Assuring privacy of AI-powered community driven Android code vulnerability detection
Conference paper
Senanayake, J., Kalutarage, H., Piras, L., Al-Kadri, M.O. and Petrovski, A. 2024. Assuring privacy of AI-powered community driven Android code vulnerability detection. 3rd International Workshop on System Security Assurance. Bydgoszcz, Poland 19 - 20 Sep 2024
Type | Conference paper |
---|---|
Title | Assuring privacy of AI-powered community driven Android code vulnerability detection |
Authors | Senanayake, J., Kalutarage, H., Piras, L., Al-Kadri, M.O. and Petrovski, A. |
Abstract | The challenge of training AI models is heightened by the limited availability of data, particularly when public datasets are insufficient. |
Keywords | Android code vulnerability; federated learning; differential privacy; data scarcity; artificial intelligence |
Sustainable Development Goals | 9 Industry, innovation and infrastructure |
Middlesex University Theme | Creativity, Culture & Enterprise |
Research Group | MDX Software Engineering, Theory & Algorithms (SETA) Reseach Group |
Conference | 3rd International Workshop on System Security Assurance |
Publication process dates | |
Accepted | 21 Jul 2024 |
Deposited | 09 Oct 2024 |
Output status | Accepted |
Language | English |
https://repository.mdx.ac.uk/item/1qz83x
Restricted files
Accepted author manuscript
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