Yulliwas, Ph.D. student in the ROC team at the CEDRIC laboratory of CNAM, will defend his Ph.D. thesis on December 18, 2023, at 2 p.m, in the amphitheater Fabry Pérot at CNAM, 292 rue Saint-Martin, 75003 Paris.
The main objective of his research is to explore the application of homomorphic encryption in machine learning for IoT/Cloud, a crucial area for the development of future technologies. The goal is to propose innovative solutions that enhance data security in IoT/Cloud environments using machine learning.
To better organize this event, participants wishing to attend the Yulliwas’s Ph.D. defense are pleased to confirm their attendance by registering on the following Eventbrite link:
Yulliwas’s publications
3 documents
Conference papers
- Yulliwas Ameur, Samia Bouzefrane, Thinh Le Vinh. Handling security issues by using homomorphic encryption in multi-cloud environment. The 14th International Conference on Ambient Systems, Networks and Technologies (ANT), Mar 2023, Leuven, Belgium. ⟨hal-03933238⟩
- 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), Sep 2022, Paris, France. pp.142-154, ⟨10.1007/978-3-031-13945-1_11⟩. ⟨hal-03933277⟩
Book sections
- Yulliwas Ameur, Samia Bouzefrane, Vincent Audigier. Application of Homomorphic Encryption in Machine Learning. Kevin Daimi, Abeer Alsadoon, Cathryn Peoples, Nour El Madhoun Editors. Emerging Trends in Cybersecurity Applications, Springer International Publishing, pp.391-410, 2023, 978-3-031-09639-6. ⟨10.1007/978-3-031-09640-2_18⟩. ⟨hal-03933309⟩
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Ph.D. defense: Yulliwas AMEUR – December 18, 2023
