Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm
In cognitive radio network (CRN), secondary users (SUs) try to sense and utilize the vacant spectrum of the legitimate primary user (PU) in an efficient manner. The process of cooperation among SUs makes the sensing more authentic with minimum disturbance to the PU in achieving maximum utilization o...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2018/2346317 |
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| author | Noor Gul Ijaz Mansoor Qureshi Atif Elahi Imtiaz Rasool |
| author_facet | Noor Gul Ijaz Mansoor Qureshi Atif Elahi Imtiaz Rasool |
| author_sort | Noor Gul |
| collection | DOAJ |
| description | In cognitive radio network (CRN), secondary users (SUs) try to sense and utilize the vacant spectrum of the legitimate primary user (PU) in an efficient manner. The process of cooperation among SUs makes the sensing more authentic with minimum disturbance to the PU in achieving maximum utilization of the vacant spectrum. One problem in cooperative spectrum sensing (CSS) is the occurrence of malicious users (MUs) sending false data to the fusion center (FC). In this paper, the FC takes a global decision based on the hard binary decisions received from all SUs. Genetic algorithm (GA) using one-to-many neighbor distance along with z-score as a fitness function is used for the identification of accurate sensing information in the presence of MUs. The proposed scheme is able to avoid the effect of MUs in CSS without identification of MUs. Four types of abnormal SUs, opposite malicious user (OMU), random opposite malicious user (ROMU), always yes malicious user (AYMU), and always no malicious user (ANMU), are discussed in this paper. Simulation results show that the proposed hard fusion scheme has surpassed the existing hard fusion scheme, equal gain combination (EGC), and maximum gain combination (MGC) schemes by employing GA. |
| format | Article |
| id | doaj-art-399b6d8d18624c9e952a31de3da4baf3 |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-399b6d8d18624c9e952a31de3da4baf32025-02-03T01:33:24ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772018-01-01201810.1155/2018/23463172346317Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic AlgorithmNoor Gul0Ijaz Mansoor Qureshi1Atif Elahi2Imtiaz Rasool3Department of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad 44000, PakistanDepartment of Electrical Engineering, Air University, Islamabad 44000, PakistanDepartment of Electrical Engineering, Faculty of Engineering and Technology, International Islamic University, Islamabad 44000, PakistanDepartment of Electronics, University of Peshawar, Peshawar 25000, PakistanIn cognitive radio network (CRN), secondary users (SUs) try to sense and utilize the vacant spectrum of the legitimate primary user (PU) in an efficient manner. The process of cooperation among SUs makes the sensing more authentic with minimum disturbance to the PU in achieving maximum utilization of the vacant spectrum. One problem in cooperative spectrum sensing (CSS) is the occurrence of malicious users (MUs) sending false data to the fusion center (FC). In this paper, the FC takes a global decision based on the hard binary decisions received from all SUs. Genetic algorithm (GA) using one-to-many neighbor distance along with z-score as a fitness function is used for the identification of accurate sensing information in the presence of MUs. The proposed scheme is able to avoid the effect of MUs in CSS without identification of MUs. Four types of abnormal SUs, opposite malicious user (OMU), random opposite malicious user (ROMU), always yes malicious user (AYMU), and always no malicious user (ANMU), are discussed in this paper. Simulation results show that the proposed hard fusion scheme has surpassed the existing hard fusion scheme, equal gain combination (EGC), and maximum gain combination (MGC) schemes by employing GA.http://dx.doi.org/10.1155/2018/2346317 |
| spellingShingle | Noor Gul Ijaz Mansoor Qureshi Atif Elahi Imtiaz Rasool Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm International Journal of Antennas and Propagation |
| title | Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm |
| title_full | Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm |
| title_fullStr | Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm |
| title_full_unstemmed | Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm |
| title_short | Defense against Malicious Users in Cooperative Spectrum Sensing Using Genetic Algorithm |
| title_sort | defense against malicious users in cooperative spectrum sensing using genetic algorithm |
| url | http://dx.doi.org/10.1155/2018/2346317 |
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