PLURIDIS – Laboratoire Informatique d’Avignon

PhD defense of Sahand Khodaparas Talatapeh – 15/07/2024

16 July 2024

Title: Cache Orchestration and Optimization in IoT Networks Jury Members: Mme AnnaMaria VEGNI, Roma Tree University, Italy Rapporteur M. Antoine GALLAIS, INSA Hauts-de-France, France Rapporteur M. Jamshid BAGHERZADEH, Urmia University, Iran Examinateur Mme Leila SHARIFI, Urmia University, Iran Examinatrice M. Vahid SOLOUK, Urmia University, Iran Examinateur M. Yezekael HAYEL, Avignon University, France Examinateur M. Abderrahim BENSLIMANE, Avignon University, France Directeur de thèse M. Saleh YOUSEFI, Urmia University, Iran Co-Direteur de thèse Abstract In the rapidly evolving landscape of the Internet of Things (IoT) and the Internet of Vehicles (IoV), caching emerges as a pivotal technology to enhance network efficiency, reduce latency, and improve user experiences. These technological domains face growing demands for better data management and delivery mechanisms due to increasing data volumes and network complexity. In this thesis, we explore innovative caching strategies within the realms of the IoT and the IoV to enhance network services and user experiences. The research presented spans three distinct yet interconnected studies, each addressing critical aspects of network performance, including latency reduction, content delivery efficiency, and network coverage expansion. The first study focuses on enhancing content-centric networking caching capabilities within IoT environments. By employing hierarchical network orchestrations and a global SDN/Cache controller (GSCC), Plus d'infos

Best paper award

19 February 2024

Congratulations to Grace Tessa Masse and Abderrahim Benslimane, for the best paper award they obtained at International Conference on Computing, Networking and Communications (IEEE ICNC 2024) Title: A Secure Hierarchical Federated Learning Using Dirichlet-based Trust Management Abstract—Hierarchical Federated Learning (HFL) is a distributed machine learning training system in which a server works with several clients and edge nodes while maintaining data privacy. Distributed machine learning training systems are also known as Federated Learning, but HFL is a type of Federated Learning that utilizes a hierarchical network architecture to address computational issues when dealing with a high number of clients. However, HFL is vulnerable to attacks such as data poisoning, which may jeopardize the entire training process and result in misclassifications. As system defenders, we have to tackle this issue. Using a label-flipping attack, we investigate the effect of data poisoning attacks on HFL training. We propose a trust management-based strategy to mitigate data poisoning attacks, which assesses client trustworthiness using a Dirichlet distribution. We maintain a record of previous activities, allowing the server to enhance its knowledge based on client reliability. We demonstrate the proposed approach’s effectiveness through improvements in model performance after removing malicious clients, using the MNIST dataset Plus d'infos

PhD defense of Julio Perez-Garcia – 18 December 2023

14 December 2023

Place: University of Avignon, Campus Hannah Arendt, Salle des ThèsesDate: Monday, December 18, 2023 at 14:00. Title: Contribution to security and privacy in the Blockchain-based Internet of Things: Robustness, Reliability, and Scalability. Abstract: The Internet of Things (IoT) is a diverse network of objects or ”things” typically interconnected via the Internet. Given the sensitivity of the information exchanged in IoT applications, it is essential to guarantee security and privacy. This problem is aggravated by the open nature of wireless communications, and the power and computing resource limitations of most IoT devices. At the same time, existing IoT security solutions are based on centralized architectures, which raises scalability issues and the single point of failure problem, making them susceptible to denial-of-service attacks and technical failures. Blockchain has emerged as an attractive solution to IoT security and centralization issues. Blockchains replicate a permanent, append-only record of all transactions occurring on a network across multiple devices, keeping them synchronized through a consensus protocol. Blockchain implementation may involve high computational and energy costs for devices. Consequently, solutions based on Fog/Edge computing have been considered in the integration with IoT. This approach shifts the higher computational load and higher energy consumption to the devices with higher Plus d'infos

PhD defense of Sarkis Moussa – 30 June 2023

30 June 2023

Date: Friday, June 30, 2023. 2pm Place: thesis room (salle des thèses) at the Hannah Arendt campus. For those unable to attend, here is the BBB link for the video conference: https://v-au.univ-avignon.fr/live/bbb-soutenance-de-these-sarkis-moussa-30-juin-2023/ Title: Architecture and Protocols for Public Safety Users in the 5G Cellular Networks Abstract: Public Safety Networks (PSNs) are wireless communication systems designed to meet the needs of emergency responders, including firefighters, police, and many other Public Safety (PS) agencies. These networks are used to prevent or respond to incidents that pose a threat to people or property. Traditionally, these PSNs were supported by reliable, but low-rate radio technologies that provide limited services such as voice communication among Public Safety Users (PSUs). Consequently, their capability to take advantage of recent developments in wireless networks and broadband applications was restricted. At the forefront of wireless communication technologies, 5th Generation (5G) and beyond Cellular Networks (CNs), are ideal for this purpose due to their advanced infrastructure and tailored techniques developed for broadband services. Their capacity for high data transmission, low latency in data exchange, and ability to support a significant number of connected devices make them perfectly suited to overcome the limitations associated with PSNs. Integrating PSNs into 5G can Plus d'infos

PhD defense of Chaimaa Boudagdigue – 8 February 2023

8 February 2023

Thesis presented at Avignon University to obtain the grade of doctor. Titre : Trust Models to secure Internet of Things networks Superviser: Abderrahim Benslimane Date: 15 March, 2023 at 14:00 Abstract: The Internet of Things (IoT) is a new paradigm where any device of everyday life can become part of the Internet. The device just needs to be equipped with a microcontroller, a transceiver and appropriate protocol stacks that make it able to communicate. IoT makes everyday devices intelligent and able to interact in a collaborative way in order to provide intelligent services in different fields such as: agriculture, industry, healthcare and many others. To achieve these objectives, IoT devices must manage confidential and privacy-related data of their users, which makes them very vulnerable to security threats. However, IoT devices do not have the necessary resources (energy, memory, processing, etc.) to implement strong security or to apply the traditional security measures based on cryptographic techniques usually deployed in traditional Internet. Moreover, the traditional security measures cannot ensure the reliability of the IoT networks, especially in the presence of internal attacks. Hence, our work consists in proposing a dynamic analytical trust management model where each IoT device in the network evaluates the trust Plus d'infos

PhD defense of Sakil Ahmed Chowdhury – 4 May 2022

4 May 2022

Title: Three Branch Diversity Systems for Multi-Hop IoT Networks Date: May 4, 2022 at 7:30 pm Thesis Examination Committee: Abstract: Internet of Things (IoT) is an emerging technological paradigm connecting numerous smart objects for advanced applications ranging from home automation to industrial control to healthcare. The rapid development of wireless technologies and miniature embedded devices has enabled IoT systems for such applications, which have been deployed in a variety of environments. One of the factors limiting the performance of IoT devices is the multipath fading caused by reflectors and attenuators present in the environment where these devices are deployed. Leveraging polarization diversity is a well-known technique to mitigate the deep signal fades and depolarization effects caused by multipath. However, neither experimental validation of the performance of polarization diversity antenna with more than two branches nor the potency of existing antenna selection techniques on such antennas in practical scenarios has received much attention. The objectives of this dissertation are threefold. First, to demonstrate the efficacy of a tripolar antenna, which is specifically designed for IoT devices, in harsh environments through simulations and experimental data. Second, to develop antenna selection strategies to utilize polarized signals received at the antenna, considering the restrictions Plus d'infos

PhD defense of Randa Abdelmonem – 26 January 2021

26 January 2021

Date: Tuesday 26 January 2021 at 9:00 AM. Title: Quality of Service and Privacy in Internet of Things Dedicated to Healthcare Jury: Abstract: The Internet of Things (IoT) based healthcare systems usually composed of medical and environmental sensors, remote servers, and the network. These systems focus on providing remote monitoring, disease diagnosis, and treatment progress observation. The healthcare systems in IoT domain helps in realizing long-term economical, ubiquitous, and patient centered care systems, that result in improving treatment and patient outcomes. This research contributes to the domain by proposing a Cloud-Fog based architecture that can embrace multiple healthcare scenarios, and able to adapt dynamically with the context and status of the patients. It allows the mobility and physical activity of the patients in the environment through deployment and implementation of an appropriate Received Signal Strength (RSS) based handoff mechanism. It also proposes a mobility-aware task scheduling and allocation approach in cloud-fog computing paradigm, called MobMBAR, with the objective of minimizing the total schedule time (makespan). MobMBAR performs dynamic balanced healthcare tasks distribution between the cloud and fog devices. It is a data locality based approach that depends on changing the location where the data is computed to where it actually resides. Plus d'infos

PhD defense of Dina Tarek – 18 December 2020

18 December 2020

Dina Tarek will defend her thesis on Friday, December 18th at 2:30 PM. This thesis is jointly supervised with Egypt. Titre : Development of Spectrum Sharing Protocol for Cognitive Radio Internet of Things Jury: Abstract: Internet of Things (IoT) presents a new life style by developing smart homes, smart grids, smart city, smart transportation … etc., so IoT is developing rapidly. However recent researches focus on developing the IoT applications disregarding the IoT spectrum scarcity problem facing it. Integrating Internet of Things (IoT) technology and Cognitive Radio Networks (CRNs), forming Cognitive Radio Internet of Things (CRIoTs), is an economical solution for overcoming the IoT spectrum scarcity. The aim of this thesis is to solve the problem of spectrum sharing for CRIoT; the work in thesis is presented in three parts. Our first contribution is to propose two new protocols to solve the problem of channel status prediction for interweave CRNs. Both protocols uses Hidden Markov Model (HMM). In the training stage of both protocols, the available data are trained to produce two HMM models, an idle HMM model and a busy one. Both models are used together to produce the 2-model HMM. In the prediction stage the first protocol uses Bayes theorem and the 2-model HMM, while the Plus d'infos