbent users in licensed spectrum bands without inducing interference to incumbent communications. This technology can significantly alleviate the spectrum shortage problem and improve the efficiency of spectrum utilization. Networks consisting of CR nodes (i.e., CR networks)---often called dynamic spectrum access networks or NeXt Generation (XG) communication networks---are envisioned to provide high bandwidth to mobile users via heterogeneous wireless architectures and dynamic spectrum access techniques. In recent years, the operational aspects of CR networks have attracted great research interest. However, research on the security aspects of CR networks has been very limited. In this thesis, we discuss security issues that pose a serious threat to CR networks. Specifically, we focus on three potential attacks that can be launched at the physical or MAC layer of a CR network: primary user emulation (PUE) attack, spectrum sensing data falsification (SSDF) attack, and control channel jamming (CCJ) attack. These attacks can wreak havoc to the normal operation of CR networks. After identifying and analyzing the attacks, we discuss countermeasures. For PUE attacks, we propose a transmitter verification scheme for attack detection. The scheme utilizes the location information of transmitters together with their signal characteristics to verify licensed users and detect PUE attackers. For both SSDF attacks and CCJ attacks, we seek countermeasures for attack mitigation. In particular, we propose Weighted Sequential Probability Ratio Test (WSPRT) as a data fusion technique that is robust against SSDF attacks, and introduce a multiple-rendezvous cognitive MAC (MRCMAC) protocol that is robust against CCJ attacks. Using security analysis and extensive numerical results, we show that the proposed schemes can effectively counter the aforementioned attacks in CR networks.
Ph. D.

The cognitive radio network (CRN) concept has been proposed as a solution to the growing demand and underutilization of the radio spectrum. To improve the radio spectrum utilization, CRN technology allows the coexistence of licensed and unlicensed systems over the same spectrum. In an underlay spectrum sharing system, secondary users (SUs) transmit simultaneously with the primary users (PUs) in the same frequency band given that the interference caused by the SU to the PU remains below a tolerable interference limit. Besides the transmission power limitation, a secondary network is subject to distinct channel impairments such as fading and interference from the primary transmissions. Also, CRNs face new security threats and challenges due to their unique cognitive characteristics.This thesis analyzes the performance of underlay CRNs and underlay cognitive relay networks under spectrum sharing constraints and security constraints. Distinct SU transmit power policies are obtained considering various interference constraints such as PU outage constraint or PU peak interference power constraint. The thesis is divided into an introduction and two research parts based on peer-reviewed publications. The introduction provides an overview of radio spectrum management, basic concepts of CRNs, and physical layer security. In the first research part, we study the performance of underlay CRNs with emphasis on a multiuser environment.In Part I-A, we consider a secondary network with delay-tolerant applications and analyze the ergodic capacity. Part I-B analyzes the secondary outage capacity which characterises the maximum data rate that can be achieved over a channel for a given outage probability. In Part I-C, we consider a secondary network with delay constrained applications, and derive expressions of the outage probability and delay-limited throughput. Part I-D presents a queueing model that provides an analytical tool to evaluate the secondary packet-level performance with multiple classes of traffic considering general interarrival and service time distributions. Analytical expressions of the SU average packet transmission time, waiting time in the queue, andtime spent in the system are provided.In the second research part, we analyze the physical layer security for underlay CRNs and underlay cognitive relay networks. Analytical expressions of the probability of non-zero secrecy capacity and secrecy outage probability are derived.Part II-A considers a single hop underlay CRN in the presence of multiple eavesdroppers (EAVs) and multiple SU-Rxs. In Part II-B, an underlay cognitive relay network in the presence of multiple secondary relays and multiple EAVs is studied.Numerical examples illustrate that it is possible to exploit the physical layer characteristics to achieve both security and quality of service in CRNs while satisfying spectrum sharing constraints.

Les réseaux de télécommunications sont soumis à des processus d'amélioration et d'optimisation continue. Chaque nouvelle itération apporte son lot de défis et limites. En effet, la croissance exponentielle des appareils de télécommunication, des stations de base aux équipements utilisateurs conduisent à de sérieux problèmes d'economie d'énergie. En plus des menaces à la vie privée, en particulier pour les réseaux sans fil car les canaux utilisés par les opérateurs peuvent également être utilisés par une oreille indiscrète quelconque. L'optimisation de l'utilisation du spectre est également un défi en raison du fait que le spectre disponible dans les systèmes de communication sans fil est devenu une ressource très rare en raison de la demande croissante. Les réseaux émergents, tels que les femtocells, souffrent également des défis mentionnés précédemment. Le travail de thèse actuel se concentre sur la proposition de solutions aux défis cités précédemment: l'efficacité énergétique, le partage du spectre et la sécurité. Le travail de recherche présenté dans cette thèse a porté sur trois axes principaux: Premièrement, trouver un moyen de réduire au minimum la consommation d'énergie des femtocellules dans les reseaux BWA femto/macro-cellulaire en diminuant le nombre d'événements de mobilité non désirées et l'introduction de nouveaux états de puissance pour la femtocellule. En second lieu, proposer une solution qui vise à réduire le temps de transmission prévu dans le temps de séjour de l'utilisateur secondaire (SU) dans la couverture d'une femtocellule en utilisant un algorithme basé sur le temps minimum prévu de transmission dans le temps de séjour de l'équipement utilisateur (UE). Enfin, introduire un nouveau modèle qui basé sur la sélection du meilleur relais qui maximise le taux de confidentialité et les avantages de l'augmentation du nombre de relais sous la contrainte de qualité de service à la destination
Telecommunications networks are subject to continuous improvement and enhancement processes. Every new iteration brings its set of challenges and limitations. In fact, the exponential growth in telecommunication devices, from base stations to user equipments lead to serious energy efficiency issues. Along with the privacy threats, especially for wireless networks as the channels used by operators can also be used by any eavesdropper. Spectrum usage optimization is also a challenge due to the fact that the available spectrum in wireless communications systems has been a very rare resource because of the increasing demand. Emerging networks, such as femtocells, suffer also from the previously mentioned challenges. The current thesis work focuses on proposing several solutions to the previously cited challenges: energy efficiency, spectrum sharing and security. The research work introduced in this thesis has focused on three main axes: First, find a way to minimize the energy consumption of femtocells in macro/femto-cellular BWA networks by decreasing the number of unwanted mobility events and introducing new power states for the femtocell device. Second, propose a solution that aims to reduce the expected transmission time within the dwell time of Secondary User (SU) in the coverage of a femtocell using an algorithm based on the minimum expected transmission time within the dwell time of the User Equipment (UE) in the coverage of the femtocell. Finally, introduce a new scheme that is based on best relay selection method that maximizes the secrecy rate and benefits from increasing the number of relays under QoS constraint at the destination

A Cognitive Radio Network (CRN) is a technology that allows unlicensed users to utilise licensed spectrum by detecting an idle band through sensing. How- ever, most research studies on CRNs have been carried out without considering the impact of sensing on the performance and security of CRNs. Sensing is essential for secondary users (SUs) to get hold of free band without interfering with the signal generated by primary users (PUs). However, excessive sensing time for the detection of free spectrum for SUs as well as extended periods of CRNs in an insecure state have adverse effects on network performance. Moreover, a CRN is very vulnerable to attacks as a result of its wireless nature and other unique characteristics such as spectrum sensing and sharing. These attacks may attempt to eavesdrop or modify the contents of packets being transmitted and they could also deny legitimate users the opportunity to use the band, leading to underutilization of the spectrum space. In this context, it is often challenging to differentiate between networks under Denial of Service (DoS) attacks from those networks experiencing congestion. This thesis employs a novel Stochastic Activity Network (SAN) model as an effective analytic tool to represent and study sensing vs performance vs security trade-offs in CRNs. Specifically, an investigation is carried out focusing on sensing vs security vs performance trade-offs, leading to the optimization of the spectrum band’s usage. Moreover, consideration is given either when a CRN experiencing congestion and or it is under attack. Consequently, the data delivery ratio (PDR) is employed to determine if the network is under DoS attack or experiencing congestion. In this context, packet loss probability, queue length and throughput of the transmitter are often used to measure the PDR with reference to interarrival times of PUs. Furthermore, this thesis takes into consideration the impact of scalability on the performance of the CRN. Due to the unpredictable nature of PUsactivities on the spectrum, it is imperative for SUs to swiftly utilize the band as soon as it becomes available. Unfortunately, the CRN models proposed in literature are static and unable to respond effectively to changes in service demands. To this end, a numerical simulation experiment is carried out to determine the impact of scalability towards the enhancement of nodal CRN sensing, security and performance. Atthe instant the band becomes idle and there are requests by SUs waiting for encryption and transmission, additional resources are dynamically released in order to largely utilize the spectrum space before the reappearance of PUs. These additional resources make the same service provision, such as encryption and intrusion detection, as the initial resources. To this end,SAN model is proposed in order to investigate the impact of scalability on the performance of CRN. Typical numerical simulation experiments are carried out, based on the application of the Mobius Petri Net Package to determine the performance of scalable CRNs (SCRNs) in comparison with unscalable CRNs (UCRNs) and associated interpretations are made.

Cognitive radios are currently presented as the solution to the ever-increasing spectrum shortage problem. However, their increased capabilities over traditional radios introduce a new dimension of security threats. Cooperative Spectrum Sensing (CSS) has been proposed as a means to protect cognitive radio networks from the well known security threats: Primary User Emulation (PUE) and Spectrum Sensing Data Falsification (SSDF). I demonstrate a new threat to trust-based CSS protocols, called the Rogue Signal Framing (RSF) intrusion. Rogue signals can be exploited to create the illusion of malicious sensors which leads to the framing of innocent sensors and consequently, their removal from the shared spectrum sensing. Ultimately, with fewer sensors working together, the spectrum sensing is less robust for making correct spectrum access decisions. The simulation experiments illustrate the impact of RSF intrusions which, in severe cases, shows roughly 40\% of sensors removed. To mitigate the RSF intrusion's damage to the network's trust, I introduce a new defense based on community detection from analyzing the network's Received Signal Strength (RSS) diversity. Tests show a 95\% damage reduction in terms of removed sensors from the shared spectrum sensing, thus retaining the benefits of CSS protocols.

Common control channels in cognitive radio (CR) ad hoc networks are spectrum resources temporarily allocated and commonly available to CR users for control message exchange. With no presumably available network infrastructure, CR users rely on cooperation to perform spectrum management functions. One the one hand, CR users need to cooperate to establish common control channels, but on the other hand, they need to have common control channels to facilitate such cooperation. This control channel problem is further complicated by primary user (PU) activities, channel impairments, and intelligent attackers. Therefore, how to reliably and securely establish control links in CR ad hoc networks is a challenging problem. In this work, a framework for control channel design and analysis is proposed to address control channel reliability and security challenges for seamless communication and spectral efficiency in CR ad hoc networks. The framework tackles the problem from three perspectives: (i) responsiveness to PU activities: an efficient recovery control channel method is devised to efficiently establish control links and extend control channel coverage upon PU's return while mitigating the interference with PUs, (ii) robustness to channel impairments: a reinforcement learning-based cooperative sensing method is introduced to improve cooperative gain and mitigate cooperation overhead, and (iii) resilience to jamming attacks: a jamming-resilient control channel method is developed to combat jamming under the impacts of PU activities and spectrum sensing errors by leveraging intrusion defense strategies. This research is particularly attractive to emergency relief, public safety, military, and commercial applications where CR users are highly likely to operate in spectrum-scarce or hostile environment.

Recently, massive multiple-input multiple-output (MIMO) systems have gained significant attention as a new network architecture to not only achieving unprecedented spectral and energy efficiencies, but also to alleviating propagation losses and inter-user/inter-cell interference. Therefore, massive MIMO has been identified as one of the key candidate technologies for the 5th generation wireless standard. This dissertation thus focuses on (1) developing a performance analysis framework for cognitive massive MIMO systems by investigating the uplink transmissions of multi-cell multi-user massive MIMO secondary systems, which are underlaid in multi-cell multi-user primary massive MIMO systems, with taking into consideration the detrimental effects of practical transmission impairments, (2) proposing a new wireless-powered underlay cognitive massive MIMO system model, as the secondary user nodes is empowered by the ability to efficiently harvest energy from the primary user transmissions, and then access and utilize the primary network spectrum for information transmission, and (3) developing a secure communication strategy for cognitive multi-user massive MIMO systems, where physical layer secure transmissions are provisioned for both primary and secondary systems by exploiting linear precoders and artificial noise (AN) generation in order to degrade the signal decodability at eavesdropper. The key design feature of the proposed cognitive systems is to leverage the spatial multiplexing strategies to serve a large number of spatially distributed user nodes by using very large numbers of antennas at the base-stations. Moreover, the fundamental performance metrics, the secondary transmit power constraints, which constitute the underlay secondary transmissions subject to a predefined primary interference temperature, and the achievable sum rates of the primary and secondary systems, are characterized under different antenna array configurations. Additionally, the detrimental impact of practical wireless transmission impairments on the performance of the aforementioned systems are quantified. The important insights obtained throughout these analyses can be used as benchmarks for designing practical cognitive spectrum sharing networks.

The thesis presents research on multiobjective optimization based on memetic computing and its applications in engineering. We have introduced a framework for adaptive multiobjective memetic optimization algorithms (AMMOA) with an information theoretic criterion for guiding the selection, clustering, and local refinements. A robust stopping criterion for AMMOA has also been introduced to solve non-linear and large-scale optimization problems. The framework has been implemented for different benchmark test problems with remarkable results. This thesis also presents two applications of these algorithms. First, an optimal image data hiding technique has been formulated as a multiobjective optimization problem with conflicting objectives. In particular, trade-off factors in designing an optimal image data hiding are investigated to maximize the quality of watermarked images and the robustness of watermark. With the fixed size of a logo watermark, there is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. We propose to use a hybrid between general regression neural networks (GRNN) and the adaptive multiobjective memetic optimization algorithm (AMMOA) to solve this challenging problem. This novel image data hiding approach has been implemented for many different test natural images with remarkable robustness and transparency of the embedded logo watermark. We also introduce a perceptual measure based on the relative Rényi information spectrum to evaluate the quality of watermarked images. The second application is the problem of joint spectrum sensing and power control optimization for a multichannel, multiple-user cognitive radio network. We investigated trade-off factors in designing efficient spectrum sensing techniques to maximize the throughput and minimize the interference. To maximize the throughput of secondary users and minimize the interference to primary users, we propose a joint determination of the sensing and transmission parameters of the secondary users, such as sensing times, decision threshold vectors, and power allocation vectors. There is a conflict between these two objectives, thus a multiobjective optimization problem is used again in the form of AMMOA. This algorithm learns to find optimal spectrum sensing times, decision threshold vectors, and power allocation vectors to maximize the averaged opportunistic throughput and minimize the averaged interference to the cognitive radio network.
February 2016

No
The growth of wireless devices affects the availability of limited frequencies or spectrum bands as it has been known that spectrum bands are a natural resource that cannot be added. Meanwhile, the licensed frequencies are idle most of the time. Cognitive radio is one of the solutions to solve those problems. Cognitive radio is a promising technology that allows the unlicensed users known as secondary users (SUs) to access licensed bands without making interference to licensed users or primary users (PUs). As cloud computing has become popular in recent years, cognitive radio networks (CRNs) can be integrated with cloud platform. One of the important issues in CRNs is security. It becomes a problem since CRNs use radio frequencies as a medium for transmitting and CRNs share the same issues with wireless communication systems. Another critical issue in CRNs is performance. Security has adverse effect to performance and there are trade-offs between them. The goal of this paper is to investigate the performance related to security trade-off in CRNs with supporting cloud platforms. Furthermore, Queuing Network Models with preemptive resume and preemptive repeat identical priority are applied in this project to measure the impact of security to performance in CRNs with or without cloud platform. The generalized exponential (GE) type distribution is used to reflect the bursty inter-arrival and service times at the servers. The results show that the best performance is obtained when security is disabled and cloud platform is enabled.

With the rapid proliferation of new technologies and services in the wireless domain, spectrum scarcity has become a major concern. Cognitive radios (CRs) arise as a promising solution to the scarcity of spectrum. A basic operation of the CRs is spectrum sensing. Whenever a primary signal is detected, CRs have to vacate the specific spectrum band. Malicious users can mimic incumbent transmitters so as to enforce CRs to vacate the specific band. Cognitive radio networks (CRNs) are expected to bring an evolution to the spectrum scarcity problem through intelligent use of the fallow spectrum bands. However, as CRNs are wireless in nature, they face all common security threats found in the traditional wireless networks. Common security combating measures for wireless environments consist of authorization, authentication, and access control. But CRNs face new security threats and challenges that have arisen due to their unique cognitive (self-configuration, self-healing, self-optimization, and self-protection) characteristics. Because of these new security threats, the use of traditional security combating measures would be inadequate to address the challenges. Consequently, this research work proposes an Intrusion Detection and Response Model (IDRM) to enhance security in cognitive radio networks. Intrusion detection monitors all the activities in order to detect the intrusion. It searches for security violation incidents, recognizes unauthorized accesses, and identifies information leakages. Unfortunately, system administrators neither can keep up with the pace that an intrusion detection system is delivering responses or alerts, nor can they react within adequate time limits. Therefore, an automatic response system has to take over this task by reacting without human intervention within the cognitive radio network.
Thesis (M.Sc.(Computer Science) North-West University, Mafikeng Campus, 2012

Cognitive Radio (CR) has received tremendous research attention over the past decade, both in the academia and industry, as it is envisioned as a promising solution to the problem of spectrum scarcity. ACR is a device that senses the spectrum for occupancy by licensed users(also called as primary users), and transmits its data only when the spectrum is sensed to be available. For the efficient utilization of the spectrum while also guaranteeing adequate protection to the licensed user from harmful interference, the CR should be able to sense the spectrum for primary occupancy quickly as well as accurately. This makes Spectrum Sensing(SS) one of the where the goal is to test whether the primary user is inactive(the null or noise-only hypothesis), or not (the alternate or signal-present hypothesis). Computational simplicity, robustness to uncertainties in the knowledge of various noise, signal, and fading parameters, and ability to handle interference or other source of non-Gaussian noise are some of the desirable features of a SS unit in a CR. In many practical applications, CR devices can exploit known structure in the primary signal. IntheIEEE802.22CR standard, the primary signal is a wideband signal, but with a strong narrowband pilot component. In other applications, such as military communications, and blue tooth, the primary signal uses a Frequency Hopping (FH)transmission. These applications can significantly benefit from detection schemes that are tailored for detecting the corresponding primary signals. This thesis develops novel detection schemes and rigorous performance analysis of these primary signals in the presence of fading. For example, in the case of wideband primary signals with a strong narrowband pilot, this thesis answers the further question of whether to use the entire wideband for signal detection, or whether to filter out the pilot signal and use narrowband signal detection. The question is interesting because the fading characteristics of wideband and narrowband signals are fundamentally different. Due to this, it is not obvious which detection scheme will perform better in practical fading environments. At another end of the gamut of SS algorithms, when the CR has no knowledge of the structure or statistics of the primary signal, and when the noise variance is known, Energy Detection (ED) is known to be optimal for SS. However, the performance of the ED is not robust to uncertainties in the noise statistics or under different possible primary signal models. In this case, a natural way to pose the SS problem is as a Goodness-of-Fit Test (GoFT), where the idea is to either accept or reject the noise-only hypothesis. This thesis designs and studies the performance of GoFTs when the noise statistics can even be non-Gaussian, and with heavy tails. Also, the techniques are extended to the cooperative SS scenario where multiple CR nodes record observations using multiple antennas and perform decentralized detection. In this thesis, we study all the issues listed above by considering both single and multiple CR nodes, and evaluating their performance in terms of(a)probability of detection error,(b) sensing-throughput trade off, and(c)probability of rejecting the null-hypothesis. We propose various SS strategies, compare their performance against existing techniques, and discuss their relative advantages and performance tradeoffs. The main contributions of this thesis are as follows: The question of whether to use pilot-based narrowband sensing or wideband sensing is answered using a novel, analytically tractable metric proposed in this thesis called the error exponent with a confidence level. Under a Bayesian framework, obtaining closed form expressions for the optimal detection threshold is difficult. Near-optimal detection thresholds are obtained for most of the commonly encountered fading models. Foran FH primary, using the Fast Fourier Transform (FFT) Averaging Ratio(FAR) algorithm, the sensing-through put trade off are derived in closed form. A GoFT technique based on the statistics of the number of zero-crossings in the observations is proposed, which is robust to uncertainties in the noise statistics, and outperforms existing GoFT-based SS techniques. A multi-dimensional GoFT based on stochastic distances is studied, which pro¬vides better performance compared to some of the existing techniques. A special case, i.e., a test based on the Kullback-Leibler distance is shown to be robust to some uncertainties in the noise process. All of the theoretical results are validated using Monte Carlo simulations. In the case of FH-SS, an implementation of SS using the FAR algorithm on a commercially off-the ¬shelf platform is presented, and the performance recorded using the hardware is shown to corroborate well with the theoretical and simulation-based results. The results in this thesis thus provide a bouquet of SS algorithms that could be useful under different CRSS scenarios.

博士
國立成功大學
工程科學系
103
This dissertation investigates security information technologies for mobile orthogonal frequency division multiplexing (OFDM) systems and OFDM-based cognitive radio (CR) networks. Traditionally, security is viewed as an independent feature addressed above the physical layer (PHY). All widely used cryptographic protocols are established assuming the PHY layer is merely used to provide an error-free link. However, with the emergence of ad-hoc and decentralized networks, higher-layer security techniques are complex and hard to be implemented. To complement and enhance traditional security mechanism, we study novel schemes for OFDM systems and CR networks based on the channel power-delay profile (PDP), considering channel time and frequency selectivities. More specifically, the PHY layer, employing the properties of OFDM signals over time-variant and multipath fading channels, is aimed to assist the overall authentication process. To identify different transmitters (TXs), we employ the hypothesis test based on their PDPs to distinguish different transmission terminals in OFDM systems and primary user emulation attacks (PUEA) in OFDM-based CR networks. The proposed PDP estimation is obtained based on the redundancy of cyclic prefix (CP), which is a common feature for almost all OFDM systems. In OFDM systems, it is advantageous to use the PDP as the wireless signature, because it depends on the surrounding environment and is therefore considered to be very hard to mimic. In OFDM-based CR networks, channel-tap power is utilized as a radio-frequency fingerprint (RF) to directly detect users via PHY layer. To improve the detection performance of PHY layer in fading channels, the cooperative detection schemes using the fixed sample size test (FSST) and the sequential probability ratio test (SPRT) are devised for CR networks. Although different users can be distinguished, it is still impossible to exactly tell identity of a TX as primary user (PU) or PUEA using only PHY layer. Hence, to accurately know identities of PUs and PUEAs, the cross-layer intelligent learning ability of a mobile secondary user (SU) is exploited to establish detection databases by seamlessly combining the quick detection of PHY layer with the accuracy of higher layer authentication. The proposed methods helps PHY layer completely detect the identities of PUs and PUEAs. Finally, the performances are analyzed, and simulations confirm the advantages of the proposed methods.