MCL-FWA-BILSTM binary and multiclass accuracy comparison. حسب Arshad Hashmi (13835488)

Binary classification accuracy and DR comparison on NSL-KDD. حسب Arshad Hashmi (13835488)

Accuracy comparison with existing approaches for Binary Classification with state of art on UNSW-NB15 and NSL-KDD. حسب Arshad Hashmi (13835488)

Accuracy comparison with existing approaches for binary classification with state of art on UNSW-NB15 and NSL-KDD. حسب Arshad Hashmi (13835488)

The main workflow of the proposed algorithm. حسب Xin Li (51274)

Comparison of accuracy of MCL-FWA-BILSTM model with existing models for binary classification on UNSW-NB15 and NSL-KDD. حسب Arshad Hashmi (13835488)

The detected blocks. حسب Xin Li (51274)

The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Symmetry test result. حسب Jiyong Moon (16819302)

Related studies on IDS using deep learning. حسب Arshad Hashmi (13835488)

"…This imbalance can adversely affect the learning process of predictive models, often resulting in high false-negative rates, a major concern in Intrusion Detection Systems (IDS). By focusing on datasets with this imbalance, we aim to develop and refine advanced algorithms and techniques, such as anomaly detection, cost-sensitive learning, and oversampling methods, to effectively handle such disparities. …"

The architecture of the BI-LSTM model. حسب Arshad Hashmi (13835488)

"…This imbalance can adversely affect the learning process of predictive models, often resulting in high false-negative rates, a major concern in Intrusion Detection Systems (IDS). By focusing on datasets with this imbalance, we aim to develop and refine advanced algorithms and techniques, such as anomaly detection, cost-sensitive learning, and oversampling methods, to effectively handle such disparities. …"

Comparison of accuracy and DR on UNSW-NB15. حسب Arshad Hashmi (13835488)

"…This imbalance can adversely affect the learning process of predictive models, often resulting in high false-negative rates, a major concern in Intrusion Detection Systems (IDS). By focusing on datasets with this imbalance, we aim to develop and refine advanced algorithms and techniques, such as anomaly detection, cost-sensitive learning, and oversampling methods, to effectively handle such disparities. …"

Comparison of DR and FPR of UNSW-NB15. حسب Arshad Hashmi (13835488)

"…This imbalance can adversely affect the learning process of predictive models, often resulting in high false-negative rates, a major concern in Intrusion Detection Systems (IDS). By focusing on datasets with this imbalance, we aim to develop and refine advanced algorithms and techniques, such as anomaly detection, cost-sensitive learning, and oversampling methods, to effectively handle such disparities. …"

Pseudo Code of RBMO. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

P-value on CEC-2017(Dim = 30). حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Memory storage behavior. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Elite search behavior. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Description of the datasets. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"