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Hamdi Ouechtati

Informations générales

Hamdi Ouechtati
Grade

Assistant

Biographie courte

Hamdi Ouechtati est Docteur en Informatique de Gestion, diplômé de l’Institut Supérieur de Gestion de Tunis (ISG Tunis) en 2021. Ses travaux portent sur le contrôle d’accès adaptatif et la sécurité dans l’Internet des Objets, au sein du laboratoire SMART-LAB. Fort d’une expérience d’enseignement dans plusieurs établissements supérieurs tunisiens, il a dispensé des cours variés allant de l’algorithmique à l’intelligence artificielle et aux systèmes d’exploitation. Ses recherches et publications s’articulent autour de la sécurité, de l’intelligence artificielle et de l’optimisation, avec une attention particulière aux modèles de confiance dans les environnements IoT.

Axes de recherche

Sécurité des systèmes d’information et IoT
Confiance et recommandation
Big Data

Publications

  • 2025
    Hamdi Ouechtati, Nadia Ben Azzouna

    Multi-objective clustering and dynamic multi-hop routing in an IoT network based on Pareto optimality

    Papier conf, 2025

    Résumé

    Routing is essential in computer networks as it
    directly impacts performance metrics such as throughput and
    transmission delay. Particularly in an Internet of Things (IoT)
    network where the nodes are limited in energy (battery power)
    and the radio component is high energy-intensive. We are always
    looking to optimise this procedure in order to increase the network
    lifetime. In this work, we present a multi-objective, multihop
    routing solution that extends network lifetime while balancing
    multiple objectives, such as energy consumption, delay, and
    reliability. Our solution was compared with other approaches,
    such as Energy Optimization Routing (EOR) and Multi-Objective
    Optimization Routing (MOWR) based on the Weighted Sum
    technique, demonstrating significant improvements.

    Nadia Ben Azzouna, Hamdi Ouechtati

    Multi-Objective Clustering and Reinforcement-based Routing in IoT Networks

    Papier journal, 2025

    Résumé

    The rapid development of devices on the Internet of Things
    (IoT) and the diversity of their applications have made them
    ubiquitous. However, deploying these devices in large-scale
    networks presents several challenges, including limited energy
    capacity, security concerns, unreliable links, and transmission
    delays. This paper, proposes a multi-objective optimization
    approach for wireless IoT networks based on machine learning
    techniques. Specifically, a clustering scheme is developd by
    using an improved k-means algorithm. This is combined
    with a dynamic routing strategy based on multi-objective
    Q-learning using parallel Q-tables. This approach leads to
    measurable gains in energy efficiency, transmission latency,
    and reliability. Compared to existing approaches in similar
    contexts, such as weighted sum, the proposed solution achieves
    significant improvements in overall network performance.

  • Hamdi Ouechtati, Nadia Ben Azzouna

    Towards an Adaptive Trust Management Model Based on ANFIS in the SIoT

    SECRYPT 2024: 710-715, 2024

    Résumé

    The integration of social networking concepts into the IoT environment has led to the Social Internet of Things
    (SIoT) paradigm which enables connected devices and people to facilitate information sharing, interact, and
    enable a variety of attractive applications. However, with this emerging paradigm, people feel cautious and
    wary. They worry about violating their privacy and revealing their data. Without trustworthy mechanisms to
    guarantee the reliability of user’s communications and interactions, the SIoT will not reach enough popularity
    to be considered as a cutting-edge technology. Accordingly, trust management becomes a major challenge
    to improve security and provide qualified services. Therefore, we overcome these issues through proposing
    an adaptive trust management model based on Adaptive Neuro-Fuzzy Inference System (ANFIS) in order to
    estimate the trust level of objects in the Social Internet of Things. We formalized and implemented a new trust
    management model built ANFIS, to analyze different trust parameters, estimate the trust level of objects and
    distinguish malicious behavior from benign behaviors. Experimentation made on a real data set proves the
    performance and the resilience of our trust management model.

  • Hamdi Ouechtati, Nadia Ben Azzouna, Lamjed Ben Said

    A fuzzy logic-based model for filtering dishonest recommendations in the Social Internet of Things

    Journal of Ambient Intelligence and Humanized Computing, 14(5), 6181-6200., 2023

    Résumé

    In the recent year, Internet of Things (IoT) has been adopted in several real-world applications such as smart transportation, smart city, retail, agriculture, smart factory, etc. to make human life more reliable. The integration of social networking concepts into the IoT led to the rise of a new paradigm: the Social Internet of Things (SIoT). In the SIoT environment, the objects are capable of establishing in an autonomous way many social relationships anywhere and anytime with other trusted objects. However, in such environment, objects may provide dishonest recommendations due to malicious reasons such as bad mouthing, ballot stuffing, random opinion, etc. In order to cater these challenges, we propose a new fuzzy logic-based model to filter dishonest recommendations and estimate their trust level based on (1) their values and sending time and the place coordinates and (2) the social relationship parameters of the recommenders. Results prove that our proposed approach is able to detect 100% of the fake Sybil attack and achieves 100% of Recognition Proportion, Sensitivity, Specificity, Accuracy and F1 score and gets 0% of False Negative and False Positive Proportions in presence of up to 90% dishonest recommendations.

  • Hamdi Ouechtati, Nadia Ben Azzouna, Lamjed Ben Said

    A fuzzy logic based trust-ABAC model for the Internet of Things

    In International Conference on Advanced Information Networking and Applications (pp. 1157-1168). Cham: Springer International Publishing., 2019

    Résumé

    The Internet of Things (IoT) integrates a large amount of everyday life devices from heterogeneous network environments, bringing a great challenge into security and reliability management. In order to cope with certain challenges posed by device capacity and the nature of IoT networks, a lightweight access control model is needed to resolve security and privacy issues. In this paper, we present Fuzzy logic based Trust-ABAC model, an access control model for the Internet of Things. Our model for the IoT is an improvement of our previous work Trust-ABAC by a new Fuzzy logic-based model in which we consider an evaluation of trust based on recommendations and social relationship that can deal effectively with certain types of malicious behavior that intend to mislead other nodes. Results prove the performance of the proposed model and its capabilities to detect the collision and singular attacks with high precision.

  • Hamdi Ouechtati, Nadia Ben Azzouna, Lamjed Ben Said

    Towards a self-adaptive access control middleware for the Internet of Things

    In 2018 International Conference on Information Networking (ICOIN) (pp. 545-550). IEEE., 2018

    Résumé

    In order to cope with certain challenges posed by IoT environment and device capacity, a Self-Adaptive access control model is needed to resolve security and privacy issues. The use of complex encryption algorithms is infeasible due to the volatile nature of IoT environment and pervasive devices with limited resources. In this paper, we propose an access control middleware for the Internet of Things. The latter is an extension of the ABAC model in order to take into account the subject behavior and the trust value in the decision making process. In this work, we introduce a dynamic adaptation process of access control rules based on the risk value, the policies and rule sets which can effectively improve the security of IoT applications and produce more efficient access control mechanisms for the Internet of Things.

  • Hamdi Ouechtati, Nadia Ben Azzouna

    Trust-abac towards an access control system for the internet of things

    In International Conference on Green, Pervasive, and Cloud Computing (pp. 75-89). Cham: Springer International Publishing., 2017

    Résumé

    In order to cope with certain challenges posed by device capacity and the nature of IoT networks, a lightweight access control model is needed to resolve security and privacy issues. The use of complex encryption algorithms is infeasible due to the volatile nature of IoT environment and pervasive devices with limited resources. In this paper, we present the Trust-ABAC, an access control model for the Internet of Things, in which a coupling between the access control based on attributes and the trust concept is done. We evaluated the performance of Trust-ABAC through an experiment based on a simulation. We used the OMNeT++ simulator to show the efficiency of our model in terms of power consumption, response time and the average number of messages generated by an access request. The obtained results of simulation prove the good scalability of our Trust-ABAC model.