MSE for ILSTM algorithm in binary classification. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

Comparison between ILSTM and machine learning-based algorithms in binary classification. حسب Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. حسب Asmaa Ahmed Awad (16726315)

A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

"…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …"

Confusion matrices for KDDTest+ in binary classification. حسب Asmaa Ahmed Awad (16726315)

Shap analysis for NSL-KDD in binary classification. حسب Asmaa Ahmed Awad (16726315)

Confusion matrices for KDDTest-21 in binary classification. حسب Asmaa Ahmed Awad (16726315)

Confusion matrices for LITNET-2020 dataset in binary classification. حسب Asmaa Ahmed Awad (16726315)

LSTM vs ILSTM for LITNET-2020 in binary classification. حسب Asmaa Ahmed Awad (16726315)

LSTM vs ILSTM for KDDTest-21 for binary classification. حسب Asmaa Ahmed Awad (16726315)

Statistic Test for KDDTest+ and KDDTest-21 in binary classification. حسب Asmaa Ahmed Awad (16726315)

Accuracy and number of iterations for LSTM and ILSTM using KDDTest+ in binary classifications. حسب Asmaa Ahmed Awad (16726315)

Comparison between LSTM and ILSTM using LITNET-2020 in binary classification. حسب Asmaa Ahmed Awad (16726315)

Comparison between other methods in literature using KDDTest+ for binary classification. حسب Asmaa Ahmed Awad (16726315)

Comparison between LSTM, LSTM-BOA, LSTM-CBOA and ILSTM using KDDTest+ and KDDTest-21 in binary classification with average 10 runs. حسب Asmaa Ahmed Awad (16726315)

Summary of LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

SHAP analysis for LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

Comparison of intrusion detection systems. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

Parameter setting for CBOA and PSO. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

NSL-KDD dataset description. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"