Výsledky vyhledávání - "JOUHARI, Mohammed"

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Efficient Intrusion Detection: Combining $\chi^2$ Feature Selection with CNN-BiLSTM on the UNSW-NB15 Dataset

Autor: Jouhari, Mohammed, Benaddi, Hafsa, Ibrahimi, Khalil

Intrusion Detection Systems (IDSs) have played a significant role in the detection and prevention of cyber-attacks in traditional computing systems. It is not surprising that this technology is now being applied to secure Internet of Things (IoT) net

Externí odkaz: http://arxiv.org/abs/2407.14945

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Lightweight CNN-BiLSTM based Intrusion Detection Systems for Resource-Constrained IoT Devices

Autor: Jouhari, Mohammed, Guizani, Mohsen

Intrusion Detection Systems (IDSs) have played a significant role in detecting and preventing cyber-attacks within traditional computing systems. It is not surprising that the same technology is being applied to secure Internet of Things (IoT) networ

Externí odkaz: http://arxiv.org/abs/2406.02768

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Deep Reinforcement Learning-based Energy Efficiency Optimization For Flying LoRa Gateways

Autor: Jouhari, Mohammed, Ibrahimi, Khalil, Othman, Jalel Ben, Amhoud, El Mehdi

A resource-constrained unmanned aerial vehicle (UAV) can be used as a flying LoRa gateway (GW) to move inside the target area for efficient data collection and LoRa resource management. In this work, we propose deep reinforcement learning (DRL) to op

Externí odkaz: http://arxiv.org/abs/2302.05214

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Spreading Factor assisted LoRa Localization with Deep Reinforcement Learning

Autor: Etiabi, Yaya, JOUHARI, Mohammed, Burg, Andreas, Amhoud, El Mehdi

Most of the developed localization solutions rely on RSSI fingerprinting. However, in the LoRa networks, due to the spreading factor (SF) in the network setting, traditional fingerprinting may lack representativeness of the radio map, leading to inac

Externí odkaz: http://arxiv.org/abs/2205.11428

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A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges

Autor: Jouhari, Mohammed, Saeed, Nasir, Alouini, Mohamed-Slim, Amhoud, El Mehdi

Long-range (LoRa) technology is most widely used for enabling low-power wide area networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides extensive coverage for low-power devices, making it an ideal communication sys

Externí odkaz: http://arxiv.org/abs/2202.11082

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Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization

Autor: Jouhari, Mohammed, Al-Ali, Abdulla, Baccour, Emna, Mohamed, Amr, Erbad, Aiman, Guizani, Mohsen, Hamdi, Mounir

Unmanned Aerial Vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems relying on direct observatio

Externí odkaz: http://arxiv.org/abs/2105.11013

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Akademický článek

Anomaly Detection in Industrial IoT Using Distributional Reinforcement Learning and Generative Adversarial Networks.

Autor: Benaddi, Hafsa¹ (AUTHOR), Jouhari, Mohammed² (AUTHOR), Ibrahimi, Khalil¹ (AUTHOR), Ben Othman, Jalel³ (AUTHOR) jalel.benothman@centralesupelec.fr, Amhoud, El Mehdi² (AUTHOR)

Publikováno v: Sensors (14248220). Nov2022, Vol. 22 Issue 21, p8085. 18p.