In face recognition, several techniques have been developed over the years to
protect facial templates as well as facial sample data. With the rise of deep
learning techniques, face recognition as seen a revolution in terms of
achievable recognition accuracy. These developments also had impact on the
security techniques applied to facial data. We will demonstrate that early
template protection schemes do not provide security any longer in case deep
learning based recognition is used. Further, the security of existing selective
encryption schemes developed for facial data has to be re-considered in case deep learning
based recognition is used. Finally, we will show that learning-based
inpainting schemes can be used to successfully attack selectively encrypted
facial data.