A Jamming Attacks Detection Approach Based on CNN based Quantum Leap Method for Wireless Sensor Network

The wireless sensor network is the most significant largest communication device. WSN has been interfacing with various wireless applications. Because the wireless application needs faster communication and less interruption, the main problem of jamming attacks on wireless networks is that jamming attack detection using various machine learning methods has been used. The reasons for jamming detection may be user behaviour-based and network traffic and energy consumption. The previous machine learning system could not present the jamming attack detection accuracy because the feature selection model of Chi-Squared didn’t perform well for jamming attack detections which determined takes a large dataset to be classified to find the high accuracy for jamming attack detection. To resolve this problem, propose a CNN-based quantum leap method that detects high accuracy for jamming attack detections the WSN-DS dataset collected by the Kaggle repository. Pre-processing using the Z-score Normalization technique will be applied, performing data deviations and assessments from the dataset, and collecting data and checking or evaluating data. Fisher’s Score is used to select the optimal feature of a jamming attack. Finally, the proposed CNN-based quantum leap is used to classify the jamming attacks. The CNN-based quantum leap simulation shows the output for jamming attacks with high precision, high detection, and low false alarm detection

Efficient Advanced Encryption Standard for Securing Cognitive Radio Networks

During the last decade, the CR (Cognitive Radio) came into view as a major wireless technology to resolve the issue of spectrum secrecy and efficient spectrum utilization. However, due to unlicensed (secondary) users, there are various security threats to the CRN (Cognitive Radio Networks). Some malicious users may access the CRN and mislead the secondary users to vacate the occupied channel, which may stop the communication. In this work, we propose a new cryptographic-based algorithm, CRAES (Cognitive Radio-Advanced Encryption Standard), inspired by the traditional AES to secure the CRN. The data of the primary and secondary users is encrypted at the transmitter and decrypted at the receiver. Unlike the conventional AES, we introduce the data-dependent key-generation and shift-rows process. We also reduce the rounds of AES from 10-6 to improve the computational efficiency without compromising the overall security. The experimental results demonstrate the effectiveness of the proposed CR-AES in terms of better security, reliability, and computational efficiency

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

A Robust Cooperative Spectrum Sensing-Assisted Multiuser Resource Allocation Scheme

Cognitive radio (CR), which is proposed as a solution for spectrum scarcity, imposes some threats to the network. One severe attack to cognitive radio network is the primary user emulation attack (PUEA), in which an attacker may transmit its signal with high power or mimic specific features of the primary user's signal to prevent secondary users from accessing the licensed spectrum. In this paper, we study a subcarrier and power allocation problem for orthogonal frequency division multiple access-(OFDMA-) based CR systems in the presence of PUEA. To maximize the system throughput while keeping the interference introduced to the primary user (PU) below given thresholds with a certain probability, a joint design of a robust cooperative spectrum sensing and a resource allocation scheme is proposed. In the proposed scheme, the inaccurate classification of PU signals and PUEA signals provided by robust cooperative spectrum sensing is utilized by resource scheduling module. To further exploit the underutilized spectrum bands, we also evaluate the performance of the proposed scheme in the hybrid overlay/underlay spectrum access mechanism. Numerical results demonstrate the effectiveness of the proposed scheme compared to conventional scheme regardless of the number of SUs or the kind of spectrum access mechanism being used

Primary user emulation attack mitigation in cognitive radio networks.

M. Sc. Eng. University of KwaZulu-Natal, Durban 2014.The rapid progress in the number of users and applications in wireless communication have led to the problem of growing spectrum scarcity in recent years. This imminent spectrum scarcity problem is in part due to a rapidly increasing demand for wireless services and in part due to the inefficient usage of currently licensed spectrum bands. Cognitive radio (CR) is a new technology that is proposed to improve spectrum efficiency by allowing unlicensed secondary users to access the licensed frequency bands without interfering with the licensed primary users. A malicious secondary user can decide to exploit this spectrum access etiquette by mimicking the spectral characteristics of a primary user, and gain priority access to a wireless channel over other secondary users. This scenario is referred to in literature as Primary User Emulation Attack (PUEA). Though quite a lot of research efforts have been focused on the detection and defense strategy of PUEA in cognitive radio networks, less attention have been given to combating and mitigating PUEA in a cooperative spectrum sensing environment. This dissertation seeks to contribute to research in the field of cognitive radio networks through an investigation into the impacts of Primary User Emulation Attacks (PUEA) on cognitive radio networks, the problem of trust amongst users in the networks and also mitigating the activities of PUEA in the network. An analytical and system model for PUEA in cognitive radio networks is presented and its impacts are also studied using Neyman-Pearson Composite Hypothesis Test. The intention is to evict malicious users from the network and maximize spectrum utilization efficiency. To achieve this, techniques to verify that the source of spectrum occupancy information is from a genuine user are proposed. In a primary user emulation attack, malicious users tend to destruct the spectrum sensing process of a cognitive radio network by imitating the primary signal and deceive other secondary users from accessing vacant frequency bands. An energy detection cooperative spectrum sensing technique is proposed to mitigate this attack. This technique assists in the reduction of errors made by secondary users in detecting primary user signals in frequency bands considering the existence of PUEA in the network. The performance of our proposed method is compared to an existing energy detection spectrum sensing method that does not consider the existence of PUEA in the network. Simulated results show that the proposed method can effectively mitigate PUEA in a cognitive radio network

Um esquema para análise multicritério e cooperativa da presença de ataques EUP em redes ad hoc de rádio cognitivo

Resumo: O uso ineficiente do espectro de radiofrequências e a alta proliferação de dispositivos móveis motivaram o desenvolvimento da tecnologia de rádio cognitivo (RC). Esta permite um melhor aproveitamento do espectro de radiofrequências e tem promovido o surgimento das redes ad hoc de rádio cognitivo (CRAHNs, do inglês, Cognitive Radio Ad Hoc Networks). Nestas redes dois tipos de usuários compartilham o espectro: o usuário primário (UP) e o usuário secundário (US). O usuário primário possui licença para usar as bandas de frequência e tem prioridade para acessá-las; enquanto os usuários secundários não possuem licenças, mas utilizam estas bandas quando elas estiverem ociosas. Apesar das vantagens da tecnologia RC, o aproveitamento das frequências ociosas pode ser altamente comprometido por ataques de Emulação de Usuário Primário (EUP). Um ataque EUP é gerado por um usuário secundário, malicioso ou egoísta, que emula o comportamento e as características dos usuários primários legítimos a fim de ganhar prioridade no uso do espectro de radiofrequências. Os esquemas propostos na literatura para a análise, detecção ou mitigação dos ataques EUPs seguem arquiteturas de redes centralizadas ou distribuídas, além de exibir abordagens cooperativas ou não-cooperativas. Porém, esses esquemas realizam uma análise considerando um único critério para avaliar a presença de ataques na rede, resultando em altas taxas de falsos positivos. A fim de prover uma análise mais sofisticada e eficiente, este trabalho propõe IMCA, um esquema para análise Multicritério e Cooperativa da presença de Ataques EUP em redes ad hoc de rádio cognitivo. Este esquema segue uma abordagem descentralizada e cooperativa em que cada US realiza duas fases para determinar a probabilidade da presença de ataque EUP. A primeira fase consiste no sensoreamento e na análise dos valores de múltiplos critérios; e a segunda fase consiste na troca de informações entre vizinhos, seguida da análise das informações trocadas através do teorema de Bayes. O esquema IMCA foi implementado no simulador de rede, Network Simulator (NS), versão 2.31 e avaliado. Os resultados mostram que o esquema apresenta uma superioridade de até 25% comparado com um esquema monocritério não-cooperativo, quando executada apenas a primeira fase, e uma eficácia de até 77% na determinação da probabilidade da presença de ataques EUP, quando aplicadas as duas fases do esquema

Performance Analysis of Secondary Users in Cognitive Radio Networks

Cognitive radio technology is to improve the inefficient usage of limited spectrum resources when wireless networks coexist. Using this technology, the unlicensed users (secondary users) can opportunistically access the frequency band of licensed users (primary users). There are different kinds of cognitive radio networks. This thesis focuses on the interweave cognitive radio network, where the secondary users are only allowed to access the spectrum holes, i.e., the idle parts of the licensed spectrum band. The main task is to analyze the opportunistic dynamic spectrum allocation method based on selecting the largest available spectrum hole, where the goal is to have the maximum possible transmission rate for secondary users. The objective of this work is to give the service provider an estimation about the load of secondary users in different numbers of channels and various kinds of traffics in primary networks. The work starts with the investigation on the spectrum allocation for secondary users in a network of single-channel primary users. In our analysis, we propose a theoretical model to calculate the probability distribution of the length of the largest available spectrum hole. The contribution of this part is the modeling and performance analysis of the existing conventional method, which selects the largest available spectrum hole. The main contribution is the calculation of the conditional probability of having maximum consecutive idle channels under the condition of a given number of total channels and various number of busy channels. For any given number of channels, this conditional probability gives us the number of consecutive idle channels the secondary user can have, if we know the probability distribution of busy channels taken by primary users. The theoretical model works for any given number of total channels in the licensed frequency band, with numerical and simulation results confirming the precision of the proposed model. Later, we continue our study on the spectrum allocation in a cognitive radio network of multichannel primary users, where the secondary user temporarily takes the largest available spectrum hole. For the performance analysis, we basically need to solve two problems. First, we need to find the probability distribution of busy channels taken by primary users. Second, we need to determine the length of the largest available spectrum hole under the condition of primary users taking different channels. In the case of primary users taking multiple channels, the calculation of the conditional probability of having maximum consecutive idle channels under the condition of a given number of total channels and various number of busy channels, is approximately valid, especially in low-traffic networks. As such, the main contribution in this part is finding the probability distribution of busy channels taken by primary users. The solution scenario is based on a multidimensional Markov chain, with numerical and simulation results verifying the accuracy of the proposed model. Finally, an approximate one-dimensional Markov chain is also proposed to simplify the complicated multidimensional solution. We provide an approximate estimation for the load of the secondary user to avoid the calculation of the complex multidimensional Markov chain. The procedure significantly decreases the complexity, although we lose some information. The main concern in the one-dimensional approximation is to find the departure rates from each state of busy channels. It is actually the main challenge of this part and by approximation we provide the solution. At the end, the performance of the proposed model was validated by numerical and simulation results

ESQUEMA FLEXIBLE DE MÚLTIPLES CRITERIOS PARA DETECTAR ATAQUES DE EMULACIÓN DE USUARIO PRIMARIO EN REDES AD HOC DE RADIO COGNITIVO

LA TECNOLOGÍA DE RADIO COGNITIVO REDES DE RADIO COGNITIVO VULNERABILIDADES DE SEGURIDAD ATAQUE DE EMULACIÓN DE USUARIO PRIMARIO TÉCNICAS DE SENSORIAMENTO DEL ESPECTRO TÉCNICAS DE SENSORIAMENTO DEL ESPECTRO NO-COOPERATIVAS TÉCNICAS COOPERATIVAS DE SENSORIAMENTO DEL ESPECTRO TÉCNICAS DE ANÁLISIS DE MÚLTIPLES CRITERIOS Y ANÁLISIS CONDICIONAL ANÁLISIS DE MÚLTIPLES CRITERIOS TEOREMA DE BAYES RESUMEN ANÁLISIS DE TRABAJOS RELACIONADOS DETECCION Y MITIGACIÓN DE ATAQUES DE EMULACIÓN DE USUARIO PRIMARIO ANÁLISIS DE LOS TRABAJOS RELACIONADOS RESUMEN ESQUEMA FLEXEUP VISIÓN GENERAL DEL ESQUEMA FLEXEUP FASE INDIVIDUAL FASE DE COOPERACIÓN RESUMEN ANÁLISIS Y RESULTADOS ESCENARIOS DE SIMULACION MÉTRICAS RESULTADOS DEL DESEMPEÑO DEL ESQUEMA FLEXEUP RESUMEN CONCLUSIONES ?NALES RECOMENDACIONES Y TRABAJOS FUTURO