Data security issues in deep learning: Attacks, countermeasures, and opportunities

G Xu, H Li, H Ren, K Yang… - IEEE Communications …, 2019 - ieeexplore.ieee.org
Benefiting from the advancement of algorithms in massive data and powerful computing
resources, deep learning has been explored in a wide variety of fields and produced …

A review of deep learning security and privacy defensive techniques

MI Tariq, NA Memon, S Ahmed… - Mobile Information …, 2020 - Wiley Online Library
In recent past years, Deep Learning presented an excellent performance in different areas
like image recognition, pattern matching, and even in cybersecurity. The Deep Learning has …

Security and privacy issues in deep learning: a brief review

T Ha, TK Dang, H Le, TA Truong - SN Computer Science, 2020 - Springer
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 …

A survey on privacy inference attacks and defenses in cloud-based deep neural network

X Zhang, C Chen, Y Xie, X Chen, J Zhang… - Computer Standards & …, 2023 - Elsevier
Abstract Deep Neural Network (DNN), one of the most powerful machine learning
algorithms, is increasingly leveraged to overcome the bottleneck of effectively exploring and …

Secure and verifiable inference in deep neural networks

G Xu, H Li, H Ren, J Sun, S Xu, J Ning, H Yang… - Proceedings of the 36th …, 2020 - dl.acm.org
Outsourced inference service has enormously promoted the popularity of deep learning, and
helped users to customize a range of personalized applications. However, it also entails a …

Security and privacy issues in deep learning

H Bae, J Jang, D Jung, H Jang, H Ha, H Lee… - arXiv preprint arXiv …, 2018 - arxiv.org
To promote secure and private artificial intelligence (SPAI), we review studies on the model
security and data privacy of DNNs. Model security allows system to behave as intended …

Privacy and security issues in deep learning: A survey

X Liu, L Xie, Y Wang, J Zou, J Xiong, Z Ying… - IEEE …, 2020 - ieeexplore.ieee.org
Deep Learning (DL) algorithms based on artificial neural networks have achieved
remarkable success and are being extensively applied in a variety of application domains …

Machine learning security: Threats, countermeasures, and evaluations

M Xue, C Yuan, H Wu, Y Zhang, W Liu - IEEE Access, 2020 - ieeexplore.ieee.org
Machine learning has been pervasively used in a wide range of applications due to its
technical breakthroughs in recent years. It has demonstrated significant success in dealing …

Privacy in deep learning: A survey

F Mireshghallah, M Taram, P Vepakomma… - arXiv preprint arXiv …, 2020 - arxiv.org
The ever-growing advances of deep learning in many areas including vision,
recommendation systems, natural language processing, etc., have led to the adoption of …

A comprehensive review on deep learning algorithms: Security and privacy issues

M Tayyab, M Marjani, NZ Jhanjhi, IAT Hashem… - Computers & …, 2023 - Elsevier
Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …