Hesham Kamal — Papers on Cortexa

crossrefMachine Learning and Knowledge Extraction2025-08-06Cited by 9

AE-DTNN: Autoencoder–Dense–Transformer Neural Network Model for Efficient Anomaly-Based Intrusion Detection Systems

In this study, we introduce an enhanced hybrid Autoencoder–Dense–Transformer Neural Network (AE-DTNN) model for developing an effective intrusion detection system (IDS) aimed at improving the performance and robustness of threat detection strategies within a rapidly changing and…

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crossrefFuture Internet2024-12-23Cited by 47

Advanced Hybrid Transformer-CNN Deep Learning Model for Effective Intrusion Detection Systems with Class Imbalance Mitigation Using Resampling Techniques

Hesham Kamal, Maggie Mashaly

Network and cloud environments must be fortified against a dynamic array of threats, and intrusion detection systems (IDSs) are critical tools for identifying and thwarting hostile activities. IDSs, classified as anomaly-based or signature-based, have increasingly incorporated de…

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