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. …"

The architecture of LSTM cell. 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. …"

The architecture of ILSTM. 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 LSTM. 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. …"

LITNET-2020 data splitting approach. 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. …"

Transformation of symbolic features in NSL-KDD. 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. …"

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. حسب Olaide N. Oyelade (14047002)

الموضوعات:

An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... حسب Olaide N. Oyelade (14047002)

الموضوعات:

Medium-scale dataset comparative analysis using fitness and cost values for population size 50 and 100. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Large-scale dataset comparative analysis using computation resources. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Datasets and their properties. حسب Olaide N. Oyelade (14047002)

الموضوعات:

An illustration and comparison of the cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50... حسب Olaide N. Oyelade (14047002)

الموضوعات:

Small-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Medium-scale dataset comparative analysis using the number of features selected. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Small-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Large-scale dataset comparative analysis using the number of features selected. حسب Olaide N. Oyelade (14047002)

الموضوعات: