3.1.1 Frugality and opportunism

As the objects we consider are resource-limited and that they use a rare resource to communicate (wireless medium), all our solutions must be frugal and use as little resources as possible. A way to alleviate the energy consumption and the medium utilization is to reduce the data to send and/or to smartly decide when to send it, by what mean and to whom without jeopardizing the accuracy and completeness of the data. When to send a piece of data can indeed impact the resource utilization since in a dynamic environment, some interference could appear at different times; in a mobile environment, a piece of data could be carried rather than transmitted; in an energy-harvesting network, the amount of available energy could grow. We thus intend to closely analyse and understand interference impacts on different environments and contexts on one hand (as the research initiated in LumiCar, EthiCam, AgriNET projects) and to exploit them in the design of our protocols.

Deciding what data to send allows for a data reduction and resource savings. To do so, we will use machine learning techniques (e.g. Thompson sampling, Bayesian approaches, linear approaches, ARMA, Pearson sampling etc) that we will adapt to fit the specific context of the applications. The idea is to propose predictive algorithms to "guess" a data rather than transmitting it. This is among others what we are investigating in the AgriNET project.

In case of the availability of multiple communication technologies, the choice of this technology will impact the global system since all technologies do not provide the same QoS performances (delays, throughputs, etc) with different energy consumptions and do not face interferences the same way depending on the environment. We will thus analyse and understand all these specificities to combine them to get the best performances.

In all above mentioned cases, we will try to provide time and space depend protocols as frugal as possible but still meeting the application requirements and expectations. This will be done by opportunistically leveraging network particularities (multiple technologies, mobility, energy-harvesting, etc) based on experimental-driven behavioral analysis, as initiated with the collaboration with Sencrop.

3.1.2 Security

Security of wireless transmissions is a rising issue that gains importance with the increase of wireless devices. Our team has just started research work in security but we will pursue our efforts. Our goal will be to secure the wireless communications in different ways. Indeed, traditional security techniques (cryptography, firewalls, etc) cannot be applied in FUN because of their pervasive feature and limited resources. In terms of Security, we will focus on the lowest layers of the communication stack in order to first identify attacks that may appear at these levels and proposes i) recovering and healing solutions and ii) new solutions that are robust by design.

At the MAC layer, we will for instance investigate denial of sleep-like attacks that aim to make nodes deplete their energy quickly. At NET layer, we will investigate different routing protocols that are able to detect an abnormal behavior of a neighbor node to then exclude it from any network operation. This has obviously to be done locally and in a distributed way. In all cases, the same methodology will be applied: observe, understand and model, to then identify the threat or the malicious entity and finally heal. In some cases, we can leverage the characteristics of the communication technology to reinforce the security aspect, such as VLC that may allow Line-of-Sight (LOS) communications and for which certain types of attacks that can be effective for "traditional" wireless systems (i.e., jamming attacks) cannot be easily applied. The works initiated in the framework of the H2020 CyberSANE project, in the DGA grant and in DEPOSIA project, fall within this perspective.

3.1.3 Interconnectivity

Another challenge faced by FUN is their interconnectivity to traditional networks such as Internet and the data offloading. Because of their limited capacity, FUN devices may need to call for remote services. These latter are usually hosted in the cloud. But being served by the cloud implies sometimes long latency and uselessly congestion of the wired network. We will thus investigate how to get these services closer to the FUN devices to alleviate the energy consumption, reduce latency and network congestion. This will go from edge and mobile edge deployments to service distribution over more powerful heterogeneous devices. Our research will analyse devices needs and estimate in time and space the services to be deployed. When the service is expected to be temporary, mobile edge services could be deployed and so our investigations will include the self-deployment techniques. When some already deployed wireless devices feature more capacity, we can leverage this node heterogeneity to distribute the services over these nodes. The research conducted towards this third objective will call for adaptation of machine learning techniques to predict needs, to mobility modeling and cross-layer communication protocols. This has been initiated in the DRUID-NET project.

7.1.1 PILOT Dataset

• Name:
  Privacy-preserving data collectIon of wireLess cOmmunication Technologies.
• Keywords:
  Wireless network, Human mobility, Sensors
• Scientific Description:
  "PILOT dataset" is a privacy-preserving collection of wireless communication data from three technologies: WiFi, BLE (Bluetooth Low Energy), and LoRa (Long Range Radio), alongside sensor data (acceleration, roll, pitch). It is collected over 90 hours in various mobility scenarios, including static and mobile contexts, using Pycom FiPy devices. The dataset, which preserves privacy by masking sensitive information, is available on GitHub for use in human mobility studies and machine learning applications.
• Functional Description:
  PILOT dataset provides a new generation of collected data that would help in providing keys for studying human mobility or other applications. It is characterized by mainly two novel approaches for collecting data, at the level of Model type and Parameters recorded, as follows: 1) Collecting different types of data from sensors and wireless communication technologies at a time: WiFi probe-response, BLE beacons, LoRa packets, and from the sensors: Acceleration, Roll and Pitch information. 2) The data is collected in different mobility scenarios and mainly classified into two categories: Static vs Mobile. The overall collected data till now spans about 90 hours in total in different mobility scenarios collected using a Micropython enabled microcontroller called FiPy device. The dataset is released as a collection of text files and comma-separated values (CSV) files with mainly the timestamp, a unique identifier of the emitting device, RSSI (Received Signal Strength), and other information dedicated to each wireless technology. This dataset is privacy-preserving since it fully meets the GDPR specification, where the mac addresses and the device names are masked.
• Contact:
  Jana Koteich

7.1.2 my_ble

• Name:
  ESP-IDF my_ble component
• Keyword:
  Bluetooth
• Functional Description:
  This is a component campatible with ESP IDF V5.3.1 providing an API to use Apache MyNewt NimBLE host on ESP32 MCUs exposing simple to use predefined functions, yet giving full control over core functionalities like task handling, multiprocessing and semaphore enabled BLE scan checking.
• Contact:
  Khalil Ben Kalboussi
• Participant:
  Khalil Ben Kalboussi

7.1.3 LoRa WuR

• Name:
  librairie ESP-IDF pour module LoRa sx1261
• Keywords:
  Sx1261, LoRa, ESP32, ESP-IDF
• Functional Description:
  This is a library (in the form of a component) compatible with ESP-IDF V5.3.1 that enables the use of the SEMTECH SX1261 LoRa module with the ESP32(S3). The component is based on the low-level hardware driver provided by SEMTECH, which operates over the SPI bus, modified to include functions for sending, receiving, and packet detection in sleep mode (RxDutyCycle) in GFSK mode. The library provides functions for use in a normal mode, where it automatically handles tasks and SPI bus management internally, or in an advanced mode that offers full control over SPI bus management and process scheduling.
• URL:
  https://­gitlab.­inria.­fr/­fun-team/­lora_wur_v2/­-/­tree/­lora_wur
• Contact:
  Khalil Ben Kalboussi

SLICES

Participants: Nathalie Mitton, Lucille Colin, Solenne Fortun.

The FUN team is leading the deployment of the SLICES-FR research infrastructure, national node of the SLICES-RI ESFRI, also led by Inria and the FUN team.

8.3.1 Device mobility

The ubiquitous nature of mobile devices equipped with radio communication technologies made the collection of data a commonplace especially for studying human mobility. The collection of such datasets forms the intermediate results in many scientific research projects. Therefore, with the lack of datasets, collecting and publishing data should be seriously addressed since several scientific research is based on the gathering and analysis of measurement data. In 17, 18, we introduce the PILOT dataset, also referenced in 7.1.1, a Privacy-preserving data collectIon of wireLess cOmmunication Technologies.

The dataset is a collection of four jointly collected information in different mobility contexts. It includes three wireless communication technologies: WiFi probe- responses, BLE (Bluetooth Low Energy) beacons, and LoRa (Long Range Radio) packets, plus additional information: Acceleration, Roll, and Pitch, all collected at the same time. We provide the keys to reproduce such data collection and share the datasets already collected. The dataset is collected for approximately 90 hours, with a size of 200 MB using FiPy devices from Pycom and it is uploaded to GitHub. The dataset's utility is validated through the application of a classification machine learning model that determines the real-life situation of devices through the communication links monitored in different scenarios with an accuracy of 94%. Thus, we believe that such dataset is important for human mobility studies and applications of integrated sensing systems since it offers a new form of a classified collected data that does not exist in the already published datasets. This knowledge is latter exploited to ehance routing protocols as explained in Section 8.6.

8.3.2 Network servicing

Internet of Things (IoT) applications generate tremendous amounts of data streams which are characterized by varying Quality of Service (QoS) indicators. These indicators need to be accurately estimated in order to appropriately schedule the computational and communication resources of the access and Edge networks. Nonetheless, such types of IoT data may be produced at irregular time instances, while suffering from varying network conditions and from the mobility patterns of the edge devices. At the same time, the multipurpose nature of IoT networks may facilitate the co-existence of diverse applications, which however may need to be analyzed separately for confi- dentiality reasons.

Hence, in 6, we aim to forecast time series data of key QoS metrics, such as throughput, delay, packet delivery and loss ratio, under different network configuration settings. Additionally, to secure data ownership while performing the QoS forecasting, we propose the FeDerated Temporal Sparse Transformer (FeD-TST) framework, which allows local clients to train their local models with their own QoS dataset for each network configuration; subsequently, an associated global model can be updated through the aggregation of the local models. In particular, three IoT applications are deployed in a real testbed under eight different network configurations with varying parameters including the mobility of the gateways, the transmission power and the channel frequency. The results obtained indicate that our proposed approach is more accurate than the identified state-of-the-art solutions. This result relies on the sisyphe tool described in Section Software and 7.3.

8.3.3 Network discovery

Due to their limited resources, IoT devices are constantly striving to find a balance between energy consumption and performance. In this ongoing endeavor, the communication module frequently emerges as the foremost contributor to energy consumption. Among various communication technologies, Bluetooth Low Energy (BLE) stands out as a promising candidate due to its lightweight architecture and excellent performance. Despite recent advances in BLE optimization, the Neighbor Discovery Process (NDP) remains a highly energy-cost task. To enhance energy efficiency during this operation, we propose in 23 a new approach for the NDP that leverages the multicore architecture of a recent microcontroller to dynamically adjust the scanning duration based on the number of devices to discover. Intensive simulations have shown that a fixed scanning duration can be avoided by ending the NDP after discovering the required number of devices. Our proposal demonstrates a reduction in energy consumption through intensive simulations and a robust validation methodology. Furthermore, real-world experiments indicate that our approach can achieve up to 50% energy savings compared to a 1-second scan when only one core is used during the NDP.

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an Inria International Program

10.2.1 Visits of international scientists

10.2.2 Visits to international teams

10.3.1 Horizon Europe

10.3.2 Other european programs/initiatives

GoodFloow

Participants: Damien Wohwe Sambo, Nathalie Mitton.

• Title:
  ADEME GoodFloow Project
• Duration:
  October 2021 - June 2024
• Coordinator:
  GoodFloow
• Inria contact:
  Nathalie Mitton
• Summary:
  The goal of this project, funded by ADEME, is to design a very energy efficient node to manage reusable packaging in a more sustainable way by combining enhanced IA techniques, wake up radio and multi MAC layers.

AutonomousPack

Participants: Khalil Ben Kalboussi, Carol Habib, Nathalie Mitton.

• Title:
  ADEME AutonomousPack Project
• Duration:
  September 2023 - August 2026
• Coordinator:
  GoodFloow
• Inria contact:
  Nathalie Mitton
• Inria participants:
  Carol Habib , Nathalie Mitton
• Summary:
  The goal of the AUTONOMOUS PACK project is to push forward the achievements of the GoodFloow project by design a very energy efficient node to manage reusable packaging in a more sustainable way by combining enhanced IA techniques, wake up radio and multi MAC layers.

ANR NeMIoT

Participants: Valeria Loscri, Lucien Dikla Ngueleo.

• Title:
  Detection and geolocation of an illegitimate electromagnetic source with AI
• Duration:
  Jan. 2024 - Dec. 2026
• Coordinator:
  Univ. Lyon 1
• Inria contact:
  Valeria Loscri
• Summary:
  NEMIoT aims at (i) designing a solid framework to model, analyse and forecast the actual behaviour of IoT devices when placed in an actual IP network infrastructure as well as their impact on the hosting network infrastructure itself and (ii) developing original cross-layer solutions to finely and quickly detect and/or mitigate potential anomalies resulting from the introduction of IoT devices. To do that, NEMIoT will provide the necessary analytical methods and tools, establish a step-by-step methodology thought to be automated, and demonstrate their efficiency on testbeds with real-life IoT devices.

ANR DEPOSIA

Participants: Valeria Loscri.

• Title:
  Detection and geolocation of an illegitimate electromagnetic source with AI
• Duration:
  October 2021 - September 2024
• Coordinator:
  Virginie Deniau
• Inria contact:
  Valeria Loscri
• Summary:
  DEPOSIA focuses on the detection and geolocation of various radio frequency signal sources in order to thwart attacks on connected systems and infrastructures. The sources considered are elements which by their characteristics or their position, present an illicit character and which threaten the people security or the infrastructures. For outdoor cases, we consider drones flying over forbidden areas, telecommunication jammers, spoofing signal transmitters or wireless connected sensors used to introduce false data in monitoring platforms. For indoor cases, we also consider jamming or spoofing sources that can cause denial of service within networks or infrastructures, or fake access points that aim to carry out man-in-the-middle attacks to intercept information.

SIRCAPASS, BPI

Participants: Nathalie Mitton.

• Title:
  Monitoring road infrastructure using passive sensors
• Duration:
  June 2024 - June 2028
• Coordinator:
  SilMach
• Summary:
  This project aims to provide an operational response to the challenges associated with the preventive monitoring of bridges and the planning of their maintenance. SIRCAPASS will propose an innovation that breaks with current practices and concepts, based on the use of energy-free sensors. This project contributes to the first research focus.

ROAD-AI, common DEFI Inria and Cerema

Participants: Nathalie Mitton.

• Title:
  Routes et ouvrages d'art Diversiformes, Augmentés et intégrés
• Duration:
  July 2021 - June 2025
• Coordinator:
  Nathalie Mitton
• Summary:
  Integrated management of infrastructure assets is an approach which aims at reconciling long-term issues with short-term constraints and operational logic. The main objective is to enjoy more sustainable, safer and more resilient transport infrastructure through effective, efficient and responsible management. To achieve this, CEREMA and Inria are joining forces in this Inria Challenge (DEFI) which main goals are to overcome scientific and technical barriers that lead to the asset management of tomorrow for the benefit of road operators: (i) build a “digital twin” of the road and its environment at the scale of a complete network; (ii) define “laws” of pavement behavior; (iii) instrument system-wide bridges and tunnels and use the data in real time; (iv) define methods for strategic planning of investments and maintenance.

PEPR Network of the Future - Just Enough Network

Participants: Nathalie Mitton, Emile Egreteau-Druet.

• Title:
  PEPR NoF JEN
• Duration:
  2023 - 2028
• Inria contact:
  Nathalie Mitton
• Summary:
  Jointly with the Inria AVALON team and the AIVANCITY school, Inria FUN investigates the full life cycle of IoT-based 5G Solutions for Smart Agriculture in order to design holistic system for data collection in agriculture that take account of the full environmental footprint.

PEPR Network of the Future - FITNESS

Participants: Nathalie Mitton, Valeria Loscri, Aymen Salah Eddine Bouferroum, Marwa Slimene, Amira Mourad.

• Title:
  PEPR NoF FITNESS
• Duration:
  2023 - 2028
• Inria contact:
  Nathalie Mitton and Valeria Loscri
• Summary:
  FUN collaborates in WP2 and WP8 of this project. In WP2, Industry 4.0, we consider Industrial internet of Things (IIoT) and invetigate the security aspects related to the co-existence and interaction of different wireless communication technologies. In WP2, we investigate a whole hierarchical architecture, managing in an effective, energy-ware way trust model between resource-constrained and heterogeneous nodes. In WP3, we design a Collaborative Security and Remote Audit of V2X Communications, namely SCAR2X, aiming at a global security solution.

PEPR MobiDec

Participants: Nathalie Mitton.

• Title:
  PEPR Mobidec DataFactory
• Duration:
  2023 - 2026
• Inria contact:
  Nathalie Mitton
• Summary:
  In collaboration with Inria TRIBE and COATI teams, we build an open source easy-to-use software tool able to collect and generate data traffic over different wireless network technologies and to infer some mobility characteristics from it.

PEPR Cloud

Participants: Nathalie Mitton.

• Title:
  PEPR Cloud PC SILECS
• Duration:
  2024 - 2031
• Inria contact:
  Nathalie Mitton
• Summary:
  This project aims to build the research infrastructure to allow reproducible research in the full cIoT/edge/cloud continuum and contributes to the set up and deployment of SLICES-RI.

STIMULE CORTESE

Participants: Valeria Loscri, Selma Yahia.

• Title:
  CORTESE: Intelligent CO-existence of Communication Wireless Technologies for Secure and Intelligent applications
• Duration:
  Jan. 20233 - Dec. 2025
• Inria contact:
  Valeria Loscri
• Summary:
  This project aims at the coexistence of different technologies of wireless communication, in the vehicular context by investigating methods based on a sustainable Artificial Intelligence to select the most relevant technology to improve performance, reliability to guarantee increased robustness against cyber attacks. Given the high dynamics of the environment, learning approaches developed must be able to respond in real time with a particular focus on durability and security of wireless networks.

11.1.1 Scientific events: organisation

11.1.2 Journal

11.1.3 Invited talks

• Valeria Loscri was invited speaker for the CTO Award Ceremony organised by CRIP in November 2024.
• Valeria Loscri was invited speaker at the 5G/6G Industrial Day in Stockholm organised by RISE in October 2024.
• Valeria Loscri was invited speaker at the Joint 6G-PHYSEC & INTERACT Workshop on 6G Technologies and PHY Layer Security.
• Valeria Loscri was invited at the RoundTable of Informatic Security and Social and Human Science organized by the GDR Sécurité Informatique and GDR Internet, IA et Societé.

11.1.4 Scientific expertise

• Valeria Loscri has been appointed as FWO chair for Fundamental Research Panel (2024). Valeria Loscri was FWO expert panel member for the PhD fellowship-Fundamental Research and for the Postdoc fellowship-Fundamental Research.
• Valeria Loscri has been appointed as evaluator expert of European Union COST Action.
• Nathalie Mitton has been appointed as scientific expert to evaluate projects submitted to ANR, South Africa's National Research Foundation (NRF), NSERC (Canada) and NSC (Poland), Bourses L'Oréal FRANCE, Polish National Science Centre and BPI.
• Nathalie Mitton is an external expert of scientific board for INRAE, IRIT lab and ESISAR.

11.2.1 Teaching

• Master: Valeria Loscri, Objets Communicants, 24h (Mineure Habitat Intelligent), Ecole des Mines de Douai, France
• Master: Nathalie Mitton, Wireless networks, 16h eqTD (Master TC), Université de Lille, France
• Master: Carol Habib, Wireless sensor networks, 16h eqTD (Master IdO), Université de Lille, France
• Master: Carol Habib, Smart objects, 10h CM + 12h TP, Ecole Centrale de Lille, France
• Master: Carol Habib, Industrial Internet of Things, 10h CM, Ecole Centrale de Lille, France

11.2.2 Supervision

• PhD defended:
  • Jana Koteich, Context aware opportunistic forwarding strategy, Université de Lille, 2021-2024, Nathalie Mitton 26
• PhD in progress:
  • Aymen Bouferroum, Vulnerability detection, trust and authentication methods applied to multi-technology communication in Industrial IoT (IIoT), Université de Lille, 2023-2026, Valeria Loscri
  • Selina Cheggour, Cell-free approaches in wireless networks, Université de Lille, 2023-2026, Valeria Loscri
  • Marwa Slimene, Blockchain-based security and audit for IoT and V2X communications, Université de Lille, 2023-2026, Nathalie Mitton
  • Jiali Xu, Anomaly and attack detection in intelligent, deep systems with heterogeneous, reprogrammable nodes, Université de Lille, 2023-2026, Valeria Loscri
  • Hazem Chaabi, Adaptive deployment of a distributed wireless monitoring network and edge services using a fleet of wireless robots, Université de Lille, 2022-2025, Nathalie Mitton
  • Ildi Alla, Monitoring for detection and localisation of cyber attacks in wireless networks, Université de Lille, 2022-2025, Valeria Loscri
  • Lucien Dikla Ngueleo, Attack and anomaly detection in IoT, Université de Lille, 2024-2027, Valeria Loscri and Kevin Jiokleng
  • Emile Egreteau-Druet, Analyzing full life cycle of IoT based 5G solutions for smart agriculture, ENS Lyon, 2024-2027, Nathalie Mitton and Laurent Lefevre, Inria AVALON
  • Tatiana Al Jamous, Smart Grid management for university campus, Université de Lille, 2024-2027, Nathalie Mitton, Carol Habib and Jad Nassar (Antonine Univ., Lebanon)

11.2.3 Juries

• PhD committees:
  • Valeria Loscri is/was member of the following PhD thesis committees:Toggle sub-subsection view
    • Maugan de Murcia, University of Poitiers, chair
    • De Biasio Alvise, University of Padua
    • Montagna Andrea, University of Padua
    • Pardini Susanna, University of Padua
    • Tricomi Pierpaolo, University of Padua
    • Visintin Alessandro, University of Padua, reviewer
    • Yuan Ying, University of Padua
    • Waleed Bin Qaim, Tampere University, opponent
    • Eros Innocenti, Guglielmo Marconi University, reviewer
    • Runbo Su, University of Lorraine, reviewer
    • Alix Jeanerot, University of Lyon, INSA, reviewer
    • Aurélien Chambon, University Gustave Eiffel, reviewer
    • Francesco Paolo Saccomanno, University of Calabria, reviewer
    • Amani Aou Rida, University of Strasbourg
  • Nathalie Mitton is/was member of the following PhD thesis committees:Toggle sub-subsection view
    • Pierre Laclau, UTC, reviewer
    • Evelyne Akopyan, ENSEEITH, reviewer
    • Samuel Pelissier, INSA Lyon, reviewer
    • Fadhila Tlili, UTT
    • Aimé Cédric MUHOZA, Université Clermont Auvergne
    • Alamy Toure, UPHF, chair
    • Lucas Magnana, INSA Lyon, reviewer
    • Ayush Sinha, IIIT Allahabad, India, reviewer
• HDR committees:
  • Valeria Loscri was a member of the following HDR committe:Toggle sub-subsection view
    • Stéphanie Sahuguede, University of Limoges, reviewer
  • Nathalie Mitton was a member of the following HDR committees:Toggle sub-subsection view
    • Rahim Kacimi, Univ. Toulouse
    • Walid Bechkit, INSA Lyon, reviewer
• Research selection committees:
  • Valeria Loscri is/was member of the following selection committees:Toggle sub-subsection view
    • Associate Professors: LORIA and University Côte d'Azur
  • Nathalie Mitton was member of the following selection committees:Toggle sub-subsection view
    • Inria researcher: vice-chair of the junior researcher committee (CR) for Inria Lille and member of INRAE junior researcher committee (CR) and of Inria Senior researcher committee (DR2)
    • Professor: Sorbonne Université and Université de Rennes.

International journals

• 6 articleA.Aroosa Hameed, J.John Violos, N.Nina Santi, A.Aris Leivadeas and N.Nathalie Mitton. FeD-TST: Federated Temporal Sparse Transformers for QoS prediction in Dynamic IoT Networks.IEEE Transactions on Network and Service ManagementNovember 2024HALDOIback to text
• 7 articleV.Valeria Loscri and M.Mauro Biagi. LIBERO: LIght Bias as effective countermeasure against EavesdROpper attacks.IEEE Transactions on CommunicationsJune 2024HALback to text
• 8 articleM.Meysam Mayahi, V.Valeria Loscrí and A. M.Anna Maria Vegni. INVISIBLE2.0: an Enhanced Interference-based Handover Technique for Visible Light Communications in Vehicular Networks.Computer NetworksMarch 2024, 110280HALDOIback to text
• 9 articleN.Nathalie Mitton, Y.Yasir Saleem, V.Valeria Loscri and C.Christophe Bureau. Adaptive HELLO Protocol for Vehicular Networks.ITU Journal on Future and Evolving Technologies2024HALback to text

Invited conferences

• 10 inproceedingsC.Claudia Leoni, A. M.Anna Maria Vegni, V.Valeria Loscri and A.Abderrahim Benslimane. Reputation-based Trustworthiness Degree in Interference-variable Vehicular Networks.1st International Workshop on Trustworthy and Explainable Artificial Intelligence for Networks (TX4Nets) 2024, IFIP NetworkingThessaloniki, GreeceJune 2024HALback to text

International peer-reviewed conferences

• 11 inproceedingsI.Ildi Alla, S.Selma Yahia, V.Valeria Loscri and H.Hossien Eldeeb. Robust Device Authentication in Multi-Node Networks: ML-Assisted Hybrid PLA Exploiting Hardware Impairments.Annual Computer Security Applications Conference (ACSAC)Waikiki, Hawaii, USA, United StatesDecember 2024HALback to text
• 12 inproceedingsA.Adriana Arteaga, N.Nikos Filinis, L.Lei Fu, C.Carol Habib, L.Leonardo Militano, D.Dimitris Spatharakis, A.Anastasios Zafeiropoulos, T. M.Thomas M Bohnert, N.Nathalie Mitton and S.Symeon Papavassiliou. Virtual Objects for Robots and Sensor Nodes in Distributed Applications over the Cloud Continuum.International Workshop on Distributed Intelligent Systems (DistInSys)Paris, FranceJune 2024HALback to textback to text
• 13 inproceedingsA.Adriana Arteaga-Arce and N.Nathalie Mitton. A probabilistic routing protocol for intermittently connected networks in the rural scenarios.International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)Paris, FranceOctober 2024HALback to text
• 14 inproceedingsA.Adriana Arteaga-Arce, A.Alexandre Veremme, C.Carol Habib and N.Nathalie Mitton. Demo: Virtualized Wireless Sensor Networks for Distributed Applications over the Cloud Continuum.7th Conference on Cloud and Internet of Things 2024 (CIoT’24)Montreal, CanadaOctober 2024HALback to textback to text
• 15 inproceedingsM.Mariem Belhor, A.Anne Savard, A.Anthony Fleury, P.Patrick Sondi and V.Valeria Loscri. Enhanced RF-based 3D UAV Outdoor Geolocation: from Trilateration to Machine Learning Approaches.2024 IEEE 27th International Symposium on Real-Time Distributed Computing (ISORC)Tunis, FranceIEEEMay 2024, 1-8HALDOIback to text
• 16 inproceedingsA.Antonio Costanzo, V.Virginie Deniau and V.Valeria Loscri. Effects of intentional RF interference on Optical Wireless Communication Systems.International Symposium and Exhibition on Electromagnetic CompatibilityBruges, BelgiumSeptember 2024HALback to text
• 17 inproceedingsJ.Jana Koteich and N.Nathalie Mitton. Dataset Collection of Multi-Communication Technologies Monitored in Different Mobility Contexts.The 20th International Wireless Communications & Mobile Computing Conference (IWCMC)Ayia Napa, CyprusMay 2024HALback to textback to textback to text
• 18 inproceedingsJ.Jana Koteich and N.Nathalie Mitton. Radio Beacon Base Context Identification.CoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de CommunicationCoRes 2024: 9èmes Rencontres Francophones sur la Conception de Protocoles, l'Évaluation de Performance et l'Expérimentation des Réseaux de CommunicationSaint-Briac-sur-Mer, FranceMay 2024HALback to text
• 19 inproceedingsJ.Jana Koteich, N.Nathalie Mitton and R.Riaan Wolhuter. Mobility Context Aware Routing Protocol in DTN.39th International Conference on Information Networking (ICOIN)Chang Mai, ThailandJanuary 2025HALback to textback to text
• 20 inproceedingsJ.Joseph Mcdonnell, C.Christian Salim and N.Nathalie Mitton. Data Reduction in multi-hop collection of agriculture data.International Workshop on Selected Topics in Wireless and Mobile computing (STWiMob)Paris, FranceOctober 2024HALback to text
• 21 inproceedingsN.Nassima Merabtine, V.Valeria Loscri, D.Djamel Djenouri and S.Shahid Latif. A Novel Hybrid Framework for Realistic UAV Detection using a Mixed RF Signal Database.IEEE Future Networks - FNWFFNWF 2024 - IEEE Future Networks World ForumDubai, United Arab EmiratesJanuary 2025HALback to text
• 22 inproceedingsY.Yasir Saleem, N.Nathalie Mitton and V.Valeria Loscri. Analysis of Common Required Metrics for Vehicular Networks.WINCOM 2024 - International Conference on Wireless Networks and Mobile CommunicationsLeeds, United KingdomJuly 2024HALback to text
• 23 inproceedingsD. W.Damien Wohwe Sambo, N.Nathalie Mitton, R.Robin Delafaite, L.Laurent Clavier and R.Rédha Kassi. A new Dynamic Multicored Neighbors Discovery approach in BLE for Low Power Systems.International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)Paris, FranceOctober 2024HALback to text
• 24 inproceedingsS.Selma Yahia, S.Sylia Mekhmoukh Taleb, V.Valeria Loscri, A. A.Amylia Ait Saadi, T.Tu Dac Ho, V. N.Van Nhan Vo, H.Hossien Eldeeb and S.Sami Muhaidat. Dynamic 3D UAV Placement Optimization: Improved Bonobo Optimizer for Enhanced Coverage and Communication.IEEE International Symposium on Personal, Indoor and Mobile Radio CommunicationsValencia, SpainSeptember 2024HALback to text

Scientific books

• 25 bookV.Valeria Loscri, L.Luca Chiaraviglio and A. M.Anna Maria Vegni, eds. The Road towards 6G: Opportunities, Challenges, and Applications: A Comprehensive View of The Enabling Technologies.Springer Cham2024, 222HALDOIback to text

Doctoral dissertations and habilitation theses

• 26 thesisJ.Jana Koteich. Novel context aware opportunistic data forwarding strategy in wireless networks.Université de LilleSeptember 2024HALback to textback to text