173 citations · 226 across the 6 of their papers we have counts for
6 papers
DeepDyve: Dynamic Verification for Deep Neural Networks
Yu Li, Min Li, Bo Luo +2
Deep neural networks (DNNs) have become one of the enabling technologies in many safety-critical applications, e.g., autonomous driving and medical image analysis. DNN systems, how…
Region-Wise Attack: On Efficient Generation of Robust Physical Adversarial Examples
Bo Luo, Qiang Xu
Deep neural networks (DNNs) are shown to be susceptible to adversarial example attacks. Most existing works achieve this malicious objective by crafting subtle pixel-wise perturbat…
On Functional Test Generation for Deep Neural Network IPs
Bo Luo, Yu Li, Lingxiao Wei +1
Machine learning systems based on deep neural networks (DNNs) produce state-of-the-art results in many applications. Considering the large amount of training data and know-how requ…
On Configurable Defense against Adversarial Example Attacks
Bo Luo, Min Li, Yu Li +1
Machine learning systems based on deep neural networks (DNNs) have gained mainstream adoption in many applications. Recently, however, DNNs are shown to be vulnerable to adversaria…
I Know What You See: Power Side-Channel Attack on Convolutional Neural Network Accelerators
Lingxiao Wei, Bo Luo, Yu Li +2
Deep learning has become the de-facto computational paradigm for various kinds of perception problems, including many privacy-sensitive applications such as online medical image an…
Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks
Bo Luo, Yannan Liu, Lingxiao Wei +1
Machine learning systems based on deep neural networks, being able to produce state-of-the-art results on various perception tasks, have gained mainstream adoption in many applicat…