With the advancement of internet,there is also a rise in cybercrimes and digital attacks.DDoS(Distributed Denial of Service)attack is the most dominant weapon to breach the vulnerabilities of internet and pose a signi...With the advancement of internet,there is also a rise in cybercrimes and digital attacks.DDoS(Distributed Denial of Service)attack is the most dominant weapon to breach the vulnerabilities of internet and pose a significant threat in the digital environment.These cyber-attacks are generated deliberately and consciously by the hacker to overwhelm the target with heavy traffic that genuine users are unable to use the target resources.As a result,targeted services are inaccessible by the legitimate user.To prevent these attacks,researchers are making use of advanced Machine Learning classifiers which can accurately detect the DDoS attacks.However,the challenge in using these techniques is the limitations on capacity for the volume of data and the required processing time.In this research work,we propose the framework of reducing the dimensions of the data by selecting the most important features which contribute to the predictive accuracy.We show that the‘lite’model trained on reduced dataset not only saves the computational power,but also improves the predictive performance.We show that dimensionality reduction can improve both effectiveness(recall)and efficiency(precision)of the model as compared to the model trained on‘full’dataset.展开更多
In the relentless quest for digital sovereignty, organizations face an unprecedented challenge in safeguarding sensitive information, protecting against cyber threats, and maintaining regulatory compliance. This manus...In the relentless quest for digital sovereignty, organizations face an unprecedented challenge in safeguarding sensitive information, protecting against cyber threats, and maintaining regulatory compliance. This manuscript unveils a revolutionary blueprint for cyber resilience, empowering organizations to transcend the limitations of traditional cybersecurity paradigms and forge ahead into uncharted territories of data security excellence and frictionless secrets management experience. Enter a new era of cybersecurity innovation and continued excellence. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the secrets lifecycle management with other platform cohesive integrations. Enterprises can enhance security, streamline operations, fasten development practices, avoid secrets sprawl, and improve overall compliance and DevSecOps practice. This enables the enterprises to enhance security, streamline operations, fasten development & deployment practices, avoid secrets spawls, and improve overall volume in shipping software with paved-road DevSecOps Practices, and improve developers’ productivity. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the application secrets lifecycle with other platform cohesive integrations. Organizations can enhance security, streamline operations, fasten development & deployment practices, avoid secrets sprawl, and improve overall volume in shipping software with paved-road DevSecOps practices. Most importantly, increases developer productivity.展开更多
针对注塑机结构设计工作中对数据管理系统的需求,从优化数据管理,实现协同设计和提高设计效率的目的出发,研究了注塑机结构设计部门级产品数据库管理(Product Data Management,PDM)系统实施和综合应用。从整体上缩短了注塑机产品的开发...针对注塑机结构设计工作中对数据管理系统的需求,从优化数据管理,实现协同设计和提高设计效率的目的出发,研究了注塑机结构设计部门级产品数据库管理(Product Data Management,PDM)系统实施和综合应用。从整体上缩短了注塑机产品的开发周期。展开更多
In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repe...In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.展开更多
Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major...Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major topics of concern include“SI”(security intelligence),“D-DA”(data-driven analytics),“PE”(proven expertise),and“R-TD”(real-time defense)capabilities.“DRBTs”(dynamic response behavior types)include“incident response”,“endpoint management”,“threat intelligence”,“network security”,and“fraud protection”.The consumer demand for electricity as essential public access and service is indexed to population growth estimates.Consumer-driven economies continue to add electrical consumption to their grids even though improvements in lower-power consumption and higher design efficiencies are present in new electric-powered products.Dependence on the production of electrical energy has no peer replacement technology and creates a societal vulnerability to targeted public electrical grid interruptions.When access to,or production of,electrical power is interrupted,the result is a“Mass Effect”every consumer feels with equal distribution.Electric grid security falls directly into the levels of authorized,and unauthorized,access via the“IoT”(Internet of Things)concepts,and the“IoM2M”(Internet of Machine-to-Machine)integration.Electrical grid operations that include production and network management augment each other in order to support the demand for electricity every day either in peak or off-peak,thus cybersecurity plays a big role in the protection of such assets at our disposal.With help from AI(artificial intelligence)integrated into the IoT a resilient system can be built to protect the electric grid system nationwide and will be able to detect and preempt Smart Malware attacks.展开更多
基金supported by the Researchers Supporting Project(No.RSP-2021/395),King Saud University,Riyadh,Saudi Arabia.
文摘With the advancement of internet,there is also a rise in cybercrimes and digital attacks.DDoS(Distributed Denial of Service)attack is the most dominant weapon to breach the vulnerabilities of internet and pose a significant threat in the digital environment.These cyber-attacks are generated deliberately and consciously by the hacker to overwhelm the target with heavy traffic that genuine users are unable to use the target resources.As a result,targeted services are inaccessible by the legitimate user.To prevent these attacks,researchers are making use of advanced Machine Learning classifiers which can accurately detect the DDoS attacks.However,the challenge in using these techniques is the limitations on capacity for the volume of data and the required processing time.In this research work,we propose the framework of reducing the dimensions of the data by selecting the most important features which contribute to the predictive accuracy.We show that the‘lite’model trained on reduced dataset not only saves the computational power,but also improves the predictive performance.We show that dimensionality reduction can improve both effectiveness(recall)and efficiency(precision)of the model as compared to the model trained on‘full’dataset.
文摘In the relentless quest for digital sovereignty, organizations face an unprecedented challenge in safeguarding sensitive information, protecting against cyber threats, and maintaining regulatory compliance. This manuscript unveils a revolutionary blueprint for cyber resilience, empowering organizations to transcend the limitations of traditional cybersecurity paradigms and forge ahead into uncharted territories of data security excellence and frictionless secrets management experience. Enter a new era of cybersecurity innovation and continued excellence. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the secrets lifecycle management with other platform cohesive integrations. Enterprises can enhance security, streamline operations, fasten development practices, avoid secrets sprawl, and improve overall compliance and DevSecOps practice. This enables the enterprises to enhance security, streamline operations, fasten development & deployment practices, avoid secrets spawls, and improve overall volume in shipping software with paved-road DevSecOps Practices, and improve developers’ productivity. By seamlessly integrating secrets based on logical environments and applications (assets), dynamic secrets management orchestrates and automates the application secrets lifecycle with other platform cohesive integrations. Organizations can enhance security, streamline operations, fasten development & deployment practices, avoid secrets sprawl, and improve overall volume in shipping software with paved-road DevSecOps practices. Most importantly, increases developer productivity.
文摘In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.
文摘Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major topics of concern include“SI”(security intelligence),“D-DA”(data-driven analytics),“PE”(proven expertise),and“R-TD”(real-time defense)capabilities.“DRBTs”(dynamic response behavior types)include“incident response”,“endpoint management”,“threat intelligence”,“network security”,and“fraud protection”.The consumer demand for electricity as essential public access and service is indexed to population growth estimates.Consumer-driven economies continue to add electrical consumption to their grids even though improvements in lower-power consumption and higher design efficiencies are present in new electric-powered products.Dependence on the production of electrical energy has no peer replacement technology and creates a societal vulnerability to targeted public electrical grid interruptions.When access to,or production of,electrical power is interrupted,the result is a“Mass Effect”every consumer feels with equal distribution.Electric grid security falls directly into the levels of authorized,and unauthorized,access via the“IoT”(Internet of Things)concepts,and the“IoM2M”(Internet of Machine-to-Machine)integration.Electrical grid operations that include production and network management augment each other in order to support the demand for electricity every day either in peak or off-peak,thus cybersecurity plays a big role in the protection of such assets at our disposal.With help from AI(artificial intelligence)integrated into the IoT a resilient system can be built to protect the electric grid system nationwide and will be able to detect and preempt Smart Malware attacks.
