Nov 21, 2019 · We first investigate the potential threats of deep learning in this area, and then present the latest countermeasures based on various ...
We first investigate the potential threats of deep learning in this area, and then present the latest countermeasures based on various underlying technologies, ...
This paper proposes SecureNet, the first verifiable and privacy-preserving prediction protocol to protect model integrity and user privacy in DNNs, ...
The authors focus on data security issues in deep learning. They investigate the potential threats of deep learning in this area, and then present the latest ...
Nov 1, 2019 · We first investigate the potential threats of deep learning in this area, and then present the latest countermeasures based on various ...
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This survey attempts to systematically discuss and summarise the recent advanced security solutions for deep learning models through watermarking, encryption ...
Nov 21, 2024 · In this chapter, a comprehensive survey of security and privacy challenges in deep learning is presented. The security attacks such as poisoning ...
In this work, we introduce a survey about the attacks that could be launched against the shared models and the countermeasures that could be taken to preserve ...
Adversarial attacks occur when an attacker makes small, imperceptible modifications to input data, causing the model to make incorrect predictions. For instance ...
Dec 9, 2024 · [15] analyzes security issues of machine learning models, categorizing attacks like training data poisoning, backdoors, adversarial examples ...