Kernelization algorithms for graph modification problems are important ingredients in parameterized computation theory. In this paper, we survey the kernelization algorithms for four types of graph modification proble...Kernelization algorithms for graph modification problems are important ingredients in parameterized computation theory. In this paper, we survey the kernelization algorithms for four types of graph modification problems, which include vertex deletion problems, edge editing problems, edge deletion problems, and edge completion problems. For each type of problem, we outline typical examples together with recent results, analyze the main techniques, and provide some suggestions for future research in this field.展开更多
无线光通信网络的隐蔽窃听攻击具有高度的隐蔽性和复杂性,其中包含的复杂数据模式和特征,加大了无线光通信网络隐蔽窃听攻击检测难度。故提出无线光通信网络隐蔽窃听攻击自适应检测研究。采用图信号处理方法全面监测无线光通信网络,捕...无线光通信网络的隐蔽窃听攻击具有高度的隐蔽性和复杂性,其中包含的复杂数据模式和特征,加大了无线光通信网络隐蔽窃听攻击检测难度。故提出无线光通信网络隐蔽窃听攻击自适应检测研究。采用图信号处理方法全面监测无线光通信网络,捕捉异常信号范围;利用人工智能技术识别隐蔽窃听攻击特征;建立基于混合核最小二乘支持向量机(hybridkernel least-squares support vector machine,HKLSSVM)的窃听攻击检测模型,通过引入混合核函数将数据映射到更高维的特征空间中,识别出的隐蔽窃听攻击特征,并通过鲸鱼提升算法选择最优的惩罚参数和内核参数,实现无线光通信网络隐蔽窃听攻击自适应检测。实验结果表明,所提方法能准确获取异常信号范围和异常信号,在保证计算稳定性的同时,提高攻击检测性能。展开更多
基金supported by the National Natural Science Foundation of China (Nos. 61070224, 61232001, and 61173051)the China Postdoctoral Science Foundation (No. 2012M521551)
文摘Kernelization algorithms for graph modification problems are important ingredients in parameterized computation theory. In this paper, we survey the kernelization algorithms for four types of graph modification problems, which include vertex deletion problems, edge editing problems, edge deletion problems, and edge completion problems. For each type of problem, we outline typical examples together with recent results, analyze the main techniques, and provide some suggestions for future research in this field.
文摘无线光通信网络的隐蔽窃听攻击具有高度的隐蔽性和复杂性,其中包含的复杂数据模式和特征,加大了无线光通信网络隐蔽窃听攻击检测难度。故提出无线光通信网络隐蔽窃听攻击自适应检测研究。采用图信号处理方法全面监测无线光通信网络,捕捉异常信号范围;利用人工智能技术识别隐蔽窃听攻击特征;建立基于混合核最小二乘支持向量机(hybridkernel least-squares support vector machine,HKLSSVM)的窃听攻击检测模型,通过引入混合核函数将数据映射到更高维的特征空间中,识别出的隐蔽窃听攻击特征,并通过鲸鱼提升算法选择最优的惩罚参数和内核参数,实现无线光通信网络隐蔽窃听攻击自适应检测。实验结果表明,所提方法能准确获取异常信号范围和异常信号,在保证计算稳定性的同时,提高攻击检测性能。
