Security and Privacy Issues in Deep Learning: A Brief Review

Nowadays, deep learning is becoming increasingly important in our daily life. The appearance of deep learning in many applications in life relates to prediction and classification such as self-driving, product recommendation, advertisements and healthcare. Therefore, if a deep learning model causes false predictions and misclassification, it can do great harm. This is basically a crucial issue in the deep learning model. In addition, deep learning models use large amounts of data in the training/learning phases, which contain sensitive information. Therefore, when deep learning models are used in real-world applications, it is required to protect the privacy information used in the model. In this article, we carry out a brief review of the threats and defenses methods on security issues for the deep learning models and the privacy of the data used in such models while maintaining their performance and accuracy. Finally, we discuss current challenges and future developments. © 2020, Springer Nature Singapore Pte Ltd.