An Approach for Privacy-preserving Mobile Malware Detection through Federated Machine Learning
This year’s ITasec24 was the event where CNR researchers presented their new technique for mobile malware detection using Federated Machine Learning. The process of malware detection has traditionally involved transmitting sensitive information to centralized servers leading to serious privacy and data insecurity concerns. In our approach, however, features are extracted directly on the mobile devices and later securely shipped to