Today,securing devices connected to the internet is challenging as security threats are generated through various sources.The protection of cyber-physical systems from external attacks is a primary task.The presented ...Today,securing devices connected to the internet is challenging as security threats are generated through various sources.The protection of cyber-physical systems from external attacks is a primary task.The presented method is planned on the prime motive of detecting cybersecurity attacks and their impacted parameters.The proposed architecture employs the LYSIS dataset and formulates Multi Variant Exploratory Data Analysis(MEDA)through Principle Component Analysis(PCA)and Singular Value Decompo-sition(SVD)for the extraction of unique parameters.The feature mappings are analyzed with Recurrent 2 Convolutional Neural Network(R2CNN)and Gradient Boost Regression(GBR)to identify the maximum correlation.Novel Late Fusion Aggregation enabled with Cyber-Net(LFAEC)is the robust derived algorithm.The quantitative analysis uses predicted threat points with actual threat variables from which mean and difference vectors areevaluated.The performance of the presented system is assessed against the parameters such as Accuracy,Precision,Recall,and F1 Score.The proposed method outperformed by 98% to 100% in all quality measures compared to existing methods.展开更多
针对二维旋转不变子空间算法(estimation of signal parameters via rotational invariance technigues,ESPRIT)在求解信号时协方差矩阵存在阵列冗余问题,提出一种改进后的二维ESPRIT算法。该算法利用阵列结构原理构造2个互相关矩阵,然...针对二维旋转不变子空间算法(estimation of signal parameters via rotational invariance technigues,ESPRIT)在求解信号时协方差矩阵存在阵列冗余问题,提出一种改进后的二维ESPRIT算法。该算法利用阵列结构原理构造2个互相关矩阵,然后由合并的特殊大矩阵进行奇异值分解来估计信号子空间,最后利用2D-ESPRIT方法实现二维测向。该算法估计精度高,计算量小,通过空间平滑后既能对相干信号进行估计,也能同时估计非相干信号。展开更多
文摘Today,securing devices connected to the internet is challenging as security threats are generated through various sources.The protection of cyber-physical systems from external attacks is a primary task.The presented method is planned on the prime motive of detecting cybersecurity attacks and their impacted parameters.The proposed architecture employs the LYSIS dataset and formulates Multi Variant Exploratory Data Analysis(MEDA)through Principle Component Analysis(PCA)and Singular Value Decompo-sition(SVD)for the extraction of unique parameters.The feature mappings are analyzed with Recurrent 2 Convolutional Neural Network(R2CNN)and Gradient Boost Regression(GBR)to identify the maximum correlation.Novel Late Fusion Aggregation enabled with Cyber-Net(LFAEC)is the robust derived algorithm.The quantitative analysis uses predicted threat points with actual threat variables from which mean and difference vectors areevaluated.The performance of the presented system is assessed against the parameters such as Accuracy,Precision,Recall,and F1 Score.The proposed method outperformed by 98% to 100% in all quality measures compared to existing methods.
文摘针对二维旋转不变子空间算法(estimation of signal parameters via rotational invariance technigues,ESPRIT)在求解信号时协方差矩阵存在阵列冗余问题,提出一种改进后的二维ESPRIT算法。该算法利用阵列结构原理构造2个互相关矩阵,然后由合并的特殊大矩阵进行奇异值分解来估计信号子空间,最后利用2D-ESPRIT方法实现二维测向。该算法估计精度高,计算量小,通过空间平滑后既能对相干信号进行估计,也能同时估计非相干信号。
