All Outputs (2)

Towards securing machine learning models against membership inference attacks (2021)
Journal Article
Ben Hamida, S., Mrabet, H., Belguith, S., Alhomoud, A., & Jemai, A. (2022). Towards securing machine learning models against membership inference attacks. Computers, Materials & Continua, 70(3), 4897-4919. https://doi.org/10.32604/cmc.2022.019709

From fraud detection to speech recognition, including price prediction, Machine Learning (ML) applications are manifold and can significantly improve different areas. Nevertheless, machine learning models are vulnerable and are exposed to differen... Read More about Towards securing machine learning models against membership inference attacks.

On the security and privacy challenges of virtual assistants (2021)
Journal Article
Bolton, T., Dargahi, T., Belguith, S., Al-Rakhami, M., & Sodhro, A. (2021). On the security and privacy challenges of virtual assistants. Sensors, 21(7), e2312. https://doi.org/10.3390/s21072312

Since the purchase of Siri by Apple, and its release with the iPhone 4S in 2011, virtual assistants (VAs) have grown in number and popularity. The sophisticated natural language processing and speech recognition employed by VAs enables users to inter... Read More about On the security and privacy challenges of virtual assistants.