Distributed denial-of-service(DDoS)attacks are designed to interrupt network services such as email servers and webpages in traditional computer networks.Furthermore,the enormous number of connected devices makes it d...Distributed denial-of-service(DDoS)attacks are designed to interrupt network services such as email servers and webpages in traditional computer networks.Furthermore,the enormous number of connected devices makes it difficult to operate such a network effectively.Software defined networks(SDN)are networks that are managed through a centralized control system,according to researchers.This controller is the brain of any SDN,composing the forwarding table of all data plane network switches.Despite the advantages of SDN controllers,DDoS attacks are easier to perpetrate than on traditional networks.Because the controller is a single point of failure,if it fails,the entire network will fail.This paper offers a Hybrid Deep Learning Intrusion Detection and Prevention(HDLIDP)framework,which blends signature-based and deep learning neural networks to detect and prevent intrusions.This framework improves detection accuracy while addressing all of the aforementioned problems.To validate the framework,experiments are done on both traditional and SDN datasets;the findings demonstrate a significant improvement in classification accuracy.展开更多
Future energy descent systems will be expected to be controlled by the using of renewable power sources of which wind energy is one of the favorable sources. This paper treats with the implantation of genetic algorith...Future energy descent systems will be expected to be controlled by the using of renewable power sources of which wind energy is one of the favorable sources. This paper treats with the implantation of genetic algorithms for making the parameters needed for PID applied to interconnected thermal and hydraulic power systems at best use and most effective. Two-areas of hydraulic and thermal power systems with wind connected parallel to each one are considered to exemplify the effective parameter investigation. First hydraulic and thermal are connected with tie line with the wind connected parallel to hydraulic or thermal, and then disturbance was made at thermal power plant, then to hydraulic power plant. Simulations are performed aided by the integrated Simulink/Matlab environment taking into consideration the genetic optimization process. Multiple integral representations variables with different cost functions were considered in the search for the effective AGC parameters. The outcomes established by this paper shows the impact of the genetic algorithms for LFC about multiple areas connected power systems based on different wind power using in the tuning of such a process.展开更多
文摘Distributed denial-of-service(DDoS)attacks are designed to interrupt network services such as email servers and webpages in traditional computer networks.Furthermore,the enormous number of connected devices makes it difficult to operate such a network effectively.Software defined networks(SDN)are networks that are managed through a centralized control system,according to researchers.This controller is the brain of any SDN,composing the forwarding table of all data plane network switches.Despite the advantages of SDN controllers,DDoS attacks are easier to perpetrate than on traditional networks.Because the controller is a single point of failure,if it fails,the entire network will fail.This paper offers a Hybrid Deep Learning Intrusion Detection and Prevention(HDLIDP)framework,which blends signature-based and deep learning neural networks to detect and prevent intrusions.This framework improves detection accuracy while addressing all of the aforementioned problems.To validate the framework,experiments are done on both traditional and SDN datasets;the findings demonstrate a significant improvement in classification accuracy.
文摘Future energy descent systems will be expected to be controlled by the using of renewable power sources of which wind energy is one of the favorable sources. This paper treats with the implantation of genetic algorithms for making the parameters needed for PID applied to interconnected thermal and hydraulic power systems at best use and most effective. Two-areas of hydraulic and thermal power systems with wind connected parallel to each one are considered to exemplify the effective parameter investigation. First hydraulic and thermal are connected with tie line with the wind connected parallel to hydraulic or thermal, and then disturbance was made at thermal power plant, then to hydraulic power plant. Simulations are performed aided by the integrated Simulink/Matlab environment taking into consideration the genetic optimization process. Multiple integral representations variables with different cost functions were considered in the search for the effective AGC parameters. The outcomes established by this paper shows the impact of the genetic algorithms for LFC about multiple areas connected power systems based on different wind power using in the tuning of such a process.
