In recent years,the rapid advancement of emerging technologies such as big data,blockchain,and artificial intelligence has accelerated the transformation of currencies,shifting from materialization towards digitizatio...In recent years,the rapid advancement of emerging technologies such as big data,blockchain,and artificial intelligence has accelerated the transformation of currencies,shifting from materialization towards digitization and electronization.The e-CNY stands out as a prime example of China’s pioneering digital financial innovation globally.Governed by the central bank,it embodies the national agenda.As the e-CNY’s application field and reach expand,its relationship with the financial market grows increasingly intimate.As a significant participant in China’s financial landscape and a proactive responder to national policies,the securities industry is profoundly influenced by the e-CNY across various domains.Therefore,this paper undertakes a theoretical analysis of the e-CNY’s implementation within securities institutions,concluding that it will usher in a new paradigm for the entire financial system.展开更多
Education acts as an important part of economic growth and improvement in human welfare.The educational sectors have transformed a lot in recent days,and Information and Communication Technology(ICT)is an effective pa...Education acts as an important part of economic growth and improvement in human welfare.The educational sectors have transformed a lot in recent days,and Information and Communication Technology(ICT)is an effective part of the education field.Almost every action in university and college,right from the process fromcounselling to admissions and fee deposits has been automated.Attendance records,quiz,evaluation,mark,and grade submissions involved the utilization of the ICT.Therefore,security is essential to accomplish cybersecurity in higher security institutions(HEIs).In this view,this study develops an Automated Outlier Detection for CyberSecurity in Higher Education Institutions(AOD-CSHEI)technique.The AOD-CSHEI technique intends to determine the presence of intrusions or attacks in the HEIs.The AOD-CSHEI technique initially performs data pre-processing in two stages namely data conversion and class labelling.In addition,the Adaptive Synthetic(ADASYN)technique is exploited for the removal of outliers in the data.Besides,the sparrow search algorithm(SSA)with deep neural network(DNN)model is used for the classification of data into the existence or absence of intrusions in the HEIs network.Finally,the SSA is utilized to effectually adjust the hyper parameters of the DNN approach.In order to showcase the enhanced performance of the AOD-CSHEI technique,a set of simulations take place on three benchmark datasets and the results reported the enhanced efficiency of the AOD-CSHEI technique over its compared methods with higher accuracy of 0.9997.展开更多
文摘In recent years,the rapid advancement of emerging technologies such as big data,blockchain,and artificial intelligence has accelerated the transformation of currencies,shifting from materialization towards digitization and electronization.The e-CNY stands out as a prime example of China’s pioneering digital financial innovation globally.Governed by the central bank,it embodies the national agenda.As the e-CNY’s application field and reach expand,its relationship with the financial market grows increasingly intimate.As a significant participant in China’s financial landscape and a proactive responder to national policies,the securities industry is profoundly influenced by the e-CNY across various domains.Therefore,this paper undertakes a theoretical analysis of the e-CNY’s implementation within securities institutions,concluding that it will usher in a new paradigm for the entire financial system.
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number(IFPRC-154-611-2020)and King Abdulaziz University,DSR,Jeddah,Saudi Arabia.
文摘Education acts as an important part of economic growth and improvement in human welfare.The educational sectors have transformed a lot in recent days,and Information and Communication Technology(ICT)is an effective part of the education field.Almost every action in university and college,right from the process fromcounselling to admissions and fee deposits has been automated.Attendance records,quiz,evaluation,mark,and grade submissions involved the utilization of the ICT.Therefore,security is essential to accomplish cybersecurity in higher security institutions(HEIs).In this view,this study develops an Automated Outlier Detection for CyberSecurity in Higher Education Institutions(AOD-CSHEI)technique.The AOD-CSHEI technique intends to determine the presence of intrusions or attacks in the HEIs.The AOD-CSHEI technique initially performs data pre-processing in two stages namely data conversion and class labelling.In addition,the Adaptive Synthetic(ADASYN)technique is exploited for the removal of outliers in the data.Besides,the sparrow search algorithm(SSA)with deep neural network(DNN)model is used for the classification of data into the existence or absence of intrusions in the HEIs network.Finally,the SSA is utilized to effectually adjust the hyper parameters of the DNN approach.In order to showcase the enhanced performance of the AOD-CSHEI technique,a set of simulations take place on three benchmark datasets and the results reported the enhanced efficiency of the AOD-CSHEI technique over its compared methods with higher accuracy of 0.9997.
