Biblio

Cognitive radio technology addresses the spectrum scarcity challenges by allowing unlicensed cognitive devices to opportunistically utilize spectrum band allocated to licensed devices. However, the openness of the technology has introduced several attacks to cognitive radios, one which is the spectrum sensing data falsification attack. In spectrum sensing data falsification attack, malicious devices share incorrect spectrum observations to other cognitive radios. This paper investigates the spectrum sensing data falsification attack in cognitive radio networks. We use the modified Z-test to isolate extreme outliers in the network. The q-out-of-m rule scheme is implemented to mitigate the spectrum sensing data falsification attack, where a random number m is selected from the sensing results and q is the final decision from m. The scheme does not require the services of a fusion Centre for decision making. This paper presents the theoretical analysis of the proposed scheme.

The ever-increasing number of wireless network systems brought a problem of spectrum congestion leading to slow data communications. All of the radio spectrums are allocated to different users, services and applications. Hence studies have shown that some of those spectrum bands are underutilized while others are congested. Cognitive radio concept has evolved to solve the problem of spectrum congestion by allowing cognitive users to opportunistically utilize the underutilized spectrum while minimizing interference with other users. Byzantine attack is one of the security issues which threaten the successful deployment of this technology. Byzantine attack is compromised cognitive radios which relay falsified data about the availability of the spectrum to other legitimate cognitive radios in the network leading interference. In this paper we are proposing a security measure to thwart the effect caused by these attacks and compared it to Attack-Proof Cooperative Spectrum Sensing.

Utilization of Wireless sensor network is growing with the development in modern technologies. On other side electromagnetic spectrum is limited resources. Application of wireless communication is expanding day by day which directly threaten electromagnetic spectrum band to become congested. Cognitive Radio solves this issue by implementation of unused frequency bands as "White Space". There is another important factor that gets attention in cognitive model i.e: Wireless Security. One of the famous causes of security threat is malicious node in cognitive radio wireless sensor networks (CRWSN). The goal of this paper is to focus on security issues which are related to CRWSN as Fusion techniques, Co-operative Spectrum sensing along with two dangerous attacks in CR: Primary User Emulation (PUE) and Spectrum Sensing Data Falsification (SSDF).

In order to cater the growing spectrum demands of large scale future 5G Internet of Things (IoT) applications, Dynamic Spectrum Access (DSA) based networks are being proposed as a high-throughput and cost-effective solution. However the lack of understanding of DSA paradigm's inherent security vulnerabilities on IoT networks might become a roadblock towards realizing such spectrum aware 5G vision. In this paper, we make an attempt to understand how such inherent DSA vulnerabilities in particular Spectrum Sensing Data Falsification (SSDF) attacks can be exploited by collaborative group of selfish adversaries and how that can impact the performance of spectrum aware IoT applications. We design a utility based selfish adversarial model mimicking collaborative SSDF attack in a cooperative spectrum sensing scenario where IoT networks use dedicated environmental sensing capability (ESC) for spectrum availability estimation. We model the interactions between the IoT system and collaborative selfish adversaries using a leader-follower game and investigate the existence of equilibrium. Using simulation results, we show the nature of adversarial and system utility components against system variables. We also explore Pareto-optimal adversarial strategy design that maximizes the attacker utility for varied system strategy spaces.

Cognitive Radio (CR) has garnered much attention in the last decade, while the security issues are not fully studied yet. Existing research on attacks and defenses in CR - based networks focuses mostly on individual network layers, whereas cross-layer attacks remain fortified against single-layer defenses. In this paper, we shed light on a new vulnerability in cross-layer routing protocols and demonstrate how a perpetrator can exploit this vulnerability to manipulate traffic flow around it. We propose this cross-layer attack in CR-based wireless mesh networks (CR-WMNs), which we call off-sensing and route manipulation (OS-RM) attack. In this cross-layer assault, off-sensing attack is launched at the lower layers as the point of attack but the final intention is to manipulate traffic flow around the perpetrator. We also introduce a learning strategy for a perpetrator, so that it can gather information from the collaboration with other network entities and capitalize this information into knowledge to accelerate its malice intentions. Simulation results show that this attack is far more detrimental than what we have experienced in the past and need to be addressed before commercialization of CR-based networks.

security evaluation of cryptosystem is a critical topic in cryptology. It is used to differentiate among cryptosystems' security. The aim of this paper is to produce a new model for security evaluation of cryptosystems, which is a combination of two theories (Game Theory and Information Theory). The result of evaluation method can help researchers to choose the appropriate cryptosystems in Wireless Communications Networks such as Cognitive Radio Networks.

This paper investigates closed-form expressions to evaluate the performance of the Compressive Sensing (CS) based Energy Detector (ED). The conventional way to approximate the probability density function of the ED test statistic invokes the central limit theorem and considers the decision variable as Gaussian. This approach, however, provides good approximation only if the number of samples is large enough. This is not usually the case in CS framework, where the goal is to keep the sample size low. Moreover, working with a reduced number of measurements is of practical interest for general spectrum sensing in cognitive radio applications, where the sensing time should be sufficiently short since any time spent for sensing cannot be used for data transmission on the detected idle channels. In this paper, we make use of low-complexity approximations based on algebraic transformations of the one-dimensional Gaussian Q-function. More precisely, this paper provides new closed-form expressions for accurate evaluation of the CS-based ED performance as a function of the compressive ratio and the Signal-to-Noise Ratio (SNR). Simulation results demonstrate the increased accuracy of the proposed equations compared to existing works.

Internet of Things (IoT) will be emerged over many of devices that are dynamically networked. Because of distributed and dynamic nature of IoT, designing a recommender system for them is a challenging problem. Recently, cognitive systems are used to design modern frameworks in different types of computer applications such as cognitive radio networks and cognitive peer-to-peer networks. A cognitive system can learn to improve its performance while operating under its unknown environment. In this paper, we propose a framework for cognitive recommender systems in IoT. To the best of our knowledge, there is no recommender system based on cognitive systems in the IoT. The proposed algorithm is compared with the existing recommender systems.

In this paper, a distributed architecture for the implementation of smart city has been proposed to facilitate various smart features like solid waste management, efficient urban mobility and public transport, smart parking, robust IT connectivity, safety and security of citizens and a roadmap for achieving it. How massive volume of IoT data can be analyzed and a layered architecture of IoT is explained. Why data integration is important for analyzing and processing of data collected by the different smart devices like sensors, actuators and RFIDs is discussed. The wireless sensor network can be used to sense the data from various locations but there has to be more to it than stuffing sensors everywhere for everything. Why only the sensor is not sufficient for data collection and how human beings can be used to collect data is explained. There is some communication protocols between the volunteers engaged in collecting data to restrict the sharing of data and ensure that the target area is covered with minimum numbers of volunteers. Every volunteer should cover some predefined area to collect data. Then the proposed architecture model is having one central server to store all data in a centralized server. The data processing and the processing of query being made by the user is taking place in centralized server.

Cooperative spectrum sensing is often necessary in cognitive radios systems to localize a transmitter by fusing the measurements from multiple sensing radios. However, revealing spectrum sensing information also generally leaks information about the location of the radio that made those measurements. We propose a protocol for performing cooperative spectrum sensing while preserving the privacy of the sensing radios. In this protocol, radios fuse sensing information through a distributed particle filter based on a tree structure. All sensing information is encrypted using public-key cryptography, and one of the radios serves as an anonymizer, whose role is to break the connection between the sensing radios and the public keys they use. We consider a semi-honest (honest-but-curious) adversary model in which there is at most a single adversary that is internal to the sensing network and complies with the specified protocol but wishes to determine information about the other participants. Under this scenario, an adversary may learn the sensing information of some of the radios, but it does not have any way to tie that information to a particular radio's identity. We test the performance of our proposed distributed, tree-based particle filter using physical measurements of FM broadcast stations.

The wireless spectrum is a scarce resource, and the number of wireless terminals is constantly growing. One way to mitigate this strong constraint for wireless traffic is the use of dynamic mechanisms to utilize the spectrum, such as cognitive and software-defined radios. This is especially important for the upcoming wireless sensor and actuator networks in aircraft, where real-time guarantees play an important role in the network. Future wireless networks in aircraft need to be scalable, cater to the specific requirements of avionics (e.g., standardization and certification), and provide interoperability with existing technologies. In this paper, we demonstrate that dynamic network reconfigurability is a solution to the aforementioned challenges. We supplement this claim by surveying several flexible approaches in the context of wireless sensor and actuator networks in aircraft. More specifically, we examine the concept of dynamic resource management, accomplished through more flexible transceiver hardware and by employing dedicated spectrum agents. Subsequently, we evaluate the advantages of cross-layer network architectures which overcome the fixed layering of current network stacks in an effort to provide quality of service for event-based and time-triggered traffic. Lastly, the challenges related to implementation of the aforementioned mechanisms in wireless sensor and actuator networks in aircraft are elaborated, and key requirements to future research are summarized.

Dynamic spectrum sharing techniques applied in the UHF TV band have been developed to allow secondary WiFi transmission in areas with active TV users. This technique of dynamically controlling the exclusion zone enables vastly increasing secondary spectrum re-use, compared to the "TV white space" model where TV transmitters determine the exclusion zone and only "idle" channels can be re-purposed. However, in current such dynamic spectrum sharing systems, the sensitive operation parameters of both primary TV users (PUs) and secondary users (SUs) need to be shared with the spectrum database controller (SDC) for the purpose of realizing efficient spectrum allocation. Since such SDC server is not necessarily operated by a trusted third party, those current systems might cause essential threatens to the privacy requirement from both PUs and SUs. To address this privacy issue, this paper proposes a privacy-preserving spectrum sharing system between PUs and SUs, which realizes the spectrum allocation decision process using efficient multi-party computation (MPC) technique. In this design, the SDC only performs secure computation over encrypted input from PUs and SUs such that none of the PU or SU operation parameters will be revealed to SDC. The evaluation of its performance illustrates that our proposed system based on efficient MPC techniques can perform dynamic spectrum allocation process between PUs and SUs efficiently while preserving users' privacy.

Cloud-centric cognitive cellular networks utilize dynamic spectrum access and opportunistic network access technologies as a means to mitigate spectrum crunch and network demand. However, furnishing a carrier with personally identifiable information for user setup increases the risk of profiling in cognitive cellular networks, wherein users seek secondary access at various times with multiple carriers. Moreover, network access provisioning - assertion, authentication, authorization, and accounting - implemented in conventional cellular networks is inadequate in the cognitive space, as it is neither spontaneous nor scalable. In this paper, we propose a privacy-enhancing user identity management system using blockchain technology which places due importance on both anonymity and attribution, and supports end-to-end management from user assertion to usage billing. The setup enables network access using pseudonymous identities, hindering the reconstruction of a subscriber's identity. Our test results indicate that this approach diminishes access provisioning duration by up to 4x, decreases network signaling traffic by almost 40%, and enables near real-time user billing that may lead to approximately 3x reduction in payments settlement time.

Cooperative MIMO communication is a promising technology which enables realistic solution for improving communication performance with MIMO technique in wireless networks that are composed of size and cost constrained devices. However, the security problems inherent to cooperative communication also arise. Cryptography can ensure the confidentiality in the communication and routing between authorized participants, but it usually cannot prevent the attacks from compromised nodes which may corrupt communications by sending garbled signals. In this paper, we propose a cross-layered approach to enhance the security in query-based cooperative MIMO sensor networks. The approach combines efficient cryptographic technique implemented in upper layer with a novel information theory based compromised nodes detection algorithm in physical layer. In the detection algorithm, a cluster of K cooperative nodes are used to identify up to K - 1 active compromised nodes. When the compromised nodes are detected, the key revocation is performed to isolate the compromised nodes and reconfigure the cooperative MIMO sensor network. During this process, beamforming is used to avoid the information leaking. The proposed security scheme can be easily modified and applied to cognitive radio networks. Simulation results show that the proposed algorithm for compromised nodes detection is effective and efficient, and the accuracy of received information is significantly improved.

We consider an underlay cognitive network with secondary users that support full-duplex communication. In this context, we propose the application of antenna selection at the secondary destination node to improve the secondary user secrecy performance. Antenna selection rules for cases where exact and average knowledge of the eavesdropping channels are investigated. The secrecy outage probabilities for the secondary eavesdropping network are analyzed, and it is shown that the secrecy performance improvement due to antenna selection is due to coding gain rather than diversity gain. This is very different from classical antenna selection for data transmission, which usually leads to a higher diversity gain. Numerical simulations are included to verify the performance of the proposed scheme.

This paper investigates the secrecy performance of full-duplex relay mode in underlay cognitive radio networks using decode-and-forward relay selection. The analytical results prove that full-duplex mode can guarantee security under critical conditions such as the bad residual self-interference and the presence of hi-tech eavesdropper. The secrecy outage probability is derived based on the statistical characteristics of channels in this considered system. The system is examined under five circumferences: 1) Different values of primary network's desired outage probability; 2) Different values of primary transmitter's transmit power; 3) Applying of multiple relays selection; 4) Systems undergo path-loss during the transmission process; 5) Systems undergo self-interference in relays. Simulation results are presented to verify the analysis.

We address secure resource allocation for an OFDMA cooperative cognitive radio network (CRN) with energy harvesting (EH) capability. In the network, one primary user (PU) cooperates with several untrusted secondary users (SUs) with one SU transmitter and several SU receivers, where the SU transmitter and all SU receivers may overhear the PU transmitter's information while all SU receivers may eavesdrop on each other's signals. We consider the scenario when SUs are wireless devices with small physical sizes; therefore to improve system performance we suppose that SUs are equipped with co-located orthogonally dual-polarized antennas (ODPAs). With ODPAs, on one hand, the SU transmitter can first harvest energy from radio frequency (RF) signals emitted by the PU transmitter, and then utilize the harvested energy to simultaneously serve the PU and all SU receivers. On the other hand, by exploiting polarization-based signal processing techniques, both the PU's and SUs' physical-layer security can be enhanced. In particular, to ensure the PU's communication security, the PU receiver also sends jamming signals to degrade the reception performance of SUs, and meanwhile the jamming signals can also become new sources of energy powering the SU transmitter. For the considered scenario, we investigate the joint allocation of subcarriers, powers, and power splitting ratios to maximize the total secrecy rate of all SUs while ensuring the PU's minimum secrecy rate requirement. Finally, we evaluate the performance of our resource allocation scheme through numerical analyses.

The exponential growth in the number of mobile devices, combined with the rapid demand for wireless services, has steadily stressed the wireless spectrum, calling for new techniques to improve spectrum utilization. A geo-location database has been proposed as a viable solution for wireless users to determine spectrum availability in cognitive radio networks. The protocol used by secondary users (SU) to request spectral availability for a specific location, time and duration, may reveal confidential information about these users. In this paper, we focus on SUs' location privacy in database-enabled wireless networks and propose a framework to address this threat. The basic tenet of the framework is obfuscation, whereby channel requests for valid locations are interwoven with requests for fake locations. Traffic redirection is also used to deliberately confuse potential query monitors from inferring users' location information. Within this framework, we propose two privacy-preserving schemes. The Master Device Enabled Location Privacy Preserving scheme utilizes trusted master devices to prevent leaking information of SUs' locations to attackers. The Crowd Sourced Location Privacy Preserving scheme builds a guided tour of randomly selected volunteers to deliver users channel availability queries and ensure location privacy. Security analysis and computational and communication overhead of these schemes are discussed.

Reliable detection of intrusion is the basis of safety in cognitive radio networks (CRNs). So far, few scholars applied intrusion detection systems (IDSs) to combat intrusion against CRNs. In order to improve the performance of intrusion detection in CRNs, a distributed intrusion detection scheme has been proposed. In this paper, a method base on Dempster-Shafer's (D-S) evidence theory to detect intrusion in CRNs is put forward, in which the detection data and credibility of different local IDS Agent is combined by D-S in the cooperative detection center, so that different local detection decisions are taken into consideration in the final decision. The effectiveness of the proposed scheme is verified by simulation, and the results reflect a noticeable performance improvement between the proposed scheme and the traditional method.

Primary user emulation (PUE) attack is one of the main threats affecting cognitive radio (CR) networks. The PUE can forge the same signal as the real primary user (PU) in order to use the licensed channel and cause deny of service (DoS). Therefore, it is important to locate the position of the PUE in order to stop and avoid any further attack. Several techniques have been proposed for localization, including the received signal strength indication RSSI, Triangulation, and Physical Network Layer Coding. However, the area surrounding the real PU is always affected by uncertainty. This uncertainty can be described as a lost (cost) function and conditional probability to be taken into consideration while proclaiming if a PU/PUE is the real PU or not. In this paper, we proposed a combination of a Bayesian model and trilateration technique. In the first part a trilateration technique is used to have a good approximation of the PUE position making use of the RSSI between the anchor nodes and the PU/PUE. In the second part, a Bayesian decision theory is used to claim the legitimacy of the PU based on the lost function and the conditional probability to help to determine the existence of the PUE attacker in the uncertainty area.

Recently, some papers that apply a multi-armed bandit algorithm for channel selection in a cognitive radio system have been reported. In those papers, channel selection based on Upper Confidence Bound (UCB) algorithm has been proposed. However, in those selection, secondary users are not allowed to transmit data over same channels at the same time. Moreover, they do not take security of wireless communication into account. In this paper, we propose secure channel selection methods based on UCB algorithm, taking secrecy capacity into account. In our model, secondary users can share same channel by using transmit time control or transmit power control. Our proposed methods lead to be secure against an eavesdropper compared to conventional channel selections based on only estimated channel availability. By computer simulation, we evaluate average system secrecy capacity. As a result, we show that our proposed channel selections improve average system secrecy capacity compared to conventional channel selection.

Cognitive radio networks (CRNs) have a great potential in supporting time-critical data delivery among the Internet of Things (IoT) devices and for emerging applications such as smart cities. However, the unique characteristics of different technologies and shared radio operating environment can significantly impact network availability. Hence, in this paper, we study the channel assignment problem in time-critical IoT-based CRNs under proactive jamming attacks. Specifically, we propose a probabilistic spectrum assignment algorithm that aims at minimizing the packet invalidity ratio of each cognitive radio (CR) transmission subject to delay constrains. We exploit the statistical information of licensed users' activities, fading conditions, and jamming attacks over idle channels. Simulation results indicate that network performance can be significantly improved by using a security- availability- and quality-aware channel assignment that provides communicating CR pair with the most secured channel of the lowest invalidity ratio.

The cooperative spectrum leasing process between the primary user (PU) and the secondary user (SU) in a cognitive radio network under the overlay approach and the decode and forward (DF) cooperative protocol is studied. Considering the Quality of Service (QoS) provisioning of both users, which participate in a three-phase leasing process, we investigate the maximization of PU's effective capacity subject to an average energy constraint for the SU under a heuristic power and time allocation mechanism. The aforementioned proposed scheme treats with the basic concepts of the convex optimization theory and outperforms a baseline allocation mechanism which is proven by the simulations. Finally, important remarks for the PU's and the SU's performance are extracted for different system parameters.

Cognitive radio (CR) has emerged as a promising technology to increase the utilization of spectrum resource. A pivotal challenge in CR lies on secondary users' (SU) finding each other on the frequency band, i.e., the spectrum locating. In this demo, we implement two kinds of multi-channel rendezvous technology to solve the problem of spectrum locating: (i) the common control channel (CCC) based rendezvous scheme, which is simple and effective when a control channel is always available; and (ii) the channel-hopping (CH) based blind rendezvous, which could also obtain guaranteed rendezvous on all commonly available channels of pairwise SUs in a short time without a CCC. Furthermore, the cognitive nodes in the demonstration could adjust their communication channels autonomously according to the dynamic spectrum environment for continuous data transmission.

As smart grid becomes more popular and emergent, the need for reliable communication technology becomes crucial to ensure the proper and efficient operation of the grid. Therefore, cognitive radio has been recently utilized to provide a scalable and reliable communication infrastructure for smart grid. However, accurate spectrum sensing is the core of this infrastructure. In this paper, we propose an architecture, utilizing Role-Based Delegation to manage spectrum sensing within the cognitive-radio-based communication infrastructure for smart grid and ensure its reliability and security.