http://localhost:8080/jspui/handle/123456789/488 2026-05-25T01:57:38Z http://localhost:8080/jspui/handle/123456789/1120 Title: A Layered Overview of Communication Architecture for IoT: Enabling the “Any Application–Any Device” Paradigm Authors: BENTAHAR, Atef Abstract: The Internet of Things (IoT) paradigm, which interconnects billions of diverse, resource-constrained devices, requires specialized communication architectures to achieve massive scalability and interoperability. This paper provides a structured overview of the IoT communication stack from physical transmission mechanisms to service-level interactions, highlighting how traditional network models are adapted to meet IoT-specific constraints. Through comparative analysis, we underline the particular challenges posed by low-power and lossy networks, time-critical data processing, and the incorporation of lightweight, web-oriented service frameworks. A special focus is placed on the abstraction layer that enables the “Any Application– Any Device” paradigm through standardized application services. The study clarifies how these specialized architectures are effectively implemented in practice. 2026-01-25T00:00:00Z http://localhost:8080/jspui/handle/123456789/1119 Title: Comparative Evaluation of Machine Learning Techniques for Enhanced Intrusion Detection Systems Performance Authors: BENTAHAR, Atef Abstract: In today's rapidly evolving digital landscape, safeguarding computer systems from increasingly sophisticated and frequent cyberattacks is more critical than ever. Intrusion detection plays a pivotal role in maintaining the integrity and confidentiality of sensitive data. Leveraging cutting-edge machine learning advancements, this paper explores the development of highly efficient and responsive security systems. We rigorously evaluate various machine learning techniques for intrusion detection. The results indicate that the Random Forest Classifier stands out for its exceptional precision and speed, making it an ideal choice for real-time applications. Additionally, our research benchmarks these models against existing relevant works, demonstrating the clear superiority of our implementation across multiple performance metrics. 2025-04-14T00:00:00Z http://localhost:8080/jspui/handle/123456789/811 Title: UNE NOUVELLE MAPPE DE QUALITE POUR LE DEROULEMENT DE PHASE DE L’INSAR Authors: BENTAHAR, Tarek; BENTAHAR, Atef Abstract: Dans cet article, une nouvelle mappe de qualité basée sur une modification de la mappe de la variance de la dérivée de la phase est proposée. Comme cette mappe proposée fournit plus détails sur les variations locales de l’interférogramme notamment pour les franges et les bords, le déroulement de phase pourrait être plus précis et fiable. L’influence de telle mappe de qualité se manifeste substantiellement sur les régions de forte densité des résidus. Pour prouver l’efficacité de notre proposition, le test a été réalisé sur des données satellitaires réelles et la comparaison a été faite selon plusieurs métriques pertinentes. 2021-03-12T00:00:00Z http://localhost:8080/jspui/handle/123456789/810 Title: Performance Analysis of Pioneer Single Baseline Phase Unwrapping Techniques Authors: BENTAHAR, Tarek; BENTAHAR, Atef Abstract: Phase unwrapping is a key step in the interferogram processing chain. This process reconstructs the phase images to obtain a 3D presentation of the scanned surface called digital elevation model. From 80's to date, several phase unwrapping algorithms have been proposed whose performance differs from one algorithm to another. Some algorithms are fast or accurate and there are other approaches that try to attain a tradeoff between accuracy and processing time. This paper analyzes the performance of some pioneering methods in the phase unwrapping field. The chosen methods are implemented and tested for real inSAR data provided by ESA ERS-1, and compared according to several relevant criteria to assess the computation time and accuracy of each one. 2021-03-24T00:00:00Z