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Security threat assessment of simultaneous multiple Denial-of-Service attacks in IEEE 802.22 Cognitive Radio networks
... Our previous work in [19] introduces the Bayesian Attack 164 Graph (BAG) model as a possible metric of the probability of 165 Denial of Service (DoS) in the IEEE 802.22 CRNs under the 166 assumption of contingent multiple DoS attacks. In [19], the 167 impact of contingent Dos attacks on CRNs was proven to be 168 much higher than the most severe sole attack. ...
... Our previous work in [19] introduces the Bayesian Attack 164 Graph (BAG) model as a possible metric of the probability of 165 Denial of Service (DoS) in the IEEE 802.22 CRNs under the 166 assumption of contingent multiple DoS attacks. In [19], the 167 impact of contingent Dos attacks on CRNs was proven to be 168 much higher than the most severe sole attack. In Section-III 169 of this paper, the BAG model is described in details and then 170 utilized to assess the probability of success of contingent acute 171 jamming attacks. ...
... The complexity of the jamming attacks in CRNs was 464 assessed in [19] where the result of attack complexity evalua-465 tion ranges from 0 (i.e., None), 1 (i.e., Easy), 2 (i.e., Solvable) 466 to 3 (i.e., Strong). Applying the evaluation grid 4 in [19], the 467 value of r 1 , representing the complexity of the PUE attack, is 468 set to 2 (i.e., Solvable) as it requires the generation of a sig-469 nal with specific characteristics, e.g., digital TV signals. ...
The deceiving attacker is a radio jammer, equipped with a cognitive radio (CR) platform, which senses the frequency spectrum and launches jamming actions to block, mask, or emulate the legitimate active wireless connections. Using the IEEE 802.22 cognitive radio network (CRN) as a basis, this paper proposes a set of deception-based defense strategies to protect the CRNs from the deceiving attack. The Stackelberg framework is adopted in the formulation of the security problem to account for the attacker’s reconnaissance capabilities. To this end, the Stackelberg equilibria (SE) between the attacker(s) and the defending CRs are calculated under the two cases when the attacker(s) and the defending CRs know and are uncertain about the primary user activity. The backward induction method is used to calculate the points of SE in the formulated security game. Both theoretical analysis and numerical results show that the defending CRs can decrease the probability of success of the deceiving attack to nearly 0% when the CRs have the incentive to defend the frequency channel(s).
... Only few research efforts targeted the security assessment of the IEEE 802.22 CR networks, such as [6], [8] and [9]. In this paper, the algorithm in [9] is adopted to assess p mj because it introduces a quantifiable metric. ...
... Only few research efforts targeted the security assessment of the IEEE 802.22 CR networks, such as [6], [8] and [9]. In this paper, the algorithm in [9] is adopted to assess p mj because it introduces a quantifiable metric. The adopted algorithm utilizes the Bayesian attack graph (BAG) model. ...
... The adopted algorithm utilizes the Bayesian attack graph (BAG) model. For brevity, the main steps of the adopted algorithm are listed below, however, more details can be found in [9]. 1) Develop the BAG model considering all l z ∈ m j 2) Calculate the probability of vulnerability exploitation between each child node S ch and its parent nodes P a[S ch ]. 3) Calculate the probability of attack propagation from parent nodes to each child node p(S ch |P a[S ch ]). ...
... The pdf p (a) (χ) can be evaluated by substituting the (15) in to (12) and (13) to evaluate σ 2 χ and µ χ . Finally, to detect the presence of the attacker, we formulate the Wald's Sequential Probability Ratio Test (SPRT) [18]. ...
... Requires: [57][58][59] Postcondition Postcondition: [39,41,43,45,60]; Effect: [61]; Provides: [57][58][59]; Consequence: [31,32,50,62,63]; Impact: [28,59,[64][65][66][67]; ...
Perceiving and understanding cyber-attacks can be a difficult task, and more effective techniques are needed to aid cyber-attack perception. Attack modelling techniques (AMTs) - such as attack graphs, attack trees and fault trees, are a popular method of mathematically and visually representing the sequence of events that lead to a successful cyber-attack. These methods are useful visual aids that can aid cyber-attack perception.
This survey paper describes the fundamental theory of cyber-attack before describing how important elements of a cyber-attack are represented in attack graphs and attack trees. The key focus of the paper is to present empirical research aimed at analysing more than 180 attack graphs and attack trees to identify how attack graphs and attack trees present cyber-attacks in terms of their visual syntax.
There is little empirical or comparative research which evaluates the effectiveness of these methods. Furthermore, despite their popularity, there is no standardised attack graph visual syntax configuration, and more than seventy self-nominated attack graph and twenty attack tree configurations have been described in the literature — each of which presents attributes such as preconditions and exploits in a different way. The survey demonstrates that there is no standard method of representing attack graphs or attack trees and that more research is needed to standardise the representation.
... The existing work on securing the FD-CRNs has considered the physical layer security with dedicated anti-jamming antennas to avoid eavesdroppers. However, the wide range of specific CRN security and privacy threats, such as primary user emulation (PUE) attacks [56], denial-of-service attacks [210], and spectrum sensing data falsification (SSDF) attacks [211], need to be studied from the FD-CRN perspective, taking the spectrum sensing and SIS approaches into consideration. Furthermore, in FD-CRNs with a common control channel, e.g., [211], security strategies for this crucial common control channel need to be developed and evaluated. ...
Wireless networks with their ubiquitous applications have become an indispensable part of our daily lives. Wireless networks demand more and more spectral resources to support the ever increasing numbers of users. According to network engineers, the current spectrum crunch can be addressed with the introduction of cognitive radio networks (CRNs). In half-duplex (HD) CRNs, the secondary users (SUs) can either only sense the spectrum or transmit at a given time. This HD operation limits the SU throughput because the SUs cannot transmit during the spectrum sensing. However, with the advances in self-interference suppression (SIS), full-duplex (FD) CRNs allow for simultaneous spectrum sensing and transmission on a given channel. This FD operation increases the throughput and reduces collisions as compared to HD-CRNs. In this paper, we present a comprehensive survey of FD-CRN communications. We cover the supporting network architectures and the various transmit and receive antenna designs. We classify the different SIS approaches in FD-CRNs. We survey the spectrum sensing approaches, and security requirements for FD-CRNs. We also survey major advances in full-duplex medium access protocol (FD-MAC) protocols as well as open issues, challenges, and future research directions to support the FD operation in CRNs.
The paper addresses the problem of spectrum sensing data falsification (SSDF) attacks in cooperative sensing and develops a dynamic trust management scheme to reliably detect and mitigate such attacks in cognitive radio networks. Secondary users (SUs) sense the spectrum to identify and dynamically access the available primary user (PU) channel. To improve sensing reliability, SUs send their sensing reports (subject to sensing error of individual spectrum sensor, e.g., energy detector) to a fusion center, where sensing reports are combined to identify the channel state (idle or busy). Three types of SUs are considered: (i) normal users reporting their sensing results honestly, (ii) attackers reporting their sensing results inaccurately in form of random on-off attacks, (iii) irrelevant users observing independent spectrum events. The consistency of sensing results is checked at the fusion center with channel outcome of scheduled transmissions (obtained under possible feedback errors) and the probabilistic trust of each user is updated with Bayes rule. Then, the optimal decision rule for cooperative sensing is determined dynamically with new trust assignments. Performance is evaluated separately under Gaussian signal assumption and with wireless transmission data collected with actual radios. Results show that dynamic trust management reliably detects user types and eliminates effects of SSDF attacks. Both the sensing error probability and the throughput are significantly improved compared to the case when all users are by default trusted to be normal users. This performance gain is maintained as the number of attackers or irrelevant users increases in the cognitive radio network.
Attack graphs are a powerful tool for security risk assessment by analysing
network vulnerabilities and the paths attackers can use to compromise valuable
network resources. The uncertainty about the attacker's behaviour and
capabilities make Bayesian networks suitable to model attack graphs to perform
static and dynamic analysis. Previous approaches have focused on the
formalization of traditional attack graphs into a Bayesian model rather than
proposing mechanisms for their analysis. In this paper we propose to use
efficient algorithms to make exact inference in Bayesian attack graphs,
enabling the static and dynamic network risk assessments. To support the
validity of our proposed approach we have performed an extensive experimental
evaluation on synthetic Bayesian attack graphs with different topologies,
showing the computational advantages in terms of time and memory use of the
proposed techniques when compared to existing approaches.
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.
The Byzantine attack in cooperative spectrum sensing (CSS), also known as the
spectrum sensing data falsification (SSDF) attack in the literature, is one of
the key adversaries to the success of cognitive radio networks (CRNs). In the
past couple of years, the research on the Byzantine attack and defense
strategies has gained worldwide increasing attention. In this paper, we provide
a comprehensive survey and tutorial on the recent advances in the Byzantine
attack and defense for CSS in CRNs. Specifically, we first briefly present the
preliminaries of CSS for general readers, including signal detection
techniques, hypothesis testing, and data fusion. Second, we analyze the spear
and shield relation between Byzantine attack and defense from three aspects:
the vulnerability of CSS to attack, the obstacles in CSS to defense, and the
games between attack and defense. Then, we propose a taxonomy of the existing
Byzantine attack behaviors and elaborate on the corresponding attack
parameters, which determine where, who, how, and when to launch attacks. Next,
from the perspectives of homogeneous or heterogeneous scenarios, we classify
the existing defense algorithms, and provide an in-depth tutorial on the
state-of-the-art Byzantine defense schemes, commonly known as robust or secure
CSS in the literature. Furthermore, we highlight the unsolved research
challenges and depict the future research directions.
Cognitive Radio (CR) is a promising technology for opportunistically accessing underutilized licensed spectrum to achieve higher spectrum efficiency and communication throughput. These performance gains are contingent upon the efficient coordination of channel access to the idle portion of the spectrum, an operation performed at the Medium Access Control (MAC) layer. In this article we identify various vulnerabilities of state-of-the-art CR MAC protocols, exploited by selfish/malicious CR users for gaining an unfair share of the available network resources. Furthermore, possible countermeasures for detecting and mitigating these vulnerabilities are discussed.
Attack graph analysis has been established as a powerful tool for analyzing network vulnerability. However, previous approaches to network hardening look for exact solutions and thus do not scale. Further, hardening elements have been treated independently, which is inappropriate for real environments. For example, the cost for patching many systems may be nearly the same as for patching a single one. Or patching a vulnerability may have the same effect as blocking traffic with a firewall, while blocking a port may deny legitimate service. By failing to account for such hardening interdependencies, the resulting recommendations can be unrealistic and far from optimal. Instead, we formalize the notion of hardening strategy in terms of allowable actions, and define a cost model that takes into account the impact of interdependent hardening actions. We also introduce a near-optimal approximation algorithm that scales linearly with the size of the graphs, which we validate experimentally.
Security risk assessment and mitigation are two vital processes that need to be executed to maintain a productive IT infrastructure. On one hand, models such as attack graphs and attack trees have been proposed to assess the cause-consequence relationships between various network states, while on the other hand, different decision problems have been explored to identify the minimum-cost hardening measures. However, these risk models do not help reason about the causal dependencies between network states. Further, the optimization formulations ignore the issue of resource availability while analyzing a risk model. In this paper, we propose a risk management framework using Bayesian networks that enable a system administrator to quantify the chances of network compromise at various levels. We show how to use this information to develop a security mitigation and management plan. In contrast to other similar models, this risk model lends itself to dynamic analysis during the deployed phase of the network. A multiobjective optimization platform provides the administrator with all trade-off information required to make decisions in a resource constrained environment.
The cognitive radio enabled IEEE 802.22 wireless regional area network (WRAN) is designed to opportunistically utilize the unused or under-utilized TV bands. However, due to the open nature of cognitive radio networks and lack of proactive security protocols, the IEEE 802.22 networks are vulnerable to various denial-of-service (DoS) threats. In this paper, we study coordinated DoS attacks on IEEE 802.22 networks from the malicious users' perspective. We consider both one-stage and a multi-stage cases of the problem. In the one-stage scenario, we formulate a cooperative game among the malicious nodes and derive the optimal decision strategy for the them. In the multi-stage case, we propose a discrete-time Markov chain model for the dynamic behavior of both malicious nodes and the 802.22 secondary networks. Simulation and numerical results demonstrate that in the one-stage case, the coordinated attack achieves 10-15% improvement compared to the non-cooperative attack from the perspective of malicious nodes, and, in the multi-stage case, there exists an optimal number of malicious nodes that maximize the net payoff under the steady state.
Cognitive Radio (CR) is seen as one of the enabling tech- nologies for realizing a new spectrum access paradigm, viz. Opportunistic Spectrum Sharing (OSS). IEEE 802.22 is the world's first wireless standard based on CR technology. It defines the air interface for a wireless regional area network (WRAN) that uses fallow segments of the licensed (incum- bent) TV broadcast bands. CR technology enables unli- censed (secondary) users in WRANs to utilize licensed spec- trum bands on a non-interference basis to incumbent users. The coexistence between incumbent users and secondary users is referred to as incumbent coexistence. On the other hand, the coexistence between secondary users in different WRAN cells is referred to as self-coexistence. The 802.22 draft standard prescribes several mechanisms for address- ing incumbent- and self-coexistence issues. In this paper, we describe how adversaries can exploit or undermine such mechanisms to degrade the performance of 802.22 WRANs and increase the likelihood of those networks interfering with incumbent networks. The standard includes a security sub- layer to provide subscribers with privacy, authentication, and confidentiality. Our investigation, however, revealed that the security sublayer falls short of addressing all of the key security threats. We also discuss countermeasures that may be able to address those threats.
Security risk assessment and mitigation are two vital processes that need to be executed to maintain a productive IT infrastructure. On one hand, models such as attack graphs and attack trees have been proposed to assess the cause-consequence relationships between various network states, while on the other hand, different decision problems have been explored to identify the minimum-cost hardening measures. However, these risk models do not help reason about the causal dependencies between network states. Further, the optimization formulations ignore the issue of resource availability while analyzing a risk model. In this paper, we propose a risk management framework using Bayesian networks that enable a system administrator to quantify the chances of network compromise at various levels. We show how to use this information to develop a security mitigation and management plan. In contrast to other similar models, this risk model lends itself to dynamic analysis during the deployed phase of the network. A multiobjective optimization platform provides the administrator with all trade-off information required to make decisions in a resource constrained environment.
An attack graph is a succinct representation of all paths through a system that end in a state where an intruder has successfully achieved his goal. Today Red Teams determine the vulnerability of networked systems by drawing gigantic attack graphs by hand. Constructing attack graphs by hand is tedious, error-prone, and impractical for large systems. By viewing an attack as a violation of a safety property, we can use off-the-shelf model checking technology to produce attack graphs automatically: a successful path from the intruder's viewpoint is a counterexample produced by the model checker In this paper we present an algorithm for generating attack graphs using model checking as a subroutine. Security analysts use attack graphs for detection, defense and forensics. In this paper we present a minimization analysis technique that allows analysts to decide which minimal set of security measures would guarantee the safety of the system. We provide a formal characterization of this problem: we prove that it is polynomially equivalent to the minimum hitting set problem and we present a greedy algorithm with provable bounds. We also present a reliability analysis technique that allows analysts to perform a simple cost-benefit trade-off depending on the likelihoods of attacks. By interpreting attack graphs as Markov Decision Processes we can use the value iteration algorithm to compute the probabilities of intruder success for each attack the graph.
In the last decade, cognitive radio (CR) has emerged as a major next generation wireless networking technology, which is the most promising candidate solution to solve the spectrum scarcity and improve the spectrum utilization. However, there exist enormous challenges for the open and random access environment of CRNs, where the unlicensed secondary users (SUs) can use the channels that are not currently used by the licensed primary users (PUs) via spectrum-sensing technology. Because of this access method, some malicious users may access the cognitive network arbitrarily and launch some special attacks, such as primary user emulation attack, falsifying data or denial of service attack, which will cause serious damage to the cognitive radio network. In addition to the specific security threats of cognitive network, CRNs also face up to the conventional security threats, such as eavesdropping, tampering, imitation, forgery, and noncooperation etc. Hence, Cognitive radio networks have much more risks than traditional wireless networks with its special network model. In this paper, we considered the security threats from passive and active attacks. Firstly, the PHY layer security is presented in the view of passive attacks, and it is a compelling idea of using the physical properties of the radio channel to help provide secure wireless communications. Moreover, malicious user detection is introduced in the view of active attacks by means of the signal detection techniques to decrease the interference and the probabilities of false alarm and missed detection. Finally, we discuss the general countermeasures of security threats in three phases. In particular, we discuss the far reaching effect of defensive strategy against attacks in CRNs.
Cognitive radio (CR) is regarded as an emerging technology, which equips wireless devices with the capability to adapt their operating parameters on the fly based on the radio environment, to utilize the scarce radio frequency (RF) spectrum in an efficient and opportunistic manner. However, due to the increasingly pervasive existence of smart wireless devices in cognitive radio network (CRN), CR systems are vulnerable to numerous security threats that affect the overall performance. There have been many significant advances on security threats and countermeasures in CRN in the past few years. Our main goal in this paper is to present the state-of-the-art research results and approaches proposed for CRN security to protect both unlicensed secondary users (SUs) and licensed primary users (PUs). Specifically, we present the recent advances on security threats/attacks and countermeasures in CRN focusing more on physical layer by categorizing them in terms of their types, their existence in CR cycle, network protocol layers (exploited during their activities and defense strategies), and game theoretic approaches. The recent important attacks and countermeasures in CRN are also summarized in form of tables. We also present recommendations that can be followed while implementing countermeasures to enhance CRN security. With this article, readers can have a more thorough understanding of CRN security attacks and countermeasures, and research trends in this area.
Cognitive radio networks were established by IEEE 802.22 wireless regional area network (WRAN) to allow unlicensed users utilize the idle TV band opportunistically. Although many researches were done for diminishing the effect of security vulnerable, the security issues are still open problems. One of the most important attacks in physical layer of cognitive radio is primary user emulation attack (PUEA). In this paper, comprehensive studies about probability of successful PUEA over general wireless propagation environments are scrutinized. The analyses started with considering path loss/shadowing and also path loss/fading scenarios which are important starting points of investigation a general case. In the general case, the wireless propagation model is supposed consisting of Nakagami-m fading superimposed on lognormal shadowing and path loss with considering IEEE 802.22 standard. Numerical results demonstrate that successful PUEA could be obtained at long distance of a good secondary user by increasing the number of collaborative malicious users.
Though research in the vulnerabilities of cognitive radio exists, few explore the threat vectors against both the cognitive engine and the underlying SDR infrastructure within which it operates. Presenting a risk assessment methodology, this paper takes such a holistic approach and then further contributes to the research area by offering three misuse cases that portray how the vulnerabilities discussed could be exploited. Specifically, these cases visualise the risk environment based on a denial of service, an advanced persistent threat, and an insider threat and will allow for security practitioners to anticipate how their organisations may be impacted. Finally, suggested techniques for mitigation of these risks are discussed. As with all emerging technologies, there are a number of unknown conditions or influences that will shape the eventual realisation of its maturity. Risk management is the best mechanism to address those unknowns.
The cognitive radio is an emerging technology that holds great promise due to its adaptive nature and ability to exploit the advantages inherent to software defined radios (SDR). The cognitive radio's potential to address spectrum access challenges resulting from an exponential increase in the number of network devices will make it a leading technology of the next decade. For this reason, it is imperative to investigate the security considerations of the cognitive radio in its infancy rather than attempt to address them at maturity. Though research in the vulnerabilities of cognitive radio exists, few explore the threat vectors against both the cognitive engine and the underlying SDR infrastructure within which it operates. This paper takes such a holistic approach, and then further contributes to the research area by offering three misuse cases that portray how the vulnerabilities discussed could be exploited. These cases visualize the risk environment based on a denial of service, an advanced persistent threat, and an insider threat and will allow for security practitioners to anticipate how their organizations may be impacted. Moreover, by introducing a simulation of the threat one can use existing principles to analyze its prosecution (i.e. attack graphs, evidence graphs, etc.).
GPS is a radio navigation system that provides accurate navigation signals to any place on Earth. Although GPS was originally designed for military applications, GPS has also been used in many civilian applications. The reliability of GPS receivers and the availability of GPS signals have become crucial in the fast-growing use of GPS in military and civilian applications. GPS is designed as a spread spectrum system in order to provide resistance to jamming. Denial of service of GPS receivers in some European countries (intentional or unintentional jamming) has been reported. In addition, the production of GPS jammers increases doubts about GPS signal availability and GPS receiver reliability. The paper aims to investigate GPS receiver performance under different jamming waveforms. In order to determine GPS receiver performance, the GPS signal structure has been analyzed, and GPS jamming strategies and GPS receiver architectures have been investigated. A generic GPS receiver model is implemented using the MATLAB/SIMULINK tool. Since jamming strategies mainly disturb a GPS receiver's signal processing functions, only the signal processing functions of the GPS receiver are investigated. The effect of several GPS jamming strategies are investigated by simulation.
Cognitive Radio (CR) is seen as one of the enabling tech- nologies for realizing a new spectrum access paradigm, viz. Opportunistic Spectrum Sharing (OSS). IEEE 802.22 is the world's flrst wireless standard based on CR technology. It deflnes the air interface for a wireless regional area network (WRAN) that uses fallow segments of the licensed (incum- bent) TV broadcast bands. CR technology enables unli- censed (secondary) users in WRANs to utilize licensed spec- trum bands on a non-interference basis to incumbent users. The coexistence between incumbent users and secondary users is referred to as incumbent coexistence. On the other hand, the coexistence between secondary users in difierent WRAN cells is referred to as self-coexistence. The 802.22 draft standard prescribes several mechanisms for address- ing incumbent- and self-coexistence issues. In this paper, we describe how adversaries can exploit or undermine such mechanisms to degrade the performance of 802.22 WRANs and increase the likelihood of those networks interfering with incumbent networks. The standard includes a security sub- layer to provide subscribers with privacy, authentication, and confldentiality. Our investigation, however, revealed that the security sublayer falls short of addressing all of the key security threats. We also discuss countermeasures that may be able to address those threats.
Cognitive radio (CR) is regarded as one of the best options to solve the problem of low spectrum utilization. However, information security of CR limits its wide application. Most of the known security schemes are aiming at the location verification for incumbent transmitter, but it is not available for Ad hoc. In this paper, a new security scenario in physical layer is proposed. It takes advantage of the "fingerprint" verification of the transmitter against primary user emulation (PUE) attacks. The phase noise of the noisy carrier is extracted from the received modulated signal and directly applied to identify the transmitter.security schemesprimary user emulation attacks.
With the advent of cognitive radios, existing wireless networks are expected to undergo a radical change in how they operate. Traditional wireless devices operate in fixed frequency bands and follow fixed network protocols set at the time of manufacture, unlike the emerging wireless devices based on cognitive radio technology which are expected to operate across multiple frequency bands with a variety of protocols that can change over the life of the device. While the wireless networks in which a cognitive radio device operates may implement device authentication, integrity checks and other higher-layer security mechanisms; the possibility of physical layer attacks, such as jamming attacks, still exists. This research work focuses on assessing potential cognitive radio specific physical layer attacks using the so-called Hammer model. In particular, we investigate vulnerabilities that may prevent CR communication in specific bands, completely deny a cognitive radio to communicate or induce it to cause harmful interference to existing users; so called denial-of-service attacks. In the process, we identify, analyze, and assess the risk level posed by the potential attacks in the different CR design paradigms proposed by different research groups. Further, this work recommends the most and least susceptible of the CR design paradigms under consideration.
Security in wireless networks is challenging. Security in cognitive radio networks (CRN) is even more challenging. This is because a CRN consists of cognitive radios (CR) which have many more functions and processes to account for, such as sensing, geolocation, spectrum management, access to the policy database etc. Each of these functions and processes need to be assessed for potential vulnerabilities and security mechanisms need to be provided for protection of not just the secondary users of the spectrum but also the primary users or the incumbents. This paper discusses the potential security vulnerabilities and the remediations for the same in a CRN with an example using a commercial IEEE 802.22 standard. Due to the unique characteristics of the CRs in a CRN, enhanced security mechanisms are required. The security mechanisms in CRN are divided into several security sub-layers which protect non-cognitive as well as cognitive functions of the system and the interactions between the two. This paper describes these security features as incorporated into the IEEE 802.22 standard. It is possible to apply similar security mechanisms for a military CRN.
Cognitive radios sense spectrum activity and apply spectrum policies in order to make decisions on when and in what bands they may communicate. These activities go beyond what is done when traditional radios communicate. This paper examines the denial of service vulnerabilities that are opened by these additional activities and explores potential protection remedies that can be applied. An analysis of how vulnerable are victim cognitive radios to potential denial of service attacks is presented along different axis, namely the network architecture employed, the spectrum access technique used and the spectrum awareness model. The goal is to assist cognitive radio designers to incorporate effective security measures now in the early stages of cognitive radio development.
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