With the recent increase in network attacks by threats,malware,and other sources,machine learning techniques have gained special attention for intrusion detection due to their ability to classify hundreds of features ...With the recent increase in network attacks by threats,malware,and other sources,machine learning techniques have gained special attention for intrusion detection due to their ability to classify hundreds of features into normal system behavior or an attack attempt.However,feature selection is a vital preprocessing stage in machine learning approaches.This paper presents a novel feature selection-based approach,Remora Optimization Algorithm-Levy Flight(ROA-LF),to improve intrusion detection by boosting the ROA performance with LF.The developed ROA-LF is assessed using several evaluation measures on five publicly available datasets for intrusion detection:Knowledge discovery and data mining tools competition,network security laboratory knowledge discovery and data mining,intrusion detection evaluation dataset,block out traffic network,Canadian institute of cybersecu-rity and three engineering problems:Cantilever beam design,three-bar truss design,and pressure vessel design.A comparative analysis between developed ROA-LF,particle swarm optimization,salp swarm algorithm,snake opti-mizer,and the original ROA methods is also presented.The results show that the developed ROA-LF is more efficient and superior to other feature selection methods and the three tested engineering problems for intrusion detection.展开更多
We first introduce a new approach for optimising a cascaded spline adaptive filter(CSAF)to identify unknown nonlinear systems by using a meta-heuristic optimisation algorithm(MOA).The CSAF architecture combines Hammer...We first introduce a new approach for optimising a cascaded spline adaptive filter(CSAF)to identify unknown nonlinear systems by using a meta-heuristic optimisation algorithm(MOA).The CSAF architecture combines Hammerstein and Wiener systems,where the nonlinear blocks are implemented with the spline network.The algorithms used optimise the weights of the spline interpolation function and linear filter by using an adequately weighted cost function,leading to improved filter stability,steady state performance,and guaranteed convergence to globally optimal solutions.We investigate two CSAF architectures:Hammerstein–Wiener SAF(HW-SAF)and Wiener–Hammerstein SAF(WH-SAF)structures.These architectures have been designed using gradient-based approaches which are inefficient due to poor convergence speed,and produce suboptimal solutions in a Gaussian noise environment.To avert these difficulties,we estimate the design parameters of the CSAF architecture using four independent MOAs:differential evolution(DE),brainstorm optimisation(BSO),multi-verse optimiser(MVO),and a recently proposed remora optimisation algorithm(ROA).In ROA,the remora factor’s control parameters produce near-global optimal parameters with a higher convergence speed.ROA also ensures the most balanced exploration and exploitation phases compared to DE-,BSO-,and MVO-based design approaches.Finally,the identification results of three numerical and industryspecific benchmark systems,including coupled electric drives,a thermic wall,and a continuous stirred tank reactor,are presented to emphasise the effectiveness of the ROA-based CSAF design.展开更多
文摘With the recent increase in network attacks by threats,malware,and other sources,machine learning techniques have gained special attention for intrusion detection due to their ability to classify hundreds of features into normal system behavior or an attack attempt.However,feature selection is a vital preprocessing stage in machine learning approaches.This paper presents a novel feature selection-based approach,Remora Optimization Algorithm-Levy Flight(ROA-LF),to improve intrusion detection by boosting the ROA performance with LF.The developed ROA-LF is assessed using several evaluation measures on five publicly available datasets for intrusion detection:Knowledge discovery and data mining tools competition,network security laboratory knowledge discovery and data mining,intrusion detection evaluation dataset,block out traffic network,Canadian institute of cybersecu-rity and three engineering problems:Cantilever beam design,three-bar truss design,and pressure vessel design.A comparative analysis between developed ROA-LF,particle swarm optimization,salp swarm algorithm,snake opti-mizer,and the original ROA methods is also presented.The results show that the developed ROA-LF is more efficient and superior to other feature selection methods and the three tested engineering problems for intrusion detection.
文摘We first introduce a new approach for optimising a cascaded spline adaptive filter(CSAF)to identify unknown nonlinear systems by using a meta-heuristic optimisation algorithm(MOA).The CSAF architecture combines Hammerstein and Wiener systems,where the nonlinear blocks are implemented with the spline network.The algorithms used optimise the weights of the spline interpolation function and linear filter by using an adequately weighted cost function,leading to improved filter stability,steady state performance,and guaranteed convergence to globally optimal solutions.We investigate two CSAF architectures:Hammerstein–Wiener SAF(HW-SAF)and Wiener–Hammerstein SAF(WH-SAF)structures.These architectures have been designed using gradient-based approaches which are inefficient due to poor convergence speed,and produce suboptimal solutions in a Gaussian noise environment.To avert these difficulties,we estimate the design parameters of the CSAF architecture using four independent MOAs:differential evolution(DE),brainstorm optimisation(BSO),multi-verse optimiser(MVO),and a recently proposed remora optimisation algorithm(ROA).In ROA,the remora factor’s control parameters produce near-global optimal parameters with a higher convergence speed.ROA also ensures the most balanced exploration and exploitation phases compared to DE-,BSO-,and MVO-based design approaches.Finally,the identification results of three numerical and industryspecific benchmark systems,including coupled electric drives,a thermic wall,and a continuous stirred tank reactor,are presented to emphasise the effectiveness of the ROA-based CSAF design.
