معرفی
S. Boumerdassi is a researcher at the CEDRIC Laboratory of Conservatoire National des Arts et Métiers (CNAM). He has been actively involved in interdisciplinary research spanning networking, machine learning, image encryption, and IoT systems since the early 2000s. His work has focused on security protocols, energy efficiency in data centers, and anomaly detection frameworks.
- Key Research Areas:
- Networking: VANETs, LoRaWAN, network anomalies, and edge computing.
- Security: Blockchain oracles, cryptographic protocols, and wireless sensor network security.
- Machine Learning: Applications in network optimization and sustainable agriculture.
- Image Encryption: Chaotic maps, DCT coefficients, and grain algorithms.
Recent Publications highlight his contributions to federated learning, anomaly detection, and mobility models.
Leadership and Collaboration
He has co-organized conferences like Mobile, Secure, and Programmable Networking and contributed to edited volumes on machine learning and IoT. His collaborations include researchers from Springer, IEEE, and institutions across France, Italy, Spain, and Canada.
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