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ORCIDHafsa Benaddi
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2020 – today
- 2024
[c9]Mohammed Jouhari, Hafsa Benaddi, Khalil Ibrahimi:
Efficient Intrusion Detection: Combining X2 Feature Selection with CNN-BiLSTM on the UNSW-NB15 Dataset. WINCOM 2024: 1-6- [i1]Mohammed Jouhari, Hafsa Benaddi, Khalil Ibrahimi:
Efficient Intrusion Detection: Combining χ2 Feature Selection with CNN-BiLSTM on the UNSW-NB15 Dataset. CoRR abs/2407.14945 (2024) - 2023
- [c8]Hafsa Benaddi, Mohammed Jouhari, Khalil Ibrahimi, Abderrahim Benslimane, El Mehdi Amhoud:
Improvement of Anomaly Detection System in the IoT Networks using CNN-LSTM Approach. GLOBECOM 2023: 3771-3776 - 2022
- [j2]Hafsa Benaddi
, Mohammed Jouhari, Khalil Ibrahimi, Jalel Ben-Othman, El Mehdi Amhoud:
Anomaly Detection in Industrial IoT Using Distributional Reinforcement Learning and Generative Adversarial Networks. Sensors 22(21): 8085 (2022) - [j1]Hafsa Benaddi, Khalil Ibrahimi, Abderrahim Benslimane, Mohammed Jouhari, Junaid Qadir:
Robust Enhancement of Intrusion Detection Systems Using Deep Reinforcement Learning and Stochastic Game. IEEE Trans. Veh. Technol. 71(10): 11089-11102 (2022) - [c7]Khalil Ibrahimi, Hafsa Benaddi:
Improving the IDS for BoT-IoT Dataset-Based Machine Learning Classifiers. CommNet 2022: 1-6 - [c6]Hafsa Benaddi, Mohammed Jouhari, Khalil Ibrahimi, Abderrahim Benslimane, El Mehdi Amhoud:
Adversarial Attacks Against IoT Networks using Conditional GAN based Learning. GLOBECOM 2022: 2788-2793 - 2021
- [c5]Hafsa Benaddi, Mohammed Jouhari, Khalil Ibrahimi, Abderrahim Benslimane:
Securing IoT Transactions Against Double-Spending Attacks based on Signaling Game Approach. GLOBECOM 2021: 1-6 - 2020
- [c4]Hafsa Benaddi, Khalil Ibrahimi:
A Review: Collaborative Intrusion Detection for IoT integrating the Blockchain technologies. WINCOM 2020: 1-6
2010 – 2019
- 2019
- [c3]Hafsa Benaddi, Khalil Ibrahimi, Haytham Dahri, Abderrahim Benslimane:
A Framework to Secure Cluster-Header Decision in Wireless Sensor Network Using Blockchain. ACOSIS 2019: 205-218 - [c2]Hafsa Benaddi, Khalil Ibrahimi, Abderrahim Benslimane, Junaid Qadir:
A Deep Reinforcement Learning Based Intrusion Detection System (DRL-IDS) for Securing Wireless Sensor Networks and Internet of Things. WiCON 2019: 73-87 - 2018
- [c1]Hafsa Benaddi, Khalil Ibrahimi, Abderrahim Benslimane:
Improving the Intrusion Detection System for NSL-KDD Dataset based on PCA-Fuzzy Clustering-KNN. WINCOM 2018: 1-6
Coauthor Index
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