The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
La détection du spectre est une technologie clé dans les systèmes de radio cognitive (CR). La détection coopérative du spectre à l'aide d'un modèle distribué offre une détection améliorée pour l'utilisateur principal, ce qui expose le système CR à une nouvelle menace de sécurité. Cette menace est la diminution des performances de détection coopérative en raison de la falsification des données de détection du spectre générée par des utilisateurs malveillants. Notre schéma proposé, basé sur des statistiques robustes, utilise uniquement les données de puissance reçue des nœuds de détection passés disponibles pour estimer les paramètres de distribution des hypothèses de présence et d'absence du signal primaire. Ces paramètres estimés sont utilisés pour réaliser la théorie de Dempster-Shafer sur la fusion des données de preuve qui entraîne l'élimination des utilisateurs malveillants. De plus, afin d'améliorer les performances, le poids de fiabilité d'un nœud est complété avec le schéma de fusion de données. Les résultats de simulation indiquent que le schéma proposé peut fournir une puissante capacité d'élimination des utilisateurs malveillants ainsi qu'un gain élevé de fusion de données dans divers cas de conditions de canal.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Nhan NGUYEN-THANH, Insoo KOO, "A Robust Secure Cooperative Spectrum Sensing Scheme Based on Evidence Theory and Robust Statistics in Cognitive Radio" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 12, pp. 3644-3652, December 2009, doi: 10.1587/transcom.E92.B.3644.
Abstract: Spectrum sensing is a key technology within Cognitive Radio (CR) systems. Cooperative spectrum sensing using a distributed model provides improved detection for the primary user, which opens the CR system to a new security threat. This threat is the decrease of the cooperative sensing performance due to the spectrum sensing data falsification which is generated from malicious users. Our proposed scheme, based on robust statistics, utilizes only available past sensing nodes' received power data for estimating the distribution parameters of the primary signal presence and absence hypotheses. These estimated parameters are used to perform the Dempster-Shafer theory of evidence data fusion which causes the elimination of malicious users. Furthermore, in order to enhance performance, a node's reliability weight is supplemented along with the data fusion scheme. Simulation results indicate that our proposed scheme can provide a powerful capability in eliminating malicious users as well as a high gain of data fusion under various cases of channel condition.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.3644/_p
Copier
@ARTICLE{e92-b_12_3644,
author={Nhan NGUYEN-THANH, Insoo KOO, },
journal={IEICE TRANSACTIONS on Communications},
title={A Robust Secure Cooperative Spectrum Sensing Scheme Based on Evidence Theory and Robust Statistics in Cognitive Radio},
year={2009},
volume={E92-B},
number={12},
pages={3644-3652},
abstract={Spectrum sensing is a key technology within Cognitive Radio (CR) systems. Cooperative spectrum sensing using a distributed model provides improved detection for the primary user, which opens the CR system to a new security threat. This threat is the decrease of the cooperative sensing performance due to the spectrum sensing data falsification which is generated from malicious users. Our proposed scheme, based on robust statistics, utilizes only available past sensing nodes' received power data for estimating the distribution parameters of the primary signal presence and absence hypotheses. These estimated parameters are used to perform the Dempster-Shafer theory of evidence data fusion which causes the elimination of malicious users. Furthermore, in order to enhance performance, a node's reliability weight is supplemented along with the data fusion scheme. Simulation results indicate that our proposed scheme can provide a powerful capability in eliminating malicious users as well as a high gain of data fusion under various cases of channel condition.},
keywords={},
doi={10.1587/transcom.E92.B.3644},
ISSN={1745-1345},
month={December},}
Copier
TY - JOUR
TI - A Robust Secure Cooperative Spectrum Sensing Scheme Based on Evidence Theory and Robust Statistics in Cognitive Radio
T2 - IEICE TRANSACTIONS on Communications
SP - 3644
EP - 3652
AU - Nhan NGUYEN-THANH
AU - Insoo KOO
PY - 2009
DO - 10.1587/transcom.E92.B.3644
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2009
AB - Spectrum sensing is a key technology within Cognitive Radio (CR) systems. Cooperative spectrum sensing using a distributed model provides improved detection for the primary user, which opens the CR system to a new security threat. This threat is the decrease of the cooperative sensing performance due to the spectrum sensing data falsification which is generated from malicious users. Our proposed scheme, based on robust statistics, utilizes only available past sensing nodes' received power data for estimating the distribution parameters of the primary signal presence and absence hypotheses. These estimated parameters are used to perform the Dempster-Shafer theory of evidence data fusion which causes the elimination of malicious users. Furthermore, in order to enhance performance, a node's reliability weight is supplemented along with the data fusion scheme. Simulation results indicate that our proposed scheme can provide a powerful capability in eliminating malicious users as well as a high gain of data fusion under various cases of channel condition.
ER -