Solayman Ayoubi’s CV
Presentation
I am a PhD candidate in Computer Science, specializing in the application of AI to network security. I am set to defend my thesis in April 2024, where I’ve developed innovative frameworks for evaluating and enhancing machine learning-based intrusion detection systems. My research has equipped me with deep expertise in machine learning and security solutions. I will be available to begin work in August 2024, aligning perfectly with the start of the cohort.
Education
Sorbonne University, PhD in Artificial Intelligence
- Jan 2022 to Apr 2025
- Focus: Machine Learning-based Intrusion Detection Systems (IDS)
University of Lyon, MSc in Artificial Intelligence
- Sep 2019 to Jun 2021
- Focus: Computer Science and Artificial Intelligence
- Coursework: Multi-agent Systems, Machine Learning, Data Mining, Data Visualization, Graph Theory, Internet of Things (IoT)
University of Lyon, BSc in Computer Science
- Sep 2016 to Jun 2019
- Focus: Computer Science and Mathematics
- Coursework: Object-Oriented, Functional, and Concurrent Programming, Multi-agent Systems, Machine Learning, Data Mining, Data Visualization, Graph Theory, IoT, Databases, Systems and Networks
Experience
LIP6, UMR 7606 Sorbonne Université, CNRS, Researcher in AI and Network Security (PhD Student)
- Jan 2022 to Apr 2025
- Paris, France
- Developed a framework for comprehensive evaluation and comparison of IDS models
- Expertise in supervised, unsupervised, and adversarial learning techniques for IDS security
- Researched model explainability and privacy attacks (e.g., membership inference, model extraction)
LIP6, UMR 7606 Sorbonne Université, CNRS, Researcher in AI and Network Security (Intern)
- Feb 2021 to Jul 2021
- Paris, France
- Survey of IDS assessment methodologies, metrics and datasets
- Design of a data-driven assessment approach
- Evaluation of the approach on some available IDS implementations
University of Lyon, Software Engineer (Intern)
- Jul 2020 to Dec 2020
- Lyon, France
- Deployment of the university’s mobile application on Android and iOS
- Improved reliability of existing services and interconnection with university services
Roverba CGS, DevOps Engineer (Intern)
- Apr 2019 to Sep 2019
- Lyon, France
- Detailed report and comparisons of FOSS ERP solutions
- Creation of a monitoring solution on network equipment and hyperconverged solutions
- Creation and deployment of virtual clusters
Publications
- 2022
- Fabien Charmet, Harry Chandra Tanuwidjadja, Solayman Ayoubi, Pierre-François Gimenez, Yufei Han and Houda Jmila, Gregory Blanc, Takeshi Takahashi, Zonghua Zhang
- Annals of Telecommunications
Data-Driven Evaluation of Intrusion Detectors: A Methodological Framework (10.1007/978-3-031-30122-3_9)
- 2023
- Solayman Ayoubi, Gregory Blanc, Houda Jmila, Thomas Silverston, Sébastien Tixeuil
- Foundations and Practice of Security
Demo: Towards Reproducible Evaluations of ML-Based IDS Using Data-Driven Approaches (10.1145/3658644.3691368)
- 2024
- Solayman Ayoubi, Gregory Blanc, Houda Jmila, Sébastien Tixeuil
- Conference on Computer and Communications Security (CCS ‘24)
- 2024
- Solayman Ayoubi, Gregory Blanc, Houda Jmila, Sébastien Tixeuil
- International Conference on Risks and Security of Internet and Systems
Projects
Deployment automation
- 2018
- Set of scripts allowing the deployment of different services
- Based on docker the scripts can also create a cluster to allow high availability of the deployed services
- Tools Used: Shell, Docker, Swarm
Billing Software
- 2019
- Freelance project for the company Roverba
- Development of a billing software for out-of-package communications related to VoIP telephone subscriptions
- Tools Used: Go, SQL, PHP, Javascript
Graph Convolutional Networks
- 2020
- State of the art analysis of GCNs (neural networks) usage for community detection
- Implementation of different methods from the scientific literature
- Tools Used: Python, Pytorch, NetworkX
Skills
- Languages: French (mother tongue), English (C1)
- Programming: C++, Java, SQL, NoSQL, JavaScript, Python, Go
- Machine-Learning: Numpy, Scikit-Learn, Pytorch, Keras, Tensorflow, MLlib, XAI
- Technologies: Power BI, Hadoop, Spark, CI/CD, Cloud, Linux, Shell, Networks, Docker
- Soft: Communication, Leadership, Orgranization, Punctuality