Spectrum Sensing and Mitigation of Primary User Emulation Attack in Cognitive Radio

The overwhelming growth of wireless communication has led to spectrum shortage issues. In recent days, cognitive radio (CR) has risen as a complete solution for the issue. It is an artificial intelligence-based radio which is capable of finding the free spectrum and utilises it by adapting itself to the environment. Hence, searching of the free spectrum becomes the key task of the cognitive radio termed as spectrum sensing. Some malicious users disrupt the decision-making ability of the cognitive radio. Proper selection of the spectrum scheme and decision-making capability of the cognitive reduces the chance of colliding with the primary user. This chapter discusses the suitable spectrum sensing scheme for low noise environment and a trilayered solution to mitigate the primary user emulation attack (PUEA) in the physical layer of the cognitive radio. The tag is generated in three ways. Sequences were generated using DNA and chaotic algorithm. These sequences are then used as the initial seed value for the generation of gold codes. The output of the generator is considered as the authentication tag. This tag is used to identify the malicious user, thereby PUEA is mitigated. Threat-free environment enables the cognitive radio to come up with a precise decision about the spectrum holes

Malicious User Attack in Cognitive Radio Networks

Signal detection in cognitive radio network (CRN) is influenced by several factors. One of them is malicious user that emulate primary user (PU) signal. Emulation of PU signal causes detection error. This paper investigates the impact of malicious user attack to PU signal detection. A number of malicious users are randomly deployed around secondary user (SU) at a certain distance. They attempt to attack primary signal detection that is transmitted from 100 km to SU receiver. Then, the received signal power at secondary receiver and the performance of probability of false alarm and probability of miss detection under two hypothesis of Neyman Pearson criterion are studied. The derived results show that a number of malicious users has a significant impact to the performance of received power at SU and detection error rate

Primary User Emulation Detection in Cognitive Radio Networks

Cognitive radios (CRs) have been proposed as a promising solution for improving spectrum utilization via opportunistic spectrum sharing. In a CR network environment, primary (licensed) users have priority over secondary (unlicensed) users when accessing the wireless channel. Thus, if a malicious secondary user exploits this spectrum access etiquette by mimicking the spectral characteristics of a primary user, it can gain priority access to a wireless channel over other secondary users. This scenario is referred to in the literature as primary user emulation (PUE). This dissertation first covers three approaches for detecting primary user emulation attacks in cognitive radio networks, which can be classified in two categories. The first category is based on cyclostationary features, which employs a cyclostationary calculation to represent the modulation features of the user signals. The calculation results are then fed into an artificial neural network for classification. The second category is based on video processing method of action recognition in frequency domain, which includes two approaches. Both of them analyze the FFT sequences of wireless transmissions operating across a cognitive radio network environment, as well as classify their actions in the frequency domain. The first approach employs a covariance descriptor of motion-related features in the frequency domain, which is then fed into an artificial neural network for classification. The second approach is built upon the first approach, but employs a relational database system to record the motion-related feature vectors of primary users on this frequency band. When a certain transmission does not have a match record in the database, a covariance descriptor will be calculated and fed into an artificial neural network for classification. This dissertation is completed by a novel PUE detection approach which employs a distributed sensor network, where each sensor node works as an independent PUE detector. The emphasis of this work is how these nodes collaborate to obtain the final detection results for the whole network. All these proposed approaches have been validated via computer simulations as well as by experimental hardware implementations using the Universal Software Radio Peripheral (USRP) software-defined radio (SDR) platform

AN INVESTIGATION OF SECURITY CHALLENGES IN COGNITIVE RADIO NETWORKS

The recent advances in wireless communication have led to the problem of growing spectrum scarcity. The available wireless spectrum has become scarcer due to increasing spectrum demand for new wireless applications. The large portion of the allocated spectrum is sporadically used leading to underutilization of significant amount of spectrum. To improve the spectrum efficiency, the idea of cognitive radio technology was introduced. This concept of cognitive radio provides a promising solution for the spectrum scarcity issues in wireless networks. Meanwhile, the security issues of cognitive radio have received more attentions recently since the inherent properties of CR networks would pose new challenges to wireless communications. In this MS thesis, general concepts of security threats to the cognitive radio networks are briefly reviewed. Performances for primary user emulation attacks are studied from Neyman-Pearson criterion point of view. A novel system model with different configurations of the primary users has been proposed and studied. Our experimental results demonstrate the statistical characteristics of the probability of false alarm and miss detection in the proposed system. I will make performance comparison with others’ research in the future. Adviser: Yaoqing Yan

AN INVESTIGATION OF SECURITY CHALLENGES IN COGNITIVE RADIO NETWORKS

The recent advances in wireless communication have led to the problem of growing spectrum scarcity. The available wireless spectrum has become scarcer due to increasing spectrum demand for new wireless applications. The large portion of the allocated spectrum is sporadically used leading to underutilization of significant amount of spectrum. To improve the spectrum efficiency, the idea of cognitive radio technology was introduced. This concept of cognitive radio provides a promising solution for the spectrum scarcity issues in wireless networks. Meanwhile, the security issues of cognitive radio have received more attentions recently since the inherent properties of CR networks would pose new challenges to wireless communications. In this MS thesis, general concepts of security threats to the cognitive radio networks are briefly reviewed. Performances for primary user emulation attacks are studied from Neyman-Pearson criterion point of view. A novel system model with different configurations of the primary users has been proposed and studied. Our experimental results demonstrate the statistical characteristics of the probability of false alarm and miss detection in the proposed system. I will make performance comparison with others’ research in the future. Adviser: Yaoqing Yan

Emulación de usuario primario en la red de radio cognitiva móvil: estudio

For emerging networks such as the mobile cognitive radio network, it is essential to study their possible attacks and thus generate detection strategies. Generally attacks are focused on only one layer of the OSI model, they have been studied for each layer from the physical level to the application level and have focused on fixed secondary users. In cognitive radio networks, the primary user emulation (PUE) is the most studied attack since it affects the entire cognitive cycle from the physical layer to the upper layers. This paper defines types of PUE attack and countermeasures, analyzing the effects on fixed and mobile secondary users and attackers.En el caso de las redes emergentes, como la red de radiocomunicaciones cognitivas móviles, es esencial estudiar sus posibles ataques y generar así estrategias de detección. Por lo general, los ataques se centran en una sola capa del modelo OSI, se han estudiado para cada capa desde el nivel físico hasta el nivel de aplicación y se han centrado en los usuarios secundarios fijos. En las redes de radiocomunicaciones cognitivas, la emulación de usuario primario (PUE) es el ataque más estudiado, ya que afecta a todo el ciclo cognitivo desde la capa física hasta las capas superiores. En este documento se definen los tipos de ataque PUE y las contramedidas, analizando los efectos en los usuarios secundarios fijos y móviles y en los atacantes