Biblio
This paper investigates the effectiveness of reinforcement learning (RL) model in clustering as an approach to achieve higher network scalability in distributed cognitive radio networks. Specifically, it analyzes the effects of RL parameters, namely the learning rate and discount factor in a volatile environment, which consists of member nodes (or secondary users) that launch attacks with various probabilities of attack. The clusterhead, which resides in an operating region (environment) that is characterized by the probability of attacks, countermeasures the malicious SUs by leveraging on a RL model. Simulation results have shown that in a volatile operating environment, the RL model with learning rate α= 1 provides the highest network scalability when the probability of attacks ranges between 0.3 and 0.7, while the discount factor γ does not play a significant role in learning in an operating environment that is volatile due to attacks.
In cognitive radio networks (CRNs), secondary users (SUs) are vulnerable to malicious attacks because an SU node's opportunistic access cannot be protected from adversaries. How to design a channel hopping scheme to protect SU nodes from jamming attacks is thus an important issue in CRNs. Existing anti-jamming channel hopping schemes have some limitations: Some require SU nodes to exchange secrets in advance; some require an SU node to be either a receiver or a sender, and some are not flexible enough. Another issue for existing anti-jamming channel hopping schemes is that they do not consider different nodes may have different traffic loads. In this paper, we propose an anti-jamming channel hopping protocol, Load Awareness Anti-jamming channel hopping (LAA) scheme. Nodes running LAA are able to change their channel hopping sequences based on their sending and receiving traffic. Simulation results verify that LAA outperforms existing anti-jamming schemes.
With the improvement in technology and with the increase in the use of wireless devices there is deficiency of radio spectrum. Cognitive radio is considered as the solution for this problem. Cognitive radio is capable to detect which communication channels are in use and which are free, and immediately move into free channels while avoiding the used ones. This increases the usage of radio frequency spectrum. Any wireless system is prone to attack. Likewise, the main two attacks in the physical layer of cognitive radio are Primary User Emulation Attack (PUEA) and replay attack. This paper focusses on mitigating these two attacks with the aid of authentication tag and distance calculation. Mitigation of these attacks results in error free transmission which in turn fallouts in efficient dynamic spectrum access.
The primary objective of Cognitive Radio Networks (CRN) is to opportunistically utilize the available spectrum for efficient and seamless communication. Like all other radio networks, Cognitive Radio Network also suffers from a number of security attacks and Primary User Emulation Attack (PUEA) is vital among them. Primary user Emulation Attack not only degrades the performance of the Cognitive Radio Networks but also dissolve the objective of Cognitive Radio Network. Efficient and secure authentication of Primary Users (PU) is an only solution to mitigate Primary User Emulation Attack but most of the mechanisms designed for this are either complex or make changes to the spectrum. Here, we proposed a mechanism to authenticate Primary Users in Cognitive Radio Network which is neither complex nor make any changes to spectrum. The proposed mechanism is secure and also has improved the performance of the Cognitive Radio Network substantially.
In this article, we study the transmission secrecy performance of primary user in overlay cognitive wireless networks, in which an untrusted energy-limited secondary cooperative user assists the primary transmission to exchange for the spectrum resource. In the network, the information can be simultaneously transmitted through the direct and relay links. For the enhancement of primary transmission security, a maximum ratio combining (MRC) scheme is utilized by the receiver to exploit the two copies of source information. For the security analysis, we firstly derive the tight lower bound expression for secrecy outage probability (SOP). Then, three asymptotic expressions for SOP are also expressed to further analyze the impacts of the transmit power and the location of secondary cooperative node on the primary user information security. The findings show that the primary user information secrecy performance enhances with the improvement of transmit power. Moreover, the smaller the distance between the secondary node and the destination, the better the primary secrecy performance.
Software-defined wireless sensor cognitive radio network is one of the emerging technologies which is simple, agile, and flexible. The sensor network comprises of a sink node with high processing power. The sensed data is transferred to the sink node in a hop-by-hop basis by sensor nodes. The network is programmable, automated, agile, and flexible. The sensor nodes are equipped with cognitive radios, which sense available spectrum bands and transmit sensed data on available bands, which improves spectrum utilization. Unfortunately, the Software-defined wireless sensor cognitive radio network is prone to security issues. The sinkhole attack is the most common attack which can also be used to launch other attacks. We propose and evaluate the performance of Hop Count-Based Sinkhole Attack detection Algorithm (HCOBASAA) using probability of detection, probability of false negative, and probability of false positive as the performance metrics. On average HCOBASAA managed to yield 100%, 75%, and 70% probability of detection.
Primary user emulation (PUE) attack causes security issues in a cognitive radio network (CRN) while sensing the unused spectrum. In PUE attack, malicious users transmit an emulated primary signal in spectrum sensing interval to secondary users (SUs) to forestall them from accessing the primary user (PU) spectrum bands. In the present paper, the defense against such attack by Neyman-Pearson criterion is shown in terms of total error probability. Impact of several parameters such as attacker strength, attacker's presence probability, and signal-to-noise ratio on SU is shown. Result shows proposed method protect the harmful effects of PUE attack in spectrum sensing.
With the rapid proliferation of mobile users, the spectrum scarcity has become one of the issues that have to be addressed. Cognitive Radio technology addresses this problem by allowing an opportunistic use of the spectrum bands. In cognitive radio networks, unlicensed users can use licensed channels without causing harmful interference to licensed users. However, cognitive radio networks can be subject to different security threats which can cause severe performance degradation. One of the main attacks on these networks is the primary user emulation in which a malicious node emulates the characteristics of the primary user signals. In this paper, we propose a detection technique of this attack based on the RSS-based localization with the maximum likelihood estimation. The simulation results show that the proposed technique outperforms the RSS-based localization method in detecting the primary user emulation attacker.
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 this paper, the security performance of a dual-hop underlay cognitive radio (CR) system is investigated. In this system, we consider that the transmitted information by a source node S is forwarded by a multi-antenna relay R to its intended destination D. The relay performs the maximal-ratio combining (MRC) technique to process the multiple copies of the received signal. We also consider the presence of an eavesdropper who is attempting to intercept the transmitted information at both communication links, (i.e, S-R and R-D). In underlay cognitive radio networks (CRN), the source and the relay are required to adjust their transmission power to avoid causing interference to the primary user. Under this constraint, a closed-form expression of the secrecy outage probability is derived subject to Nakagami-m fading model. The derived expression is validated using Monte-Carlo simulation for various values of fading severity parameters as well as the number of MRC branches.
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.