smart.lab.tunisia@gmail.com +216 71 588 443
Connexion

Meriam Jemel

Informations générales

Meriam Jemel
Grade

Maître Assistant

Biographie courte

I obtained a PhD in Computer Science in 2018 from the National School for Computer Science (ENSI), Tunis, with High Honors. Before that, I earned a Master’s degree in Computer Science from the Faculty of Economics and Management of Sfax in 2008, and an Engineering Degree in Computer Science from the National Engineering School of Sfax in 2006, both with the distinction Very Good. I also completed my preparatory studies in Mathematics and Physics at the Preparatory Institute for Engineering Studies of Sfax in 2003, after receiving my Mathematics Baccalaureate in 2001. Since 2022, I have been working as an Assistant Professor at the Higher Institute of Management of Tunis (ISG). Over the course of my academic career, I have published several research articles in peer-reviewed journals and international conferences.

Équipes

Axes de recherche

Artificial Intelligence
Deep Learning
Computer Science
Health care
Machine Learning
Multi Agent System

Publications

  • 2025
    Ali Abdelghafour Bejaoui, Meriam Jemel, Nadia Ben Azzouna

    Explainable AI Planning:literature review

    Automated planning systems have become indispensable tools in a wide range of applications, from robotics and healthcare to logistics and autonomous systems. However, as these systems grow in complexity, their decision-making processes often become opaque, 2025

    Résumé

    Explainable AI Planning (XAIP) is a pivotal research
    area focused on enhancing the transparency, interpretability,
    and trustworthiness of automated planning systems. This
    paper provides a comprehensive review of XAIP, emphasizing key
    techniques for plan explanation, such as contrastive explanations,
    hierarchical decomposition, and argumentative reasoning frameworks.
    We explore the critical role of argumentation in justifying
    planning decisions and address the challenges of replanning in
    dynamic and uncertain environments, particularly in high-stakes
    domains like healthcare, autonomous systems, and logistics.
    Additionally, we discuss the ethical and practical implications
    of deploying XAIP, highlighting the importance of human-AI
    collaboration, regulatory compliance, and uncertainty handling.
    By examining these aspects, this paper aims to provide a detailed
    understanding of how XAIP can improve the transparency,
    interpretability, and usability of AI planning systems across
    various domains.

  • Meriam Jemel, Alia Maaloul, Nadia Ben Azzouna

    XAI based feature selection for gestational diabetes Mellitus prediction

    CoDIT 2024: 1939-1944, 2024

    Résumé

    Gestational Diabetes Mellitus (GDM) is a type of diabetes that develops during pregnancy. It is important for pregnant women to monitor their blood sugar levels regularly and follow a healthy diet. However, early intervention can greatly reduce risk of this type of diabetes. Machine Learning and Deep Learning techniques are utilized to predict this risk based on an individual's symptoms, lifestyle, and medical history. By identifying key features such as age, insulin, body mass index, and glucose levels, machine learning models such as Random Forest and XGBoost are used in this research work to classify patients at risk of a gestational diabetes. In addition, we propose an explainable feature selection approach to improve the accuracy of machine learning models for GDM prediction. This method involves iteratively eliminating features that exhibit a negative contribution as determined by the SHAP (Shapley Additive explanations) feature attribution explanations for the model’s predictions.

  • Hasanain F. Hashim, Meriam Jemel, Nadia Ben Azzouna

    Dynamic Threasholding GA-based ECG feature selection in cardiovascular disease diagnosis

    Iraqi Journal for Computers and Informatics. Vol. 49 No. 2, 2023, 2023

    Résumé

    Electrocardiogram (ECG) data are usually used to diagnose cardiovascular disease (CVD) with the help of a revolutionary algorithm. Feature selection is a crucial step in the development of accurate and reliable diagnostic models for CVDs. This research introduces the dynamic threshold genetic algorithm (DTGA) algorithm, a type of genetic algorithm that is used for optimization problems and discusses its use in the context of feature selection. This research reveals the success of DTGA in selecting relevant ECG features that ultimately enhance accuracy and efficiency in the diagnosis of CVD. This work also proves the benefits of employing DTGA in clinical practice, including a reduction in the amount of time spent diagnosing patients and an increase in the precision with which individuals who are at risk of CVD can be identified.

    Hasanain F. Hashim, Meriam Jemel, Nadia Ben Azzouna

    Optimization of Multiple Scaling Factors for ECG Steganography Using Dynamic Thresholding GA

    International Journal of Intelligent Systems and Applications in Engineering, 11(4), 01–10, 2023, 2023

    Résumé

    Protecting patient data has become a top priority for healthcare providers in the digital age. ECG steganography is a technique for concealing electrocardiogram (ECG) signals during Internet transmission along with other medical data. This strategy aims to recover all embedded patient data while minimizing degradation of the cover signal caused by embedding. Quantization techniques make it possible to include patient information in the ECG signal, and it has been discovered that multiple scaling factors (MSFs) provide a superior trade-off than uniform single scaling factors. In this paper, we present a novel contribution to the field: a discrete wavelet transforms and singular value decomposition-based dynamic Thresholding GA (DTGA)-based ECG steganography scheme. Using the MITIH database, we demonstrate the efficacy of this method, and our findings corroborate that DTGA significantly improves data security.

  • Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira

    RPMInterwork: A multi-agent approach for planning task-role assignments in inter-organizational workflow

    the Journal of Enterprise Information Systems, Taylor & Francis, 2019, 2019

    Résumé

    Workflow management is a core component of modern Enterprise Information Systems (EISs) infrastructure that automates the execution of critical business processes. One of the particular interests of the security community is how to ensure the completion of the workflow execution in the presence of authorisation constraints. These constraints present some restrictions on the users or the roles that are authorised to execute the workflow tasks. The goal is to enforce the legal assignments of access privileges to the executors of the workflow tasks. Despite the variety of approaches proposed in this context, an approach dedicated to the inter-organisational workflows is still missing. In this paper, we take a step towards this goal by proposing a multi-agent-based model, named RPMInter-Work (task-Role assignment Planning Model for Inter-organisational Workflow). Our approach aims to perform the planning of the task-role assignments in inter-organisational workflow in presence of authorisation constraints that are related to task-role assignments. In our research work, this planning problem is formulated as a DisCSP (Distributed Constraint Satisfaction Problem). Our proposed contribution is based on the requirements of inter-organisational workflows, in particular, the autonomy of the participating organisations and the respect of their privacy. A prototype of RPMInter-Work is implemented using JADE (Java Agent DEvelopment) platform and some evaluation results of this prototype are exposed in this paper.

  • Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira

    ECA rules for controlling authorisation plan to satisfy dynamic constraints.

    . In Proceedings of the 13th Annual Conference on Privacy, Security and Trust (PST 2015), November 26-28 2015, Aksaray, Turkey, pages 133-138, IEEE Computer Society, 2015, 2015

    Résumé

    The workflow satisfiability problem has been studied by researchers in the security community using various approaches. The goal is to ensure that the user/role is authorised to execute the current task and that this permission doesn't prevent the remaining tasks in the workflow instance to be achieved. A valid authorisation plan consists in affecting authorised roles and users to workflow tasks in such a way that all the authorisation constraints are satisfied. Previous works are interested in workflow satisfiability problem by considering intra-instance constraints, i.e. constraints which are applied to a single instance. However, inter-instance constraints which are specified over multiple workflow instances are also paramount to mitigate the security frauds. In this paper, we present how ECA (Event-Condition-Action) paradigm and agent technology can be exploited to control authorisation plan in order to meet dynamic constraints, namely intra-instance and inter-instance constraints. We present a specification of a set of ECA rules that aim to achieve this goal. A prototype implementation of our proposed approach is also provided in this paper.

  • Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira

    A novel approach for dynamic authorisation planning in constrained workow systems

    In the 6th International Conference on Security of Information and Networks (SIN 2013), July 21-23 2013, Izmir, Turkey, pages 388-391, ACM, 2013., 2013

    Résumé

    In this paper we present a specification of the most common static and dynamic workflow authorisation constraints. We propose an authorisation model that includes a planning phase, an execution phase and an adjustment phase. In addition, we focus on how the problems of role-task assignment and user-task assignment are respectively translated into CSP (Constraint Satisfaction Problem) and DyCSP (Dynamic constraint Satisfaction Problem) and solved using the explanation concept. In case of an inconsistent assignment problem, we propose to restore problem consistency based upon inconsistency explanation.

    Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira

    Towards a dynamic authorisation planning satisfying intra-instance and inter-instance constraints

    In the 6th International Conference on Security of Information and Networks (SIN 2013), July 21-23 2013, Izmir, Turkey, pages 440-443, ACM, 2013., 2013

    Résumé

    Role-Based Access Control (RBAC) model has been developed as an alternative to traditional approaches to handle access control in workflow systems. Accordingly, authorisation constraints must be defined to enforce the legal assignment of access privileges to roles and roles to users. The authorisation planning ensures that there is at least one way to complete the workflow instance without breaching any of the authorisation constraints. Authorisation planning with considering intra-instance constraints has been discussed in the research literature. However, the inter-instance constraints also need to be considered to mitigate the security fraud. In this paper, a novel authorisation system that incorporates intra-instance and inter-instance constraints is proposed. It includes the planning phase, the execution phase, and the adjustment phase. It is in charge of generating user/role assignment plans, verifying them and eventually updating them to take into account the dynamic (intra-instance and inter-instance) constraints. Besides, grounded upon agent technology and publish-subscribe communication model, a mechanism for the consideration of dynamic constraints (intra-instance and inter-intance) to generate valid assignment plans is demonstrated.

  • Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira

    Towards a scalable and dynamic access control system for web services

    In Proceedings of the 8th International conference on Web Information Systems and Technologies(WEBIST 2012), April 18 -21 2012,Porto, Portugal, pages 161-166, 2012., 2012

    Résumé

    Web services are vulnerable to different types of security attacks. The problem of secure access to web-based
    applications is becoming increasingly complex. Management complexity arises because of the scalability
    considerations such as the large number of web services users and their invocations and the fact that the
    access control system should take into account the context. In this paper we describe the architecture of
    our TDRBAC (Trust and Dynamic Role Based Access Control) model which is implemented using agent
    technology. In fact, this technology fulfills several requirements of web service’s access control by providing
    both context awareness and scalability. In order to verify the scalability of the proposed solution, we expose
    some experimental results from a prototype implemented using JADE (Java Agent DEvelopment) platform.
    The performance tests show that our TDRBAC multi-agent based system meets the scaling requirements of
    large distributed services.

  • Meriam Jemel, Nadia Ben Azzouna, Khaled Ghedira

    Towards a dynamic access control model for e-government web services

    In Proceedings of the 2010 IEEE Asia-Pacific Services Computing Conference (APSCC'10), December 6-10 2010, Hangzhou, China, pages 433-440, IEEE Computer Society, 2010

    Résumé

    The need of interoperable e-government services is addressed through the use of web services where sensitive services need to be granted to only authorized subjects from different organizations. In this paper, we propose a Trust and Dynamic Role Based Access Control model (TDRBAC) which deals with the specific requirements of e-government services. It effectively enhances the access control level since it is based on the trust level notion. The trust level evaluation is based on contextual attributes to assign to user role the appropriate view during the active session. The TDRBAC model is sensitive to the internal or external arisen events and it incorporates them in the access decision which makes it suitable for e-government dynamic environment.