DeepAI AI Chat
Log In Sign Up

Security and Privacy Issues in Deep Learning

by   Ho Bae, et al.
Seoul National University

With the development of machine learning, expectations for artificial intelligence (AI) technology are increasing day by day. In particular, deep learning has shown enriched performance results in a variety of fields. There are many applications that are closely related to our daily life, such as making significant decisions in application area based on predictions or classifications, in which a deep learning (DL) model could be relevant. Hence, if a DL model causes mispredictions or misclassifications due to malicious external influences, it can cause very large difficulties in real life. Moreover, training deep learning models involves relying on an enormous amount of data and the training data often includes sensitive information. Therefore, deep learning models should not expose the privacy of such data. In this paper, we reviewed the threats and developed defense methods on the security of the models and the data privacy under the notion of SPAI: Secure and Private AI. We also discuss current challenges and open issues.


page 3

page 7

page 10

page 12


Deep Learning Application in Security and Privacy -- Theory and Practice: A Position Paper

Technology is shaping our lives in a multitude of ways. This is fuelled ...

Disentangling private classes through regularization

Deep learning models are nowadays broadly deployed to solve an incredibl...

PoTrojan: powerful neural-level trojan designs in deep learning models

With the popularity of deep learning (DL), artificial intelligence (AI) ...

Securing Input Data of Deep Learning Inference Systems via Partitioned Enclave Execution

Deep learning systems have been widely deployed as backend engines of ar...

Mediation Challenges and Socio-Technical Gaps for Explainable Deep Learning Applications

The presumed data owners' right to explanations brought about by the Gen...

Quality Monitoring and Assessment of Deployed Deep Learning Models for Network AIOps

Artificial Intelligence (AI) has recently attracted a lot of attention, ...

Privacy Meets Explainability: A Comprehensive Impact Benchmark

Since the mid-10s, the era of Deep Learning (DL) has continued to this d...