Defense Against Objective Function Attacks in Cognitive Radio Networks  被引量:7

Defense Against Objective Function Attacks in Cognitive Radio Networks

在线阅读下载全文

作  者:PEI Qingqi LI Hongning MA Jianfeng FAN Kefeng 

机构地区:[1]Ministry of Education Key Laboratory of Computer Network and Information Security Xidian University, Xi'an 710071, China [2]Institute of China Electronic System Engineering Corporation, Beijing 100039, China [3]China Electronics Standardization Institute, Beijing 100007, China

出  处:《Chinese Journal of Electronics》2011年第1期138-142,共5页电子学报(英文版)

基  金:This work is supported by the National Natural Science Foundation of China (No.60803150, No.60803151), the National High Technology Research and Development Program of China (No.2008AA01Z411), the Key Program of NSFC-Guangdong Union Foundation (No.U0835004), China Postdoctoral Science Foundation (No.20090451) and the Planned Science and Technology Project of Shannxi Province (No.2009K08-38).

摘  要:Cognitive radio (CR) is a technology for identifying opportunities using the "spectrum holes" for communication by cognition. Consequently, we can increase spectrum resource utilization rate with CR. However, it is cognition that causes an unprecedented challenge for cognitive radio networks, especially in security performance. Based on security problems existing in cognitive radios, we analyze Objective function attacks in detail. To counter this attack, we propose a multi-objective programming model, called MOP, which verifies all parameters tampered, so that attackers can not prevent CR from adapting to surroundings. Our simulation results indicate that the MOP model can defend Objective function attacks effectively. Thus, with the MOP model based on Particle swarm optimization (PSO), cognitive radio networks will obtain the optimum condition.

关 键 词:Cognitive radio Parameters attacks Objective function attacks Spectrum sensing Multi-objective programming. 

分 类 号:TN929.5[电子电信—通信与信息系统] TP309.2[电子电信—信息与通信工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象