The QoS and privacy trade-off of adversarial deep learning: An evolutionary game approach

Deep learning-based service has received great success in many fields and changed our daily lives profoundly. To support such service, the provider needs to continually collect data from users and protect users’ privacy at the same time. Adversarial deep learning is of widespread interest to service providers because of its ability to automatically select privacy-preserving features that have less impact on the Quality of Service (QoS). However,...