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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Posts
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portfolio
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publications
Secure and non-interactive k-NN classifier using symmetric fully homomorphic encryption
Published in Privacy in Statistical Databases (PSD 2022), Paris - Springer, 2022
A non-interactive privacy-preserving k-NN classifier built on symmetric fully homomorphic encryption.
Recommended citation: Yulliwas Ameur, Rezak Aziz, Vincent Audigier, Samia Bouzefrane. "Secure and non-interactive k-NN classifier using symmetric fully homomorphic encryption." Privacy in Statistical Databases (PSD 2022), Springer, 2022, pp. 142-154. https://hal.science/hal-03933277
Application of Homomorphic Encryption in Machine Learning
Published in In: Emerging Trends in Cybersecurity Applications (Springer), 2023
Survey and practical perspective on homomorphic encryption schemes and tools for privacy-preserving machine learning.
Recommended citation: Yulliwas Ameur, Samia Bouzefrane, Vincent Audigier. "Application of Homomorphic Encryption in Machine Learning." In: Emerging Trends in Cybersecurity Applications, Springer, 2023, pp. 391-410. https://hal.science/hal-03933309
Handling security issues by using homomorphic encryption in multi-cloud environment
Published in ANT 2023 - 14th International Conference on Ambient Systems, Networks and Technologies (Leuven, Belgium) - Procedia Computer Science, vol. 220, 2023
Securing outsourced computation across multiple cloud providers with homomorphic encryption.
Recommended citation: Yulliwas Ameur, Samia Bouzefrane, Le Vinh Thinh. "Handling security issues by using homomorphic encryption in multi-cloud environment." Procedia Computer Science, vol. 220, 2023, pp. 390-397. https://hal.science/hal-03933238
Exploring the Scope of Machine Learning using Homomorphic Encryption in IoT/Cloud (PhD thesis)
Published in HESAM Université - Conservatoire national des arts et métiers (Cnam), Paris, 2023
PhD thesis supervised by Samia Bouzefrane and Vincent Audigier - privacy-preserving ML (k-NN, k-means, differential privacy) over encrypted data in IoT/Cloud.
Recommended citation: Yulliwas Ameur. "Exploring the Scope of Machine Learning using Homomorphic Encryption in IoT/Cloud." PhD thesis, HESAM Universite / Cnam, defended December 18, 2023. https://theses.hal.science/tel-04587371
Enhancing privacy in VANETs through homomorphic encryption in machine learning applications
Published in ANT 2024 - 15th International Conference on Ambient Systems, Networks and Technologies (Hasselt, Belgium) - Procedia Computer Science, vol. 238, 2024
Privacy-preserving machine learning for vehicular ad-hoc networks using homomorphic encryption.
Recommended citation: Yulliwas Ameur, Samia Bouzefrane. "Enhancing privacy in VANETs through homomorphic encryption in machine learning applications." Procedia Computer Science, vol. 238, 2024, pp. 151-158. https://hal.science/hal-04676567
Developing Adaptive Homomorphic Encryption through Exploration of Differential Privacy
Published in Journal of Cyber Security and Mobility, 2024
Combining homomorphic encryption with differential privacy for adaptive privacy-preserving machine learning.
Recommended citation: Yulliwas Ameur, Samia Bouzefrane, Soumya Banerjee. "Developing Adaptive Homomorphic Encryption through Exploration of Differential Privacy." Journal of Cyber Security and Mobility, 2024, pp. 863-886. https://hal.science/hal-05330716
Advancing Blockchain Privacy: The Role of Homomorphic Encryption
Published in In: Intelligent Cybersecurity and Resilience for Critical Industries, 2025
Homomorphic encryption as a building block for privacy-preserving blockchain applications.
Recommended citation: Yulliwas Ameur, Ilhem Taberkane, Samia Bouzefrane. "Advancing Blockchain Privacy: The Role of Homomorphic Encryption." In: Intelligent Cybersecurity and Resilience for Critical Industries, 2025. https://hal.science/hal-05330722
Artificial Intelligence and Machine Learning: Revolutionizing Supply Chain Security
Published in In: Securing the Digital Supply Chain: Advances, Challenges, and Solutions (Springer, Cham), 2026
How AI/ML enable predictive analytics, anomaly detection and real-time decision-making for supply chain security.
Recommended citation: Yulliwas Ameur, Malek Kraiem. "Artificial Intelligence and Machine Learning: Revolutionizing Supply Chain Security." In: B. Hammi, N. El Madhoun (eds.), Securing the Digital Supply Chain, Signals and Communication Technology, Springer, Cham, 2026, pp. 183-201. https://doi.org/10.1007/978-3-032-11119-7_8
Secure k-means Clustering using Homomorphic Encryption
Published in ANT 2026 - 17th International Conference on Ambient Systems, Networks and Technologies (Istanbul, Türkiye), 2026
Privacy-preserving k-means clustering on homomorphically encrypted data. To appear in Procedia Computer Science.
Recommended citation: Yulliwas Ameur, Rezak Aziz, Vincent Audigier, Samia Bouzefrane. "Secure k-means Clustering using Homomorphic Encryption." ANT 2026, Istanbul, April 14-16, 2026. To appear in Procedia Computer Science.
GovSecLLM++ SECAI 2026 Artifact Package (dataset)
Published in Zenodo, 2026
Experimental artifacts of GovSecLLM++, a compliance-aware benchmark for security testing and governance evidence in LLM-based applications.
Recommended citation: Yulliwas Ameur, Samia Bouzefrane. "GovSecLLM++ SECAI 2026 Artifact Package." Zenodo, 2026. DOI: 10.5281/zenodo.20646702. https://doi.org/10.5281/zenodo.20646702
talks
Secure Machine Learning: applying homomorphic encryption in machine learning
Published:
Introduction to homomorphic encryption, overview of the most promising schemes and tools, and discussion of privacy-preserving machine learning (PPML) models.
Exploring the Scope of Machine Learning using Homomorphic Encryption in IoT/Cloud (PhD pitch)
Published:
Doctoral presentation during the trusted-AI & cybersecurity day organized by Systematic Paris-Region and Campus Cyber.
How homomorphic encryption revolutionizes machine learning by protecting data
Published:
Invited talk on the benefits of homomorphic encryption (HE) for cloud data security and privacy-preserving machine learning (PPML): HE schemes, current tools and practical applications.
teaching
Advanced cryptography: introduction to homomorphic encryption (2021-2022)
MSc seminar (4h), Cnam Paris, 2021
Fast-track introduction to homomorphic encryption within the advanced cryptography course.
ATER - Université Paris Panthéon-Assas (2023-2024)
Undergraduate (192h), Université Paris Panthéon-Assas, 2023
Teaching and research fellow (ATER): Python programming, VBA programming, databases, office tools.
Adjunct lecturer (2023-2024): Paris Cité, Paris 8, ESILV, Guardia, EPSI
Bachelor / MSc modules, Multiple institutions, 2023
Université Paris Cité: digital forensics & malware analysis, introduction to cryptography (M1). Université Paris 8: smart-card programming (M1). ESILV: information security, applied cryptography, security policies, forensics (B3). Guardia Cyber School: IS & cybersecurity fundamentals, intelligence analysis, web attacks, security & civil liberties, transition to post-quantum cryptography. EPSI: SIEM (M1).
Guest expert - ULB / University of Bamenda MSc in cybersecurity (2024)
MSc modules, Université Libre de Bruxelles - University of Bamenda, 2024
Specialized modules “Computing on Encrypted Data” and “Smart Card Security” within the academic cooperation between ULB and the University of Bamenda.
Cybersecurity courses - Efrei (since 2024)
Engineering cycle / MSc level, Efrei, Paris Panthéon-Assas Université, 2024
Head of the work-study “Networks & Security” major and educational lead of the Airbus cyber range.