言语行为理论是哲学和语言学,特别是语言哲学和语用学的重要理论之一。与言语行为理论有关的诸多著作中,最重要最经典的是奥斯汀的How to Do Things with Words。然而这不是一本易读的书,为此作者分析了该书的脉络,给准备精读该书的读...言语行为理论是哲学和语言学,特别是语言哲学和语用学的重要理论之一。与言语行为理论有关的诸多著作中,最重要最经典的是奥斯汀的How to Do Things with Words。然而这不是一本易读的书,为此作者分析了该书的脉络,给准备精读该书的读者提供一些参考。展开更多
The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber threats.Among the myriad of potential...The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber threats.Among the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of traffic.As IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT serves.In this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS attacks.The CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)methods.The proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in real-time.This involvesemploying the best-performing ML algorithmfor detection and the integration of warning mechanisms.We believe this approach will significantly enhance the field of security research and continue to refine it based on future insights and developments.展开更多
高中英语课本中有这样一个句子:And there,glowing with a faint blue light in theglass test tubes on the tables,was themysterious something which they had worked so hardto find:Radium.句中something的基本意思为“某事、某...高中英语课本中有这样一个句子:And there,glowing with a faint blue light in theglass test tubes on the tables,was themysterious something which they had worked so hardto find:Radium.句中something的基本意思为“某事、某物”。它究竟归属何种词性,各家辞书众说纷云。有些词典,如《现代高级英汉双解词典》干脆把“名词和代词”不加区别地放在一起,不予细分。展开更多
Background Performance metrics currently focus on the measurement of the application of guideline-indi- cated medications without considering the appropriate dosing of these drugs.
文摘The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber threats.Among the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of traffic.As IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT serves.In this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS attacks.The CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)methods.The proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in real-time.This involvesemploying the best-performing ML algorithmfor detection and the integration of warning mechanisms.We believe this approach will significantly enhance the field of security research and continue to refine it based on future insights and developments.
文摘高中英语课本中有这样一个句子:And there,glowing with a faint blue light in theglass test tubes on the tables,was themysterious something which they had worked so hardto find:Radium.句中something的基本意思为“某事、某物”。它究竟归属何种词性,各家辞书众说纷云。有些词典,如《现代高级英汉双解词典》干脆把“名词和代词”不加区别地放在一起,不予细分。
文摘Background Performance metrics currently focus on the measurement of the application of guideline-indi- cated medications without considering the appropriate dosing of these drugs.
