A Study on Techniques/Algorithms used for Detection and Prevention of Security Attacks in Cognitive Radio Networks

In this paper a detailed survey is carried out on the taxonomy of Security Issues, Advances on Security Threats and Countermeasures ,A Cross-Layer Attack, Security Status and Challenges for Cognitive Radio Networks, also a detailed survey on several Algorithms/Techniques used to detect and prevent SSDF(Spectrum Sensing Data Falsification) attack a type of DOS (Denial of Service) attack and several other  Network layer attacks in Cognitive Radio Network or Cognitive Radio Wireless Sensor Node Networks(WSNN’s) to analyze the advantages and disadvantages of those existing algorithms/techniques

Detection And Prevention Of Types Of Attacks Using Machine Learning Techniques In Cognitive Radio Networks

A number of studies have been done on several types of data link and network layer attacks and defenses for CSS in CRNs, but there are still a number of challenges unsolved and open issues waiting for solutions. Specifically, from the perspective of attackers, when launching the attack, users have to take into account of the factors of attack gain, attack cost and attack risk, together.  From the perspective of defenders, there are also three aspects deserving consideration: defense reliability, defense efficiency and defense universality. The attacks and defenses are mutually coupled from each other. Attackers need to adjust their strategies to keep their negative effects on final decisions and avoid defenders’ detection, while defenders have to learn and analyze attack behaviors and designs effective defense rules. Indeed, attack and defense ought to be considered together. the proposed methodology overcomes the problems of several data link and network layer attacks and it effects in CSS(Co-operative Spectrum Sensing) of CNRs using Machine Learning based Defense, Cross layers optimization techniques and Defence based Prevention mechanisms

Novel Approaches for the Performance Enhancement of Cognitive Radio Networks

This research is dedicated to the study of the challenges faced by Cognitive Radio (CR) networks, which include self-coexistence of the networks in the spectral environment, security and performance threats from malicious entities, and fairness in spectrum contention and utilization. We propose novel channel acquisition schemes that allow decentralized CR networks to have multiple channel access with minimal spectrum contentions. The multiple channel acquisition schemes facilitate fast spectrum access especially in cases where networks cannot communicate with each other. These schemes enable CR networks to self-organize and adapt to the dynamically changing spectral environment. We also present a self-coexistence mechanism that allows CR networks to coexist via the implementation of a risk-motivated channel selection based deference structure (DS). By forming DS coalitions, CR networks are able to have better access to preferred channels and can defer transmission to one another, thereby mitigating spectrum conflicts. CR networks are also known to be susceptible to Sybil threats from smart malicious radios with either monopolistic or disruptive intentions. We formulate novel threat and defense mechanisms to combat Sybil threats and minimize their impact on the performance of CR networks. A dynamic reputation system is proposed that considerably minimizes the effectiveness of intelligent Sybil attacks and improves the accuracy of spectrum-based decision-making processes. Finally, we present a distributed and cheat-proof spectrum contention protocol as an enhancement of the adaptive On-Demand Spectrum Contention (ODSC) protocol. The Modified On-Demand Spectrum Contention (MODSC) protocol enhances fairness and efficiency of spectrum access. We also show that there is substantial improvement in spectrum utilization with the incorporation of channel reuse into the MODSC protocol

A novel MAC Protocol for Cognitive Radio Networks

In Partial Fulfilment of the Requirements for the Degree Doctor of Philosophy from the University of BedfordshireThe scarcity of bandwidth in the radio spectrum has become more vital since the demand for wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum bands and the inefficiency in their utilization have been smartly addressed by the cognitive radio (CR) technology which is an opportunistic network that senses the environment, observes the network changes, and then uses knowledge gained from the prior interaction with the network to make intelligent decisions by dynamically adapting transmission characteristics. In this thesis, recent research and survey about the advances in theory and applications of cognitive radio technology has been reviewed. The thesis starts with the essential background on cognitive radio techniques and systems and discusses those characteristics of CR technology, such as standards, applications and challenges that all can help make software radio more personal. It then presents advanced level material by extensively reviewing the work done so far in the area of cognitive radio networks and more specifically in medium access control (MAC) protocol of CR. The list of references will be useful to both researchers and practitioners in this area. Also, it can be adopted as a graduate-level textbook for an advanced course on wireless communication networks. The development of new technologies such as Wi-Fi, cellular phones, Bluetooth, TV broadcasts and satellite has created immense demand for radio spectrum which is a limited natural resource ranging from 30KHz to 300GHz. For every wireless application, some portion of the radio spectrum needs to be purchased, and the Federal Communication Commission (FCC) allocates the spectrum for some fee for such services. This static allocation of the radio spectrum has led to various problems such as saturation in some bands, scarcity, and lack of radio resources to new wireless applications. Most of the frequencies in the radio spectrum have been allocated although many studies have shown that the allocated bands are not being used efficiently. The CR technology is one of the effective solutions to the shortage of spectrum and the inefficiency of its utilization. In this thesis, a detailed investigation on issues related to the protocol design for cognitive radio networks with particular emphasis on the MAC layer is presented. A novel Dynamic and Decentralized and Hybrid MAC (DDH-MAC) protocol that lies between the CR MAC protocol families of globally available common control channel (GCCC) and local control channel (non-GCCC). First, a multi-access channel MAC protocol, which integrates the best features of both GCCC and non-GCCC, is proposed. Second, an enhancement to the protocol is proposed by enabling it to access more than one control channel at the same time. The cognitive users/secondary users (SUs) always have access to one control channel and they can identify and exploit the vacant channels by dynamically switching across the different control channels. Third, rapid and efficient exchange of CR control information has been proposed to reduce delays due to the opportunistic nature of CR. We have calculated the pre-transmission time for CR and investigate how this time can have a significant effect on nodes holding a delay sensitive data. Fourth, an analytical model, including a Markov chain model, has been proposed. This analytical model will rigorously analyse the performance of our proposed DDH-MAC protocol in terms of aggregate throughput, access delay, and spectrum opportunities in both the saturated and non-saturated networks. Fifth, we develop a simulation model for the DDH-MAC protocol using OPNET Modeler and investigate its performance for queuing delays, bit error rates, backoff slots and throughput. It could be observed from both the numerical and simulation results that when compared with existing CR MAC protocols our proposed MAC protocol can significantly improve the spectrum utilization efficiency of wireless networks. Finally, we optimize the performance of our proposed MAC protocol by incorporating multi-level security and making it energy efficient

Network performance & Quality of service in data networks involving spectrum utilization techniques

This research has developed technique to improve the quality of service in wireless data networks that employ spectrum utilization techniques based on Cognitive Radio. Most multiple dimension implementations focus on maximizing the Successful Communication Probability SCP in order to improve the wireless network utilization. However this usually has a negative impact on the Quality of Service, since increasing the SCP leads to increasing signal interference and Packet Loss, and thus network performance deterioration. The Multiple Dimension Cognitive Radio technique is a new technique, proposed in this thesis, that improves the Cognitive Radio Networks (CRN) efficiency by giving opportunity to secondary users (Unlicensed users) to use several dimension such as time, frequency, modulation, coding, and antenna directionality to increase their opportunity in finding spectrum hole. In order to draw a balance between improving the networking utilization and keeping the network performance at an acceptable level, this thesis proposes a new model of multiple dimension CR which provides a compromise between maximizing the SCP and network throughput from one side and keeping the QoS within the accepted thresholds from the other side. This is important so as to avoid network performance degradation which may result from the high user density in single wireless domain as a result of maximizing the SCP. In this research, a full Cognitive Radio model has been implemented in the OPNET simulator by developing modified nodes with the appropriate coding which include basic functionality. The Purpose of this model is to simulate the CR environment and study the network performance after applying the controlled multi dimension technique presented here. The proposed technique observes the channel throughput on TCP (Transmission Control Protocol) level, also QoS KPIs (Key Performance Index) like Packet Loss and Bit Error rate, during the operation of the CR multi dimension technique and alerts the system when the throughput degrades below a certain level. The proposed technique has interactive cautious nature which keeps monitoring the network performance and once find evident on network performance deterioration it takes corrective action, terminates low priority connections and releases over utilized channels, in order to keep the performance accepted

On Random Sampling for Compliance Monitoring in Opportunistic Spectrum Access Networks

In the expanding spectrum marketplace, there has been a long term evolution towards more market€“oriented mechanisms, such as Opportunistic Spectrum Access (OSA), enabled through Cognitive Radio (CR) technology. However, the potential of CR technologies to revolutionize wireless communications, also introduces challenges based upon the potentially non€“deterministic CR behaviour in the Electrospace. While establishing and enforcing compliance to spectrum etiquette rules are essential to realization of successful OSA networks in the future, there has only been recent increased research activity into enforcement. This dissertation presents novel work on the spectrum monitoring aspect, which is crucial to effective enforcement of OSA. An overview of the challenges faced by current compliance monitoring methods is first presented. A framework is then proposed for the use of random spectral sampling techniques to reduce data collection complexity in wideband sensing scenarios. This approach is recommended as an alternative to Compressed Sensing (CS) techniques for wideband spectral occupancy estimation, which may be difficult to utilize in many practical congested scenarios where compliance monitoring is required. Next, a low€“cost computational approach to online randomized temporal sensing deployment is presented for characterization of temporal spectrum occupancy in cognitive radio scenarios. The random sensing approach is demonstrated and its performance is compared to CS€“based approach for occupancy estimation. A novel frame€“based sampling inversion technique is then presented for cases when it is necessary to track the temporal behaviour of individual CRs or CR networks. Parameters from randomly sampled Physical Layer Convergence Protocol (PLCP) data frames are used to reconstruct occupancy statistics, taking account of missed frames due to sampling design, sensor limitations and frame errors. Finally, investigations into the use of distributed and mobile spectrum sensing to collect spatial diversity to improve the above techniques are presented, for several common monitoring tasks in spectrum enforcement. Specifically, focus is upon techniques for achieving consensus in dynamic topologies such as in mobile sensing scenarios

INSTANT MESSAGING SPAM DETECTION IN LONG TERM EVOLUTION NETWORKS

The lack of efficient spam detection modules for packet data communication is resulting to increased threat exposure for the telecommunication network users and the service providers. In this thesis, we propose a novel approach to classify spam at the server side by intercepting packet-data communication among instant messaging applications. Spam detection is performed using machine learning techniques on packet headers and contents (if unencrypted) in two different phases: offline training and online classification. The contribution of this study is threefold. First, it identifies the scope of deploying a spam detection module in a state-of-the-art telecommunication architecture. Secondly, it compares the usefulness of various existing machine learning algorithms in order to intercept and classify data packets in near real-time communication of the instant messengers. Finally, it evaluates the accuracy and classification time of spam detection using our approach in a simulated environment of continuous packet data communication. Our research results are mainly generated by executing instances of a peer-to-peer instant messaging application prototype within a simulated Long Term Evolution (LTE) telecommunication network environment. This prototype is modeled and executed using OPNET network modeling and simulation tools. The research produces considerable knowledge on addressing unsolicited packet monitoring in instant messaging and similar applications

Low power wide area network, cognitive radio and the internet of things : potentials for integration

The Internet of Things (IoT) is an emerging paradigm that enables many beneficial and prospective application areas, such as smart metering, smart homes, smart industries, and smart city architectures, to name but a few. These application areas typically comprise end nodes and gateways that are often interconnected by low power wide area network (LPWAN) technologies, which provide low power consumption rates to elongate the battery lifetimes of end nodes, low IoT device development/purchasing costs, long transmission range, and increased scalability, albeit at low data rates. However, most LPWAN technologies are often confronted with a number of physical (PHY) layer challenges, including increased interference, spectral inefficiency, and/or low data rates for which cognitive radio (CR), being a predominantly PHY layer solution, suffices as a potential solution. Consequently, in this article, we survey the potentials of integrating CR in LPWAN for IoT-based applications. First, we present and discuss a detailed list of different state-of-the-art LPWAN technologies; we summarize the most recent LPWAN standardization bodies, alliances, and consortia while emphasizing their disposition towards the integration of CR in LPWAN.We then highlight the concept of CR in LPWAN via a PHY-layer front-end model and discuss the benefits of CR-LPWAN for IoT applications. A number of research challenges and future directions are also presented. This article aims to provide a unique and holistic overview of CR in LPWAN with the intention of emphasizing its potential benefits.This work was supported by the Council for Scientific and Industrial Research, Pretoria, South Africa, through the Smart Networks collaboration initiative and Internet of Things (IoT)-Factory Program (funded by the Department of Science and Innovation (DSI), South Africa).http://www.mdpi.com/journal/sensorsam2021Electrical, Electronic and Computer Engineerin