Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive data.Traditional detection methods often fail to keep pace with ...Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive data.Traditional detection methods often fail to keep pace with the evolving sophistication of cyber threats.This paper introduces a novel hybrid ensemble learning framework that leverages a combination of advanced machine learning algorithms—Logistic Regression(LR),Support Vector Machines(SVM),eXtreme Gradient Boosting(XGBoost),Categorical Boosting(CatBoost),and Deep Neural Networks(DNN).Utilizing the XSS-Attacks-2021 dataset,which comprises 460 instances across various real-world trafficrelated scenarios,this framework significantly enhances XSS attack detection.Our approach,which includes rigorous feature engineering and model tuning,not only optimizes accuracy but also effectively minimizes false positives(FP)(0.13%)and false negatives(FN)(0.19%).This comprehensive methodology has been rigorously validated,achieving an unprecedented accuracy of 99.87%.The proposed system is scalable and efficient,capable of adapting to the increasing number of web applications and user demands without a decline in performance.It demonstrates exceptional real-time capabilities,with the ability to detect XSS attacks dynamically,maintaining high accuracy and low latency even under significant loads.Furthermore,despite the computational complexity introduced by the hybrid ensemble approach,strategic use of parallel processing and algorithm tuning ensures that the system remains scalable and performs robustly in real-time applications.Designed for easy integration with existing web security systems,our framework supports adaptable Application Programming Interfaces(APIs)and a modular design,facilitating seamless augmentation of current defenses.This innovation represents a significant advancement in cybersecurity,offering a scalable and effective solution for securing modern web applications against evolving threats.展开更多
Objective： To study multi-directional derivation of cord blood mononuclear cells to CD3AK, LAK and CIK cells as well as changes of killing activity to gastric cancer cell strain in vitro. Methods： CD3mAb and IL-2 we...Objective： To study multi-directional derivation of cord blood mononuclear cells to CD3AK, LAK and CIK cells as well as changes of killing activity to gastric cancer cell strain in vitro. Methods： CD3mAb and IL-2 were used to induce CD3AK cells, and IL-2 was used to induce LAK cells; IFN-γ was used in the beginning, then IL-1, CD3mAb and IL-2 were used to induce CIK cells after 24 h for observing amplification and analyzing their relationship. The phenotypes of the cultured CIK cells were analyzed by flow cytometry. Subsequently, by using MGC-803 gastric cancer cell strain as target cells, the killing activity of CD3AK, LAK and CIK cells was evaluated by using MTT method. Results： The amplification activity of CD3AK and CIK cells was all far higher than LAK cells （P〈0.05）. The amplification activity had no obvious difference between CIK cells and CD3AK cells at prophase, but that was far higher in CIK cells than CD3AK cells at about 20^th day （P〈0.05）. The flow cytometry revealed that the amount of CD3^＋ CD56^＋ cells, major effector cells after CIK cells being cultured was significantly increased （P〈0.05）, moreover, the amount of CD8^＋ cells was significantly increased as well （P〈0.05）. The killing activities of CD3AK and CIK cells to the MGC-803 gastric cancer cell strain were all significantly higher than LAK cells, while the killing activity of CIK cells was stronger than CD3AK cells （P〈0.05）. Conclusion： CIK cells have stronger amplification activity and killing activity, and can be taken as more effective killing cells applied to the tumor adoptive immunotherapy.展开更多
Let E be a vector bundle over a compact Riemannian manifold M. We construct a natural metric on the bundle space E and discuss the relationship between the killing vector fields of E and M. Then we give a proof of the...Let E be a vector bundle over a compact Riemannian manifold M. We construct a natural metric on the bundle space E and discuss the relationship between the killing vector fields of E and M. Then we give a proof of the Bott-Baum-Cheeger Theorem for vector bundle E.展开更多
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2024R513),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive data.Traditional detection methods often fail to keep pace with the evolving sophistication of cyber threats.This paper introduces a novel hybrid ensemble learning framework that leverages a combination of advanced machine learning algorithms—Logistic Regression(LR),Support Vector Machines(SVM),eXtreme Gradient Boosting(XGBoost),Categorical Boosting(CatBoost),and Deep Neural Networks(DNN).Utilizing the XSS-Attacks-2021 dataset,which comprises 460 instances across various real-world trafficrelated scenarios,this framework significantly enhances XSS attack detection.Our approach,which includes rigorous feature engineering and model tuning,not only optimizes accuracy but also effectively minimizes false positives(FP)(0.13%)and false negatives(FN)(0.19%).This comprehensive methodology has been rigorously validated,achieving an unprecedented accuracy of 99.87%.The proposed system is scalable and efficient,capable of adapting to the increasing number of web applications and user demands without a decline in performance.It demonstrates exceptional real-time capabilities,with the ability to detect XSS attacks dynamically,maintaining high accuracy and low latency even under significant loads.Furthermore,despite the computational complexity introduced by the hybrid ensemble approach,strategic use of parallel processing and algorithm tuning ensures that the system remains scalable and performs robustly in real-time applications.Designed for easy integration with existing web security systems,our framework supports adaptable Application Programming Interfaces(APIs)and a modular design,facilitating seamless augmentation of current defenses.This innovation represents a significant advancement in cybersecurity,offering a scalable and effective solution for securing modern web applications against evolving threats.
文摘Objective： To study multi-directional derivation of cord blood mononuclear cells to CD3AK, LAK and CIK cells as well as changes of killing activity to gastric cancer cell strain in vitro. Methods： CD3mAb and IL-2 were used to induce CD3AK cells, and IL-2 was used to induce LAK cells; IFN-γ was used in the beginning, then IL-1, CD3mAb and IL-2 were used to induce CIK cells after 24 h for observing amplification and analyzing their relationship. The phenotypes of the cultured CIK cells were analyzed by flow cytometry. Subsequently, by using MGC-803 gastric cancer cell strain as target cells, the killing activity of CD3AK, LAK and CIK cells was evaluated by using MTT method. Results： The amplification activity of CD3AK and CIK cells was all far higher than LAK cells （P〈0.05）. The amplification activity had no obvious difference between CIK cells and CD3AK cells at prophase, but that was far higher in CIK cells than CD3AK cells at about 20^th day （P〈0.05）. The flow cytometry revealed that the amount of CD3^＋ CD56^＋ cells, major effector cells after CIK cells being cultured was significantly increased （P〈0.05）, moreover, the amount of CD8^＋ cells was significantly increased as well （P〈0.05）. The killing activities of CD3AK and CIK cells to the MGC-803 gastric cancer cell strain were all significantly higher than LAK cells, while the killing activity of CIK cells was stronger than CD3AK cells （P〈0.05）. Conclusion： CIK cells have stronger amplification activity and killing activity, and can be taken as more effective killing cells applied to the tumor adoptive immunotherapy.
文摘Let E be a vector bundle over a compact Riemannian manifold M. We construct a natural metric on the bundle space E and discuss the relationship between the killing vector fields of E and M. Then we give a proof of the Bott-Baum-Cheeger Theorem for vector bundle E.
