Non-traditional security issues have arisen since the 1960s,especially after the end of the Cold War,and are becoming a major issue in world security and politics.This reflects tremendous changes in the world situatio...Non-traditional security issues have arisen since the 1960s,especially after the end of the Cold War,and are becoming a major issue in world security and politics.This reflects tremendous changes in the world situation.With diverse causes and plural referent objects,non-traditional security issues cover nearly all the problems in the world today and make development difficult to sustain.This raises the question of whether human society and the earth can survive.Power politics one-sidedly stresses the role of power,endangering the harmonious development of nations and the whole of human society.It is not at all conducive to the solution of non-traditional security issues.The solution of non-traditional security issues demands cooperation from all actors in the international community.Multiple means are needed to solve these issues.Equal dialogue between all the actors,which can easily be attained,will play an effective role,as long as all actors respect each other's differences.展开更多
The rapid digitalization of urban infrastructure has made smart cities increasingly vulnerable to sophisticated cyber threats.In the evolving landscape of cybersecurity,the efficacy of Intrusion Detection Systems(IDS)...The rapid digitalization of urban infrastructure has made smart cities increasingly vulnerable to sophisticated cyber threats.In the evolving landscape of cybersecurity,the efficacy of Intrusion Detection Systems(IDS)is increasingly measured by technical performance,operational usability,and adaptability.This study introduces and rigorously evaluates a Human-Computer Interaction(HCI)-Integrated IDS with the utilization of Convolutional Neural Network(CNN),CNN-Long Short Term Memory(LSTM),and Random Forest(RF)against both a Baseline Machine Learning(ML)and a Traditional IDS model,through an extensive experimental framework encompassing many performance metrics,including detection latency,accuracy,alert prioritization,classification errors,system throughput,usability,ROC-AUC,precision-recall,confusion matrix analysis,and statistical accuracy measures.Our findings consistently demonstrate the superiority of the HCI-Integrated approach utilizing three major datasets(CICIDS 2017,KDD Cup 1999,and UNSW-NB15).Experimental results indicate that the HCI-Integrated model outperforms its counterparts,achieving an AUC-ROC of 0.99,a precision of 0.93,and a recall of 0.96,while maintaining the lowest false positive rate(0.03)and the fastest detection time(~1.5 s).These findings validate the efficacy of incorporating HCI to enhance anomaly detection capabilities,improve responsiveness,and reduce alert fatigue in critical smart city applications.It achieves markedly lower detection times,higher accuracy across all threat categories,reduced false positive and false negative rates,and enhanced system throughput under concurrent load conditions.The HCIIntegrated IDS excels in alert contextualization and prioritization,offering more actionable insights while minimizing analyst fatigue.Usability feedback underscores increased analyst confidence and operational clarity,reinforcing the importance of user-centered design.These results collectively position the HCI-Integrated IDS as a highly effective,scalable,and human-aligned solution for modern threat detection environments.展开更多
文摘Non-traditional security issues have arisen since the 1960s,especially after the end of the Cold War,and are becoming a major issue in world security and politics.This reflects tremendous changes in the world situation.With diverse causes and plural referent objects,non-traditional security issues cover nearly all the problems in the world today and make development difficult to sustain.This raises the question of whether human society and the earth can survive.Power politics one-sidedly stresses the role of power,endangering the harmonious development of nations and the whole of human society.It is not at all conducive to the solution of non-traditional security issues.The solution of non-traditional security issues demands cooperation from all actors in the international community.Multiple means are needed to solve these issues.Equal dialogue between all the actors,which can easily be attained,will play an effective role,as long as all actors respect each other's differences.
基金funded and supported by the Ongoing Research Funding program(ORF-2025-314),King Saud University,Riyadh,Saudi Arabia.
文摘The rapid digitalization of urban infrastructure has made smart cities increasingly vulnerable to sophisticated cyber threats.In the evolving landscape of cybersecurity,the efficacy of Intrusion Detection Systems(IDS)is increasingly measured by technical performance,operational usability,and adaptability.This study introduces and rigorously evaluates a Human-Computer Interaction(HCI)-Integrated IDS with the utilization of Convolutional Neural Network(CNN),CNN-Long Short Term Memory(LSTM),and Random Forest(RF)against both a Baseline Machine Learning(ML)and a Traditional IDS model,through an extensive experimental framework encompassing many performance metrics,including detection latency,accuracy,alert prioritization,classification errors,system throughput,usability,ROC-AUC,precision-recall,confusion matrix analysis,and statistical accuracy measures.Our findings consistently demonstrate the superiority of the HCI-Integrated approach utilizing three major datasets(CICIDS 2017,KDD Cup 1999,and UNSW-NB15).Experimental results indicate that the HCI-Integrated model outperforms its counterparts,achieving an AUC-ROC of 0.99,a precision of 0.93,and a recall of 0.96,while maintaining the lowest false positive rate(0.03)and the fastest detection time(~1.5 s).These findings validate the efficacy of incorporating HCI to enhance anomaly detection capabilities,improve responsiveness,and reduce alert fatigue in critical smart city applications.It achieves markedly lower detection times,higher accuracy across all threat categories,reduced false positive and false negative rates,and enhanced system throughput under concurrent load conditions.The HCIIntegrated IDS excels in alert contextualization and prioritization,offering more actionable insights while minimizing analyst fatigue.Usability feedback underscores increased analyst confidence and operational clarity,reinforcing the importance of user-centered design.These results collectively position the HCI-Integrated IDS as a highly effective,scalable,and human-aligned solution for modern threat detection environments.
